Miracle-dz/UniFAR-FTUs huggingface dataset:
Bioaccumulation of Heavy Metals by Selected Plant Species from Uranium Mining Dumps in the Sudety Mts

Concentrations of the heavy metals Cd, Pb, Cu, ni, Mn, zn and Fe in soils of uranium-bearing dumps (Sudety Mts. Sw Poland, the dumps containing a high proportion of polymetallic minerals), as well as in two tree species (Salix caprea L., Betula pendula Roth.) and a shrub (Rubus idaeus L.), which frequently occur in this area, in spite of being disturbed by mining activities in the past. The accumulation ratio values of heavy metals were calculated. it was revealed that all the species examined, especially the tree species, accumulated high concentrations of heavy metals, above the average values given for plants in literature. R. idaeus generally exhibited the lowest concentrations of heavy metals except Mn, while S. caprea accumulated the highest levels of Cd exhibiting the greatest accumulation capability for this metal within all the examined dumps. There is a potential of using the examined plants in the monitoring of heavy metals in the environment on the basis of a significant correlation between heavy metal content of foliage and soil.
Reducing the loss of color and details in single image defogging

In order to avoid the problem that the color distortion and the details are not obvious, this paper presents an improved defogging algorithm. It uses the dark channel prior to estimate the atmospheric light and the transmission and proposes a new gradient domain filtering to refine the transmission. Then, the intensity compensation is used to enhance the image color information. At the same time, the atmospheric light value is estimated and boundary constrains is used to roughly estimate the transmission, and, weights is added to define the transmission. So the scene transmission of both is refined, the image is reduced by atmospheric scattering model and two images are fused with the fusion strategy. The fusion of image uses the auto white balance to fine tune to get the final image. According to the experimental results, the algorithm effectively solves the problem of color distortion and loss of detail information in the defog image.
Full – body Tactile P 300 – based Brain – computer Interface Accuracy Refinement

In this study we report results of a classification accuracy performance comparison for a novel full– body tactile P300–based brain–computer interface (BCI) paradigm. In the discussed BCI experiments six spatial vibrotactile stimulus patterns are given to the user body entire back and limbs. The acquired somatosensory ERP signals are classified for the BCI purposes using a step– wise linear discriminant analysis (SWLDA), linear and non–linear (Gaussian kernel) support vector machines with features drown from an electroencephalogram (EEG) preprocessed signals. The aim of the current project is to determine the most suitable classification methods for a tactile P300–based BCI paradigm and to affirm a validity of vibrotactile stimulus patterns for the user full–body– based interfacing paradigm. The best grand mean averaged accuracies for each classification method result in rates of 57.48% for SWLDA, 58.5% for linear and 59.83% for non–linear SVMs, respectively. Keywords— Brain–computer interface (BCI); EEG; tactile P300–based BCI; machine learning.
Sliding Mode Control with RBF Neural Network for Two Link Robot Manipulator

Nonlinear control techniques are applied on mechanical systems namely two link robot manipulator to study the effect of the controllers on the tracking performance of the two system. A design of sliding mode control(SMC) for the position tracking of two link robot manipulator based on the sliding mode control technique and the Lyapunov stability theory is carried out to eliminate the perturbation and asymptotical stability can be achieved when the system is subjected to the sliding mode. A sliding mode control method based on RBF(radial basis function) neural network is addressed which has the capability of learning uncertain control actions shown by the several industrial robots. In RBFNN-SMC method the algorithm for tuning the parameters are extracted from the RBF function. The comparative study is done based on the evaluated parameters for the system
Native Listeners' Shadowing of Non-native Utterances as Spoken Annotation Representing Comprehensibility of the Utterances

