Miracle-dz/UniFAR-FTUs huggingface dataset:
Interaction of aerosol particles with low-level , warm , precipitating stratiform clouds

It has been known for many years that clouds developing over the continents differ substantially in their precipitation efficiency from clouds developing under maritime conditions. The radically different cloud condensation nuclei (CCN) size distributions and composition play a clear role in precipitation development, particularly in warm clouds. The effect of aerosols on cloud microphysics is significant and occurs on a global scale (Breon et al., 2002). Enhanced CCN concentrations that could be produced both through natural or anthropogenic processes would be expected to inhibit rain production (Radke et al., 1989; Durkee et al., 2000). However, modelling studies (Johnson 1982; Lahave and Rosenfeld, 2003) and recent observations (Rosenfeld et al. 2002) show that when giant CCN are ingested into non-precipitating clouds the precipitation rates are restored. Feingold et al. (1999) investigated the impact of giant and ultragiant CCN on drizzle formation in stratocumulus using a number of different models. They found that at low CCN concentrations, drizzle is often active and the addition of giant CCN has little impact. At higher CCN concentrations, drizzle development is slow and giant CCN has great potential for enhancing precipitation.
Performance of Biometrics : False Acceptance Rate ( FAR ) False Rejection Rate ( FRR ) Image Classification Techniques : SVM Classifier K-Nearest Neighbour Classifier Naive Bayes Decision Trees

Now a days, Security demands are increasing in networked society. With these increases in biometric systems for accurate user authentication are becoming more popular. Iris Recognition System is one of the most popular authentication approach based on Iris of an individual. Every Iris has fine unique texture and does not change overtime. This project proposes a new iris recognition system based on feature level fusion using PCA to improve speed and accuracy of authentication. The iris textures are extracted from 2DGabor filters and Haar wavelet. In this textures are fused and then used to identify genuine users. In order to classify the extracted features process this project is using different classification techniques like KNN, Decision Trees, Multilayer Perceptron, Support Vector Machine (SVM) and Navie Bayes techniques. The proposed Iris recognition system is evaluated basing on Equal Error Rate using FAR and FRR.
Simple, but Therefore Clever Idea – An Effective Dendrological Inventory Process for Landscape Architecture and Design Projects

Good solutions do not necessarily need to be highly complicated or costly. This article introduces a simple way to improve the economic efficiency of the digitalization of dendrological inventory data. The application developed in this study makes it possible to effectively link drawing and database programmes so that data can be utilized in both CAD (computer-aided design) and GIS (geographic information system) systems. Furthermore, no additional investments in training or technology are necessary, as this application uses software already featured in most plan design offices.
The Target Location Ranging Based on Monocular Vision of Mobile Robot

In order to achieve the positioning of target objects ranging work for the realization of a mobile robot with monocular vision,the paper proposes a fusion-based the monocular visual geometric ranging algorithm.The method utilizes a circular curve fitting method optimized for the monocular ranging method resulting program data,to overcome the impact due to changes in the external environment,as well as an error generated when the reference identification ranging positioning accuracy,and by experiment verify the feasibility of such a fusion.
The Analysis of Reduced Audit Quality Behavior : The Intervening Role of Turnover Intention

Reduced audit quality behavior is an important issue for public accounting firms. Reduced audit quality behavior is a form of dysfunctional audit behavior that has a negative effect on users’ confidence in financial statements. This study aims to examine the antecedents of turnover intention on reduced audit quality behavior. Specifically, this study investigates the effects of locus of control and organizational commitment on reduced audit quality behavior through turnover intention. Data is analyzed based on 97 responses from auditors who work for public accounting firms in Sumatera Island, Indonesia. The results from the PLS analysis reveal that the external locus of control, weak organizational commitment, and a high turnover intention lead to reduced audit quality behavior. In addition, the result also suggests that the effect of locus of control and organizational commitment on reduced audit quality behavior is indirectly influenced by turnover intention. JEL Classification: H83, M40, L15
Personality Analysis and Prediction of Social Network Users

