Miracle-dz/UniFAR-FTUs huggingface dataset:
Emergent Reefs

The purpose of Emergent-Reefs is to establish, through computational design strategies and machine-based fabrication, seamless relationships between three different aspects of the architectural process: generation, simulation and construction, with the intent of exploiting the expressive and tectonic potential of D-Shape technology for underwater reef formations as a design response to coastal erosion. Starting from a digital simulation of a synthetic local ecosystem, a generative technique based on multi-agent systems and reaction-diffusion (through continuous cellular automata CCA) is implemented in a voxel field at several scales. Discrete voxel space eases the simulation of complex systems and processes (including CFD simulations) via CCA algorithms, which then can be translated directly to the physical production system, which in case of addtive technology can be specified as guided growth.
False News Detection on Social Media

Social media has become a major information platform where people consume and share news. However, it has also enabled the wide dissemination of false news, i.e., news posts published on social media that are verifiably false, causing significant negative effects on society. In order to help prevent further propagation of false news on social media, we set up this competition to motivate the development of automated real-time false news detection approaches. Specifically, this competition includes three sub-tasks: false-news text detection, false-news image detection and false-news multi-modal detetcion, which aims to motivate participants to further explore the efficiency of multiple modalities in detecting false news and reasonable fusion approaches of multi-modal contents. To better support this competition, we also construct and publicize a multi-modal data repository about False News on Weibo Social platform(MCG-FNeWS}) to help evaluate the performance of different approaches from participants.
Survey on Security Issues and Their Techniques in DBMS

Nowadays a Database security has become an important issue in technical world. The main objective of database security is to forbid unnecessary information exposure and modification data while ensuring the availability of the needed services. A numbers of security methods have been created for protecting the databases. Many security models have been developed based on different security aspects of database. All of these security methods are useful only when the database management system is designed and developing for protecting the database. Recently the growth of web application with database at its backend Secure Database Management System is more essential than only a Secure Database. Therefore this paper highlight on the Threats, Security Methods and Vulnerabilities in Database Management System with the help of survey performed on the field of secure databases.
VOLCANOLOGICAL AND TECTONIC INSIGHTS INTO GEOTHERMAL SYSTEMS IN THE CENTRAL TAUPO VOLCANIC ZONE , NEW ZEALAND

Volcanism, tectonism and geothermal systems in the central Taupo Volcanic Zone (TVZ), New Zealand are intimately linked in time and space. The central TVZ is an exceptionally active 120 x 60 km area of rhyoliticdominated volcanism, about 1.6 million years old and expressed by 25 large caldera-forming and about 2 orders of magnitude more additional smaller eruptions. Vent sites tend to be clustered, and the greatest volumes of magma have been discharged from 8 so-far delineated caldera volcanoes or volcanic complexes. The central TVZ is actively rifting and subsiding, but the rates of rifting and subsidence may be uneven on the 10 year timescale. There are 23 high-temperature geothermal systems across the same area, from Tokaanu in the south to Kawerau in the north, each of which requires a source of heat and permeability. The sources of heat ultimately are magma bodies intruded at depth yet, to a first order, magma and geothermal fields are widespread throughout the central TVZ and not tied to the youngest active volcanic systems at Taupo and Okataina. The most productive geothermal systems are in areas where young (<~65 ka) volcanism has
A Closed Loop Fault Tolerant Series Resonant Dc-Dc Converter

In this project we are implementing the Series-Resonant dc-dc converter (SRC) which is widely utilized in the power supply from the telecommunications, wireless power transfer for electrical vehicle and high voltage power supplies. Here we are developing the fuzzy controller for the better performance. Fuzzy controller is the most suitable for the human decision-making mechanism, providing the operation of an electronic system with decisions of experts. Therefore in the reconfiguration method of the SRC which is performance for the cases of failure in one semiconductor, which is used to decreases the requirement of the redundancy. According to the proposed scheme the full bridge will be depend upon the SRC which can be reconfigured in the half bridge topology in order to converter the operation without the failure of one switch. According to the demerits of the technique, the output voltage a drop which is half of the original value. Moreover a novel reconfiguration rectifier which is depends upon the voltage doubler metholody which is proposed technique which is used to keep the output voltage constant after the faults. By utilizing the simulation results we can verify the proposed system which confirms the effectiveness of the proposed approach.
The Gibbs energy of formation of huntite, CaMg3(CO3)4, at 298 K and 1 bar from electrochemical cell measurements