Recently, researchers’ attention has been paid to pronunciation assessment not based on comparison between learners’ utterances and native models, but based on comprehensibility of the utterances [1, 2, 3]. In our previous studies [4, 5], native listeners’ shadowing was investigated and shown to be effective to predict comprehensibility perceived by listeners (shadowers). In this paper, native listeners’ shadowings are viewed as spoken annotations that can represent comprehensibility. In [4, 5], to predict comprehensibility of a non-native utterance, the GOP scores of its corresponding native listeners’ shadowings were calculated by using a DNN-based ASR front-end. Generally speaking, annotations are prepared manually and, even when some techniques are used for annotations, only stable and reliable techniques should be used. In this paper, a simpler, stabler, and more reliable method to derive comprehensibility annotations was proposed. After native listeners’ shadowing, they are asked to read aloud the sentence intended by the learner. Reading is the most prepared speech and shadowing is probably the least prepared speech. DTW between the two utterances is supposed to be able to quantify and predict comprehensibility or shadowability perceived by the shadowers. In experiments, DTW between shadowings and readings shows higher correlation than the GOP scores of shadowings.
GPU-Based Liquid Crystal Display Processing Platform A Real-time CUDA Implementation of Local Backlight Dimming and Glare Illusion for LC-Display

Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration.
LEARNING OUTCOME OF MATHEMATICS AND SCIENCE : FEATURES OF INDONESIAN MADRASAH STUDENTS Kusaeri Universitas

This study aims to analyze the learning outcome of mathematics and sciences in the Indonesian National Examination from 2015 to 2018 of MTs (Islamic secondary school). The results of the analysis are used as the basis for making alternative policy as a possible way to improve the quality of mathematics and science learning. With the sample size of 360, 371 MTs students in East Java, the achievement was measured by using 40 multiple choice questions with each having four answer options. Split-plot and latent profile analysis of the data show that there was a consistent decrease in the achievement of mathematics and sciences of the moderate group of MTs from 2015 to 2018 with a dramatic drop in mathematics and tendency to drop for science. The fundamental implication of these findings is that there is a need for learning innovations to improve mathematics and science learning outcomes for 21st century learning. The findings can also provide data support for decision making for the revision of the mathe-matics and science curriculum and can be further used as empirical evidence for the developed countries in finding ways to improve the quality of mathematics and science learning outcomes for 21st century learning, in particular, to assist the developing countries such as Indonesia.
The Effects of Grazing Livestock on Cowpea unguiculata ) and S

The study assessed the effect livestock (cattle, goat, sheep, domestic fowls) extensive system on cowpea and soybean production in Abuja, Nigeria. For effective coverage of the multi-stage sampling technique was adopted while structured questionnaires were used for data collection. A total of 410 small-scale farmers were interviewed in Area Councils (Kwali, Kuje, Gwagwalada, Abaji) analysed using a three-way mixed analysis of variance (ANOVA). The result indicated that the effects of grazing livestock on cowpea and soybean production significantly ( < .01) varied from one location (area council) to another with Kwali Area Council as the most affected while Abaji was the least. The mean responses indicated that the grazing livestock on cowpea and soybean . 01) differed. Also, the extent of crop damage significantly ( < .01) depended on the type of grazing animal. Mean separation result showed that the most affected cowpea with cattle and goat/sheep causing the major damages while domestic fowls had the least effect. affected cowpea and soybean farmers lost an average of N5,310 ($27 US dollars) and N3,453 respectively to grazing livestock in 2014 capable of eliciting crisis between livestock owners and the crop farmers. Majority (44.88%) of the farmers reported that the animals affected the crops mostly and during harvesting (34.14%). Generally, the findings showed that grazing livestock affected cowpea and soybean production in the study area but the effects depended location, livestock type and crop type. Hence, any approach to address the problem of grazing livestock on the crops should take cognizance of these variables.
Decision-and Policy-Making : An Illustrative Case in Primary Healthcare Conceptual and Methodological Challenges in Producing Research Syntheses for