Personality is an overview of human individual characteristics.In a scientific way,it describes how one person differs from another.Personality not only highly correlates with people's real world behavior,but also correlates with the people's virtual world behavior on social network.Reachable and computable online behavior information makes it possible to analysis personality in large-scale and provides personality theory with unprecedented fuel for popularization and application.Based on the statements of standards and methods of personality measurement,we briefly discussed latest researches about personality analysis and personality prediction of social network users.Moreover,we lay our fingers on the challenges of methods for forecasting users' personality.Then we analyzed several possible modes of application of personality theory in social network.Finally,crucial problems to be solved and prospects of the future application are also stated.
A Study of Biblical Kinds Using 62 Species of Mice

 Each mouse species/kind remains distinct due to the complexity of breeding mechanisms which are hardwired in the DNA; these mechanisms, or instincts, cause mice to be selective in choosing breeding partners. Mice can read each other as though they displayed bar codes (Beynon and Hurst 2003 and 2004) which allows them to chose a mate within their species, but yet not too closely related as to cause genetic health problems (Sherborne et al. 2007; Jiménez et al. 1994). The details of these selective breeding instincts help solve the mystery of how the Creator mechanized creatures, at least the mice, to reproduce after their kinds.  This study has also provided insight as to which mouse kinds were on the Ark: our conclusion is that most of what are considered modern-day "species" are also Biblical "kinds. " Those considered sub-species must be evaluated individually using DNA and breeding instincts to determine whether they are individual kinds or races of the same kind.
The association of statin use with risk of kidney , bladder and prostate cancer : a systematic review and meta-analysis of cohort studies

Background: Emerging evidence suggested that statins might decrease the risk of cancer. This study examined the associations of statin use with the risk of main urologic cancer, and a sex-specific relationship between statin use and the risk of cancer was also evaluated. Methods: A literature search in PubMed, MEDLINE, and Web of Science databases was undertaken through February 2017 evaluating the association between statin use and risk of main urologic cancer. Pooled relative risk (RR) estimates and 95% confidence intervals (CIs) were calculated using random-effects model. In addition, we also estimated RR ratios (RRRs) between men and women. Results: A total of 30 cohort studies contributed to the analysis. The results of the meta-analysis showed that statin users did not experience a significantly decreased risk for developing kidney cancer in both women and men (RR = 1.01, 95% CI = 0.91-1.11). Statin use in women had the reduced tendency for the risk of kidney cancer, but statin use in men had an adverse tendency for the risk of this disease (Women: RR = 0.98, 95% CI = 0.85-1.12; Men: RR = 1.09, 95% CI = 0.99-1.19). The pooled multiple-adjusted women-to-men RRR for incident kidney cancer was 0.90 (95% CI = 0.75-1.05). Compared to non-users, statin users yielded the reduced risk of total, advanced, high-grade, and low-grade prostate cancer by approximately 12%, 18%, 14% and 7% (Total: RR = 0.88, 95% CI = 0.84-0.93; Advanced: RR = 0.82, 95% CI = 0.70-0.95; High-grade: RR = 0.86, 95% CI = 0.68-0.99; Low-grade: RR = 0.93, 95% CI = 0.86-0.99), whereas the significant effects were not observed for bladder cancer (RR = 1.03, 95% CI = 0.881.17). Conclusions: The results found that sex difference could affect the association of statin use with the risk of kidney cancer. The statin use could reduce the risk of prostate cancer but no associations were found between statin use and bladder cancer.
Evaluation components of the heart rate kinetics for assessment cardiac adaptation during rehabilitation