New data are presented for the IlG~ for huntite, CaMg3(C03)4' Measurements were made using new third-kind electrochemical cells that do not require a complicated model for solute speciation or corrections for liquid-liquid junction potentials. The average value of IlG~[CaMg3(C03). (S)] (-4195.6 I 6.4 kJ/mol) measured in these electrochemical cells agrees, within experimental error, with values determined calorimetrically (e.g., -4203.4 I 1.6 kJ/mol: Hemingway and Robie, 1973) and electrochemically (-4188.6 I 1.0 kJI mol: Gamsjiiger, 1989). Our results demonstrate the utility of this new electrochemical method in the study of metal carbonate equilibria of geochemical importance.
Does Human Resource Management in Local Government Match the ‘Ideal Type’ as defined in classical HR literature? What lessons can Human Resource Professionals learn to help them get the best from the Local Government Model

Human Resource Management (H.R.M) in local government has been said to be a hybrid. The characteristics of local government H.R. M are different from those depicted in some models of the ‘ideal-type’ H.R. M due to the influence of particular cultural and management factors within local councils. This study compares the characteristics of H.R. M in local government with a model of the ‘ideal-type’ characteristics of H.R. M. The views of heads of HR working in local councils were sought to identify how and why these characteristics differ. The study found that there are significant differences between the ‘ideal type’ and the local government model. These differences which will need to be taken into consideration in the development of HR strategy if higher organisational performance is to be achieved.
Comparative Analysis of Vessel Segmentation Techniques in Retinal Images

The blood vessels are the primary anatomical structure that can be visible in retinal images. The segmentation of retinal blood vessels has been accepted worldwide for the diagnosis of both cardiovascular (CVD) and retinal diseases. Thus, it requires an appropriate vessel segmentation method for automatic detection of retinal diseases such as diabetic retinopathy and cataract. The detection of retinal diseases using computer-aided diagnosis (CAD) can help people to avoid the risks of visual impairment and save medical resources. This survey presents a comparative analysis of various machine learning and deep learning-based methods for automated blood vessel segmentation in retinal images. This paper briefly describes fundus photography, publicly available retinal databases, pre-processing and post-processing techniques for retinal vessels segmentation. A comprehensive review of the state of the art supervised and unsupervised blood vessel segmentation methodologies are presented in this paper. The objective of this study is to establish a professional structure to familiarize an individual with up-to-date vessel segmentation techniques. Moreover, we compared these approaches to the dataset, evaluation metrics, pre-processing and post-processing steps, feature extraction, segmentation methods, and induced results.
On localized signature and higher rho invariant of fibered manifolds

Higher index of signature operator is a far reaching generalization of signature of a closed oriented manifold. When two closed oriented manifolds are homotopy equivalent, one can define a secondary invariant of the relative signature operator called higher rho invariant. The higher rho invariant detects the topological nonrigidity of a manifold. In this paper, we prove product formulas for higher index and higher rho invariant of signature operator on fibered manifolds. Our result implies the classical product formula for numerical signature of fiber manifolds obtained by Chern, Hirzebruch, and Serre in "On the index of a fibered manifold". We also give a new proof of the product formula for higher rho invariant of signature operator on product manifolds, which is parallel to the product formula for higher rho invariant of Dirac operator on product manifolds obtained by Xie and Yu in "Positive scalar curvature, higher rho invariants and localization algebras" and Zeidler in "Positive scalar curvature and product formulas for secondary index invariants".
Competitive Strategies for Differential Evolution

We introduce two competitive strategies into conventional differential evolution (DE) to speed up its convergence by increasing competitive pressures among individuals and evaluate the proposals. The first strategy gives individuals with better fitness a higher opportunity for generating more offsprings, while conventional DE allows each parent individual to generate only one offspring individual fairly. This strategy compares each of poor individuals with a randomly selected individual from the current population. If the latter becomes a winner, the latter can generate one more offspring individual, but the former loses an opportunity for generating its offspring. If the former becomes a winner, no one loses this opportunity, and each of them generates one offspring individual. The second strategy does not compare a generated offspring individual with its parent but the worst individual in the current population, which can accelerate the elimination of poor individuals and keep better individuals. We design a set of controlled experiments to evaluate these two strategies using CEC2013 benchmark functions with three different dimensions. The experimental results indicate that properly enhancing competition among individuals in DE can speed up its convergence and improve optimization performance.
Schwarzian functional integrals calculus

We derive the general rules of functional integration in the theories of Schwarzian type, thus completing the elaboration of Schwarzian functional integrals calculus initiated in [, ]. Our approach is mathematically rigorous and does not contain any unproved conjectures. It is based on the analysis of the properties of the measures on the groups of diffeomorphisms, and does not appeal for the experience from other physical models. Its great merit consists in reducing a problem of functional integration to that of the only functional integral () that is calculated explicitly with the result written in the form of the ordinary integral. We evaluate two-point and four-point correlation functions defined as functional integrals over the groups Diff+1R and Diff+1(S1) , and discuss the difference between the results in the two cases.
Sparsity and morphological diversity for multivalued data analysis