This article presents and discusses five challenges encountered in conducting a knowledge synthesis on primary healthcare, commissioned by the Canadian Health Services Research Foundation. These challenges are (1) conceptualizing, defining and operationalizing complex interventions; (2) integrating quantitative and qualitative studies and assessing strength of evidence; (3) incorporating expert opinions and decision-makers’ viewpoints; (4) producing timely results; and (5) presenting the results in a concise yet understandable form. We also propose methods and operational tools to deal with these issues, particularly regarding integration of qualitative and quantitative evidence and incorporation of expert opinions into syntheses. The major challenge of the synthesis was to provide pertinent and useful information for decisionand policy-makers, while maintaining an acceptable level of scientific rigour. This approach seems promising for knowledge syntheses, which sustain a deliberative process that leads to more enlightened decision and policy-making.
Auto-tuning of Hyperparameters of Machine Learning Models

Most machine learning models use hyperparameters empirically de ned in advance of their training processes. Even a classic machine learning model, so-called multilayer perceptrons, has a lot of hyperparameters. In the case of using such a model for a classication problem, one di culty is that the achieved classi cation accuracy could drastically change every time even if the same hyperparameter values are used. Hence, it is challenging to determine an appropriate hyperparameter con guration at a low cost. The same problem has so far been discussed in the research eld of software performance automatic tuning, or auto-tuning. Therefore, in this work, we employ one of such auto-tuning mechanisms, ATMathCoreLib, for auto-tuning hyperparameters of machine learning models, and discuss the feasibility of using such technologies in the eld of machine learning.
Lawrence Berkeley National Laboratory Recent Work Title ROBOT : A Tool for Automating Ontology Workflows

Background: Ontologies are invaluable in the life sciences, but building and maintaining ontologies often requires a challenging number of distinct tasks such as running automated reasoners and quality control checks, extracting dependencies and application-specific subsets, generating standard reports, and generating release files in multiple formats. Similar to more general software development, automation is the key to executing and managing these tasks effectively and to releasing more robust products in standard forms. For ontologies using the Web Ontology Language (OWL), the OWL API Java library is the foundation for a range of software tools, including the Protégé ontology editor. In the Open Biological and Biomedical Ontologies (OBO) community, we recognized the need to package a wide range of low-level OWL API functionality into a library of common higher-level operations and to make those operations available as a command-line tool. Results: ROBOT (a recursive acronym for “ROBOT is an OBO Tool”) is an open source library and command-line tool for automating ontology development tasks. The library can be called from any programming language that runs on the Java Virtual Machine (JVM). Most usage is through the command-line tool, which runs on macOS, Linux, and Windows. ROBOT provides ontology processing commands for a variety of tasks, including commands for converting formats, running a reasoner, creating import modules, running reports, and various other tasks. These commands can be combined into larger workflows using a separate task execution system such as GNU Make, and workflows can be automatically executed within continuous integration systems. Conclusions: ROBOT supports automation of a wide range of ontology development tasks, focusing on OBO conventions. It packages common high-level ontology development functionality into a convenient library, and makes it easy to configure, combine, and execute individual tasks in comprehensive, automated workflows. This helps ontology developers to efficiently create, maintain, and release high-quality ontologies, so that they can spend more time focusing on development tasks. It also helps guarantee that released ontologies are free of certain types of logical errors and conform to standard quality control checks, increasing the overall robustness and efficiency of the ontology development lifecycle.
Efficient ACC using Binary Coding Stream for Color Descriptor

Auto color correlation (ACC) technique is proposed to enhance the availability of image content to capture local spatial correlation among different colors rather than using color correlogram technique. An ACC technique can reduce the size of color correlogram from O(m2d) to O(3md) . However, it is still not applicable for query purposes in a large image database and especially in a real time image processing. This paper presents an application of a well studied image coding technique, namely block truncation coding (BTC), to reduce the storage space required and to increase the speed of retrieval for ACC algorithm. When an ACC is represented by using a binary matrix (BTC), it does not reduce the number of bins. Therefore, a decimal conversion of the binary stream in each row of the matrix is presented. The experimental results obtained from the two different techniques, Binary Coding Stream Conversion (BCSC) and ACC techniques, are investigated.
MUTUAL EXCLUSION ROLE CONSTRAINT MINING BASED ON WEIGHT IN ROLE-BASED ACCESS CONTROL SYSTEM