The purpose of the study was assessment of the cardiovascular adaptation to the workload and physical training by analysis of the heart rate kinetics and dynamics of power spectrum components in healthy subjects and ischemic heart disease patients during rehabilitation. The contingent of study was 20 healthy subjects and 97 patients post-myocardial infarction (74 without chronic heart failure and 23 with chronic heart failure symptoms). Multistage bicycle ergometry or spiroergometry and computerized analysis of heart rate variability during active orthostatic, symptom-limited workload tests and recovery period after test were performed. The rhythmogram at 50W of the workload, and during bicycle (Kettler) training and recovery period was analyzed and the time constant (τ) of the exponential function (by using Proni method), coefficients of amplification, rapidity as well as heart rate (HR) power spectral components (σVLF, σLF, σHF) were evaluated. Heart rate kinetics response time constant to the low-level (τ50W) workload (30.3 vs. 19.3 s) and during recovery period (40 vs. 45.6 s) was delay in post-myocardial infarction patients, especially in those with CHF and low physical capacity as compared with healthy subjects. Heart rate responses (τ50W) correlated with baseline HR autonomic control components (σLF, r=-0.25, ∆RRB%, r=-0.24, RRB, r=0.23,) and with physical capacity (r=-0.30). In CHF patients the delay HR response to the workload and during recovery correlated with expressed ventilatory response (VE/VCO2, r=0.60) in this group. Positive dynamic of HR kinetics components (τ=37.1 vs. 34.6 s) and power spectrum characteristics after low intensity bicycle training procedure and during recovery (τ=42.4 vs. 39.9 s) period was observed. The faster HR reaction to the physical stressor after 3-weeks bicycle training correlated with positive dynamics of σHF (r=-0.35). The HR power spectrum components during bicycle training changed favorably (σVLF, 15.2 vs. 16.3 ms; σLF, 8.2 vs. 9.4 ms; σHF, 8.8 vs. 9.4 ms) too. Conclusions. Analysis of the heart rate kinetics components and power spectrum data during exercise provides a new possibility evaluation of the cardiac adaptation to the workload and physical training procedures in ischemic heart disease patients during rehabilitation.
geism , honesty , and trust

Age-based discrimination is considered undesirable, yet we know little about age stereotypes and their effects on honesty and trust. To investigate this aspect of ageism, we presented older adults (over age 50) and younger adults (under age 25) with incentivized belief elicitation tasks about anticipated interaction behaviors and then a series of same, different, and unknown-aged group interactions in a strategiccommunication game. All adults shared consensual stereotypes about uncooperative younger adults and cooperative older adults that demonstrated “wisdom of crowds”. While the out-group was consistently stereotyped as relatively different and more dishonest and suspicious than observed to be, the in-group was neither consistently stereotyped more accurately nor treated with more honesty and trust. Younger adults earned more by acting dishonestly with older adults and older adults earned less by trusting younger adults (despite stereotyping them as dishonest). We discuss how ageism is relevant to intergenerational cooperation in an aging society. eywords: geism ntergenerational interaction tereotype
1 Assessment and Suggestions for Rational Energy and 2 Environment Tax Policy in South Korea 3

Energy and Environment Tax is used globally as a means of environment policy. Energy 11 and Environment tax plays an important role as a driving force for the conversion to 12 environmentally friendly energy. The basic tax principles considered in the design of energy and 13 environmental taxation increases the efficiency of policy instruments. The purpose of this study is 14 to evaluate South Korea’s energy and environmental taxation based on tax principles, namely, 15 equity, efficiency, simplicity, flexibility, and accountability and to suggest directions for 16 improvement. This study applied a methodology that provides policy implications, such as 17 reviewing existing literature and comparing energy and environmental taxes. Results of this study 18 show that South Korea’s energy and environmental taxation is negative in terms of equity, 19 simplicity, and accountability. South Korea’s current energy and environmental tax is regressive to 20 income classes and complex tax structures and it does not objectively measure the impact of energy 21 and environmental taxation. However, energy and environmental taxation is evaluated positively 22 in terms of efficiency and flexibility because it meets the greenhouse gas reduction policy and 23 operates a flexible tax rate. The results of this analysis provide policy implications for reorganizing 24 South Korea’s energy and environmental taxation. 25
Natural radioactivity effects on the scaler operation mode of the ARGO-YBJ detector