The recent development of multi-channel sensors has motivated interest in devising new methods for the coherent processing of multivariate data. An extensive work has already been dedicated to multivariate data processing ranging from blind source separation (BSS) to multi/hyper-spectral data restoration. Previous work1 has emphasized on the fundamental role played by sparsity and morphological diversity to enhance multichannel signal processing. GMCA is a recent algorithm for multichannel data analysis which was used successfully in a variety of applications including multichannel sparse decomposition, blind source separation (BSS), color image restoration and inpainting. Inspired by GMCA, a recently introduced algorithm coined HypGMCA is described for BSS applications in hyperspectral data processing. It assumes the collected data is a linear instantaneous mixture of components exhibiting sparse spectral signatures as well as sparse spatial morphologies, each in specified dictionaries of spectral and spatial waveforms. We report on numerical experiments with synthetic data and application to real observations which demonstrate the validity of the proposed method.
ERIES Innovation Strategies and Firm Growth

In this work, we explore the relations between sales growth and a set of innovation indicators that capture the different sources, modes and results of the innovative activity undertaken within firms. We exploit a rich panel on innovation activity of Spanish manufacturing firms, reporting detailed CIS-type information continuously over the period 2004-2011. Standard GMM-panel estimates of the average effect of innovation activities reveal significant and positive effect for internal R&D, while no effect is found for external sourcing of knowledge (external R&D, acquisition of embodied and disembodied technologies) as well as for output of innovation (process and product innovation). However, fixed-effects quantile regressions reveal that innovation activities, apart from process innovation and disembodied technical change, display a positive effect on high-growth performance. Finally, we find evidence of super-modularity of the growth function, revealing complementarities of internal R&D with product innovation, and between product and process innovation. JEL codes: C21, D22, O31, O32
Visualizing Uncertainty for Comparing Genomic Pediatric Brain Cancer Data

State of the art genomic methods produce an abundance of data which ultimately increases the quantity within and of data repositories. Thereby, open data is of much importance to boost scientific studies for combating disease. More and more often, there are several data sources available, offering diverse sample data. Particularly, interpretation of genomic data remains a challenge due to data size and differing quality. We present an approach for visualizing uncertainty of heterogeneous data sources on mutation rates in genomic data for pediatric cancer analysis. Visualization as method for knowledge discovery will be of great importance in order to put inhomogeneity of sample data into perspective.
Affiliation with depressive peer groups and social and school adjustment in Chinese adolescents

Abstract The purpose of the present study was to examine the role of depressive peer group context in individual social and school adjustment in a sample of 1,430 Chinese adolescents (672 boys, mean age = 15.43 years) from middle (n = 430) and high (n = 1000) schools. Peer groups were identified using the Social Cognitive Map technique. One-year longitudinal data on depression and social and school adjustment were obtained from self-reports, peer nominations, teacher ratings, and school records. Multilevel analyses showed that group-level depression positively predicted later individual depression. Moreover, group-level depression negatively predicted later social competence, peer preference, school competence, and academic achievement, and it positively predicted later peer victimization and learning problems. The results suggest that affiliation with more depressive peer groups contributes to more psychological, social, and school adjustment problems in a cascading manner among Chinese adolescents.
Predicting the motion trajectories of a modular snake robot performing various gaits.

Some studies have demonstrated that snake robots have more advantages than other mobile robots in real-world applications such as search-and-rescue operations and building inspections. A pitch-and-yaw modular snake robot is capable of performing various gaits such as linear progression, rolling, sidewinding and rotating. These gaits allow the robot locomotion to adapt to different types of terrain. Predicting the motion trajectories of the gaits is necessary in order to control the robots in path planning. This thesis presents the pitch-and-yaw modular snake robot developed as a robotic platform to study snake robot locomotion. The joint control of the robot was optimised and optimal gait parameters of the sinusoid function generators, which are used to generate the gaits, were obtained. The reprojection errors of the motion capture, which was used to track the robot’s joints, were determined. The accuracy of the 2D and the 3D simple kinematic motion models, which are based on the virtual chassis, were analysed using the motion trajectories recorded from the laboratory and the ODE simulation. The models were optimised to find the average optimal ground parameters of the models by training the models with the experimentally recorded motion trajectories. The consistency in the motion trajectories for each gait was evaluated to determine the predictability of each gait. The results are presented in terms of errors in the travelled distance and direction, and the orientation of the robot. The 2D model predicted the motion trajectories of the linear progression gait and the turning gait with highest average errors of 5.4% and 10.1%. The 3D model achieved similar outcomes for the rolling gait and the rotating gait but with highest average errors of 16.5% and 10.2%. However, the failure of both the 3D model and the simulation to predict the sidewinding gait might be due to the large inconsistency in the motion trajectories of the gait and the lacking number of modules. The use of average optimal ground parameters, reprojection errors and inconsistency in the motion trajectories might have contributed to the errors of the models.
ASSESSING POTENTIAL HABITATS OF KASHMIR MARKHOR IN CHITRAL GOL NATIONAL PARK , KHYBER PAKHTUNKHWA , PAKISTAN