Role-based access control (RBAC) is the most popular access control model at present, and has become the norm in many applications. Role engineering is a way to migrate a non-RBAC system to an RBAC system. However, none of the role engineering work has employed mutual exclusion role constraint mining based on weight to our knowledge although constraint is an important aspect of RBAC, thus providing the motivation for this work. In this paper, we first define the weight of permission by considering the attributes of user and permission, and then study how to generate mutual exclusion role constraint based on weight. Finally, experiments on performance study prove the superiority of our approach.
HIGHWAY ELEVATION DATA SMOOTHING USING LOCAL ENHANCEMENT MECHANISM AND BUTTERWORTH FILTER

Highway elevation is an important factor for performing quantitative and qualitative analysis of traffic safety, traffic operation and management. Google Earth provides public accessible highway elevation data which is deemed as a credible elevation source by many researchers and transportation practitioners. However, the raw elevation dataset, extracted from Google Earth, shows multiple types of outliers. Hence, we presented a local enhancement mechanism integrated with Butterworth filter to remove noises in the raw elevation data. Segment’s elevation under local extrema grades was adjusted by the local enhancement mechanism before the Butterworth smoothing process. This operation helped reduce the side effect of over-smooth phenomenon for the Butterworth filter. Elevation data for three typical freeway segments, with some typical categories of outliers, has been analyzed and smoothed. The smoothing results provided evidence that the proposed smoothing model was good at reducing the noises in the raw elevation data. This research can help traffic regulators, administrative departments and field researchers construct trustable and large-scale elevation dataset for nationwide highways.
PRODUCTION OF BROAD AND NARROW FOCUS IN GERMAN | A STUDY APPLYING A QUANTITATIVE MODEL Hansjorg Mixdor

The present paper examines the in uence of broad and narrow focus on the F0 contours of short German utterances. The contours were analyzed using the Fujisaki-model in order to yield quantitative results. In utterances of statements, narrow focus boosts the accent command amplitude assigned to the focused item, which generally exhibits a clear accent peak. Secondary accents are reduced. The broad focus condition is characterized by accent merging. In utterances of questions, little in uence of the focus condition on the accent command amplitude was observed which may be assigned to the fact that questionnal accents generally exhibit higher accent command amplitudes than statementnal ones. The phrase command amplitude in narrow focal conditions is reduced compared with the broad focal condition.
EVALUATION OF ACUTE TOXICITY OF THIAMETHOXAM IN ALG ERIAN HONEYBEE APIS MELLIFERA INTERMISSA AND APIS MELLIFERA SAHARIENSIS

Thiamethoxam [3-(2-chlorine-1, 3-thiazole-5-ylmethy l)-5-methyl-1,3,5-oxadiazinan-4-ylidene(nitro) amin e], a systemic insecticide of the group of neonicotinoids with a large spectrum of action at low concentrati ons. It is used in the control of sucking insects and some chewing species , b cause of its excellent absorption and transloca tion in plants. The acute toxicity of contact and oral applications two Apis mellifera subspecies, Apis mellifera intermissa nd Apis mellifera sahariensis was investigated. In all toxicological studies, eac h dose included three cages of 20 individuals and each study was replicated three times. The dose–mor tality relation revealed directly proportional rela tionship between the administered dose of thiamethoxam and mortality obs erved. The mortality is reached maximum at 24 hours after treatment with doses above 50 ng / bee after oral application . Response kinetics showed classic kinetics. The hi gher the dose of thiamethoxam and faster is high mortality appears. After oral intoxication, the LD50 values of thiamet hoxam at 24h were about 12,3 ng/bee for A. m. intermissa and 13.3 ng/bee for A. m. sahariensis. After contact application, the LD50 values at 24 h were approximately 26 ng/bee for A. m. intermissa and 43.3 ng/bee for A. m. sahariensis.
Dialectical Behavior Therapy ( DBT ) during Treatment of Childhood Anxiety Disorders : A Pilot Study