ARGO-YBJ is an extensive air shower detector located at the Yangbajing Cosmic Ray Laboratory ( 4300 m a.s.l., 606 g/cm atmospheric depth). It is made by a single layer of Resistive Plate Chambers (RPCs, total surface∼ 6700 m) grouped into 153 units called ”cluster”. The lower energy threshold of the experiment is obtained using the ”scaler operation mode”, i.e. counting all the particles hitting the detector without measurement of the energy and arrival direction of the primary cosmic rays. For each cluster the signals generated by these particles are put in coincidence in a narrow time window (150 ns) and read by four independent scaler channels, giving the counting rates of≥ 1, ≥ 2, ≥ 3 and ≥ 4 hits. The study of these counting rates has given unexpected results: while the MC simulations can account fairly well for the coincident counting rates, the expectation for channel≥ 1 is about half of the measured value. Moreover as discuss in [2], the regression coefficient with the atmospheric pressure for channel≥ 1 is also about half of the value measured for the coincident counting rates: seemingly half of these counts did not cross the atmosphere. A measurement of the radioactivity of the ground below the detector and a MC simulation to estimate the contribution from this local effect on our counting rates is presented and discussed.
Supplementary Material for Does Learning Specific Features for Related Parts Help Human Pose Estimation ?

Fig. 1 and Fig. 2 respectively display some pose estimation results obtained by an eight-stack PBN on the MPII [1] and LSP [2] datasets. We collect a few short videos from YouTube to test whether our approach can generalize beyond the MPII and LSP datasets. They contain different styles of dance performances, e.g., Latin, hip hop, ballet and contemporary. A Faster RCNN [3, 4] is utilized to locate the dancers. Then we apply an eight-stack PBN trained on the MPII dataset for frame-by-frame pose estimation (single-scale testing with flipping). No pose tracking was performed. Using one NVIDIA TITAN X GPU (12 GB memory), it can infer the poses of 23.74 persons per second. Fig. 3 shows our results on some frames. The file ’demo with sound.mp4’1 demonstrates the pose estimates obtained by our approach on some video clips. Most of them have been sped up by a factor of 1.5 or 2 to shorten the demo.
Sentence Alignment for Biomedicine Texts Based on Gaussian Mixture Model

A bilingual lexicon of biomedical terms plays an important role in biomedical cross-language information retrieval.Sentence alignment is the first step to build a bilingual lexicon.The Gaussian mixture model and transfer learning are applied to align sentences.The basic idea is to consider the sentence alignment as a classification task,which can be solved by the Gaussian mixture model classifiers based on the anchor information included in medical literature abstracts.At the same time,the sentence alignment model is built by combining biomedicine literature abstracts with New Concept English corpora,and it aims at applying transfer learning to train the length features and transfer them to the model.The experiments show it improves the performance of the sentence alignment model.
Adaptation Model for Multi-grade Classrooms

Multi-age and multi-grade teaching classrooms (MGTCs) have a long history in the educational systems of the Asia-pacific countries. Often, this type of pedagogic event can be seen in the rural and remote areas of the countries, generally. The people who have taught in those classrooms have found the most difficulties in the classroom and teaching-learning management. At the same time, the time and voluminous content of the textbooks puts most of MGTCs teachers into trouble. These difficulties may result to school leaving and more drop out. However, for me the main problem of MGTCs is their curriculums. Almost Asia-Pacific educational systems implement mono-grade curricula in the MGTCs. While, MGTCs require different types of curricula because of different nature of the classrooms. Accordingly there is a need for special curriculum to set an effective teaching-learning condition. But developing a new curriculum for the sake of MGTCs may exceed expenditures and take more time from the curriculum makers of the educational systems. For the purpose of solving the above mentioned problems/difficulties and promoting the quality of teaching-learning in the MGTCs, we have found adapting the national curriculum for MGTCs as a short cut. Therefore in this paper, we will try to introduce the solution in the framework of a conceptual model to adapting national curriculum for
Building Taxonomies based on Human-Machine Teaming: Cyber Security as an Example