Since the recognition of Chitral Gol as a National Park, there has been no vegetation assessment of the area, particularly in context of the habitat of Kashmir markhor (Capra falconeri cashmiriensis). Therefore, the present study is a first ever attempt to elaborate the vegetation of Park as habitat of Kashmir markhor using multivariate statistical methods. The vegetation abundance data was systematically collected from the park area on a grid with 200m vertical and 400m horizontal spacing, resulting in 252 nested sampled plots for each of the tree (10mx10m), shrub (4mx4m) and herbaceous layers (1mx1m). The data were analyzed for possible natural grouping using TWINSPAN classification analysis that resulted in 4 vegetation communities viz., (i) Prangos pabularia – Hypericum perforatum – Rosa macrophylla community, (ii) Cedrus deodara – Pinus gerardiana – Rosa macrophylla community, (iii) Quercus baloot – Sophora mollis – Artemisia fragrans community and (iv) Artemisia fragrans – Agrostis canina – Iris hookeriana community. The ordination using Detrended correspondence analysis and regressing its scores with primary topographic attributes revealed that the altitude, (p<0.0001), aspect (p<0.05) and slope (p<0.05) have strong impact on the distribution of vegetation distribution in the park. These communities possess a diverse range of plant species and are variously utilized by Kashmir markhor as summer habitat (i), lambing season (ii) and winter habitat (iii, iv).
Mobile Service Overlay Networks for Multimedia Applications

Mobile Service Overlay Networks for Multimedia Applications Yongbo Tang Master of Applied Science Graduate Department of Electrical and Computer Engineering University of Toronto 2013 With the increasing demand on multimedia applications over the Internet, and the growing number of mobile smart devices people are using, it is helpful to develop a mobile network architecture that can support multimedia transmission without using infrastructures. We propose that service overlay networks over MANETs can serve as a supplement to the existing 3G/4G networks and Wi-Fi access point networks. In this thesis we present experiment results that show the feasibility of mobile service overlay networks to meet the requirements of multimedia streaming. And also, we improved one of the existing overlay protocols. The improved protocol takes physical location into consideration when establishing connections in the overlay network. It also limits the number of neighbors each node can have, which prevents a particular node from becoming the bottleneck of the network, when connected to too many neighbors. Evaluation results show the new protocol reduces network packet loss rate.
GROWING STOCK OF VARIOUS BROAD-LEAVED AND CONIFER FORESTS OF GARHWAL HIMALAYA

The present study was undertaken to assess the Growing Stock and Population Structure of ten temperate forest types of Garhwal Himalaya between 1200-3000m asl. Five sample-plots of 0.1 ha were randomly laid out at two sites (I and II) in each forest type to estimate the GSVD (Growing Stock Volume Density) (by using appropriate volume tables and volume equations). The GSVD values in different forest types oscillated between 198.78 m/ha (for Quercus glauca) to 907.74 m/ha (for Cedrus deodara forest). The density-diameter distribution was calculated to understand the pattern of Regeneration status of the forest type. Quercus floribunda forest type was recorded as the most dense forest with 710ind/ha (Site I) and 790 ind/ha (Site II). Analysis of Growing stock and density of particular forest type plays an important role in forest management and proper strategies for the conservation of the forests. GSVD estimation leads to quantification of biomass, which in turn is essential to assess the amount of carbon stored in the forest. The estimation of GSVD has, therefore assumed significance in estimating climate change scenario.
BlackMagic: Automatic Inlining of Scalar UDFs into SQL Queries with Froid

Relational DBMSs allow users to extend the standard declarative SQL language surface using User Defined Functions (UDFs) that implement custom behavior. While UDFs offer many advantages, it is well-known amongst practitioners that they can cause severe degradation in query performance. This degradation is due to the fact that state-of-the-art query optimizers treat UDFs as black boxes and do not reason about them during optimization. We demonstrate Froid, a framework for optimizing UDFs by opening up this black box and exposing its underlying operations to the query optimizer. It achieves this by systematically translating the entire body of an imperative multi-statement UDF into a single relational algebraic expression. Thereby, any query invoking this UDF is transformed into a query with a nested sub-query that is semantically equivalent to the UDF. We then leverage existing sub-query optimization techniques and thereby get efficient, set-oriented, parallel query plans as opposed to inefficient, iterative, serial execution of UDFs. We demonstrate the benefits of Froid including performance gains of up to multiple orders of magnitude on real workloads. Froid is available as a feature of Microsoft SQL Server 2019 called 'Scalar UDF Inlining'.