Supplementing Art Therapy with Cognitive Behavioral Therapy (CBT) and Dialectical Behavior Therapy (DBT) during Treatment of Childhood Anxiety Disorders: A Pilot Study Rachel Cecil A qualitative research study presents a thorough examination of one therapist’s methods of supplementing art therapy with cognitive behavioral therapy (CBT) and dialectical behavior therapy (DBT) during the treatment of children impaired by a variety of anxiety disorders—i.e. generalized anxiety disorder (GAD), obsessive-compulsive disorder (OCD), and posttraumatic stress disorder (PSTD). A review of the existing literature was used to inform the current study. The researcher created an exploratory case study, through the utilization of a pilot study, to gain a better understanding of the topic from an expert in these therapeutic fields. Through the gathering of data and analysis, the findings suggest that supplementing art therapy with CBT and DBT during the treatment of children impaired by GAD, OCD, and PTSD has intrinsic value in reducing the symptoms exhibited in these anxiety disorders and can create an overall improvement in their quality of life. The pilot study provided a means to analyze these three therapeutic methods within the collaborative therapeutic model in a critical manner, allowing it to be researched further and implemented in the future. Drawing on her expertise in working with children impaired by these anxiety disorders, the therapist provided valuable feedback in supplementing art therapy with CBT and DBT during the treatment of these anxiety disorders. Combining these three therapeutic methods into a collaborative model has the potential to provide adequate treatment for childhood anxiety disorders amidst the negative impacts that a cognitive and/or behavioral disorder might evoke.
Analysis of Computer Image Processing Technology in Web Design

Computer image processing technology plays an important role in web design, which can effectively increase the attractiveness and artistic sense of web pages. This paper analyzes the role of images in web design, discusses the development of current computer image processing technology, and analyzes the fusion of the two, and proposes the application of computer image processing technology in web design.
The role of the PHB complex in mitochondrial biogenesis

Prohibitins in eukaryotes consist of two subunits (PHB1 and PHB2) that together form a high molecular weight complex in the mitochondrial inner membrane. The evolutionary conservation and the ubiquitous expression in mammalian tissues of the prohibitin complex suggest an important function among eukaryotes. The PHB complex has been shown to play a role in the stabilization of newly synthesized subunits of mitochondrial respiratory enzymes in the yeast Saccharomyces cerevisiae. We have used Caenorhabditis elegans as model system to study the role of the PHB complex during development of a multicellular organism. We demonstrate that prohibitins in C. elegans form a high molecular weight complex in the mitochondrial inner membrane similar to that of yeast and humans. By using RNA-mediated gene inactivation, we show that PHB proteins are essential during embryonic development and are required for somatic and germline differentiation in the larval gonad. We further demonstrate that a deficiency in PHB proteins results in altered mitochondrial biogenesis in body wall muscle cells. This paper reports a strong loss of function phenotype for prohibitin gene inactivation in a multi-cellular organism and shows for the first time that prohibitins serve an essential role in mitochondrial function during organismal development.
Modeling of Drivable Free Space with Fused Camera Data for Autonomous Driving

The detection and modeling of drivable free space is a major challenge for autonomous driving. A novel approach is to use high resolution cameras especially in order to get semantic information of the environment. However, most approaches fail to use a suitable representation of the free space which is indispensable for subsequent processes like the behavior and motion planning. This paper presents a generic framework for detecting and compactly modeling free space based on fused camera data. For the detection, the disparity image and pixel classification of a stereo-camera are used. Based on that, a new continuous semantic free space model including temporal filtering is introduced. First evaluations show impressive results even in challenging scenarios.