Taxonomies and ontologies are handy tools in many application domains such as knowledge systematization and automatic reasoning. In the cyber security field, many researchers have proposed such taxonomies and ontologies, most of which were built based on manual work. Some researchers proposed the use of computing tools to automate the building process, but mainly on very narrow sub-areas of cyber security. Thus, there is a lack of general cyber security taxonomies and ontologies, possibly due to the difficulties of manually curating keywords and concepts for such a diverse, inter-disciplinary and dynamically evolving field. This paper presents a new human-machine teaming based process to build taxonomies, which allows human experts to work with automated natural language processing (NLP) and information retrieval (IR) tools to co-develop a taxonomy from a set of relevant textual documents. The proposed process could be generalized to support non-textual documents and to build (more complicated) ontologies as well. Using the cyber security as an example, we demonstrate how the proposed taxonomy building process has allowed us to build a general cyber security taxonomy covering a wide range of data-driven keywords (topics) with a reasonable amount of human effort.
Fast and stable color normalization of whole slide histopathology images using deep texture and color moment matching

Whole Slide Images (WSIs) are prone to color variations due to differences in fixation and staining conditions of tissue samples, as well as the scanning process. Such variations can adversely affect the image analysis, and in this paper, we propose a novel, fast and stable color normalization algorithm for WSIs called CONTEMM (COlor Normalization using deep TExture and color Moment Matching). CONTEMM estimates color transformation matrix based on pairs of reference and source patches with similar tissue components in the respective WSIs, which are selected using deep texture representations. The color transformation matrix is estimated quickly by fitting the second moment about white color. Performance of CONTEMM algorithm was evaluated using histopathology images from different slide scanners and TCGA (The Cancer Genome Atlas) datasets. CONTEMM was shown to outperform the other methods; Reinhard, Vahadane, and Macenko, in terms of variation (stability), accuracy, and computation time.
A New Personalized Recommendation Algorithm of Combining Content-based and Collaborative Filters

Personalized recommendation service system is based on user history record and recommendation algorithm to provide personalized information or commodities for different users which they may be interested in.According to the problems exist in collaborative filtering recommendation algorithm and content-based recommendation algorithm respectively,this paper presents a recommendation algorithm called ASVD that alternately merge and optimized project-latent topic matrix which is from the process of using singular value decomposition algorithm to decompose the project-keywords matrix based on project content and user ratings users-project matrix to eliminate the noise to improve the accuracy of the recommendation.Experiments show that the new hybrid algorithm ASVD can significantly improve recommendation accuracy.
Machine scheduling and Lagrangian relaxation

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A COMSOL Model of Damage Evolution Due to High Energy Laser Irradiation of Partially Absorptive Materials

In this paper we present a numerical model of the transient heat transfer and thermochemical damage evolution in an IR opaque material using COMSOL Multiphysics. The model is applied to a carbon black loaded PMMA (polymethyl-methacrylate), using material properties available in the literature supplemented with experiments. This variant of PMMA was chosen because it is homogeneous, isotropic, and the decomposition from solid to gas is relatively straightforward to characterize. The incident high energy laser beam is modeled as a Gaussian heat flux. The beam parameters used for this study are selected to mimic that of a Nd:YAG high energy laser with a wavelength of 1070nm, an output power of 110W, and a spot size with a 5.5mm beam diameter. At this wavelength, NIRS/FTIR experiments demonstrate that PMMA absorbs slightly more than half of the incident laser energy. PMMA was experimentally observed to vaporize from 310°C to 475°C via differential scanning calorimetry. The temperature range and endothermic phase change from solid to gas is incorporated in the COMSOL model. Rather than use an adaptive mesh , material removal (or ablation) is captured using temperature and phase dependent material properties. The model captures vaporization material removal by appropriately varying the thermal conductivity and density of the PMMA at the vaporization temperature. The model results are compared to experiments on carbon-laden PMMA.