Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of functionalized carbon nanotubes on properties of hot melt copolyamide

Hot melt copolyamide was mixed by the melt-blending process with 7 wt. % non-functionalized multi-walled carbon nanotubes and with amine modified multi-walled carbon nanotubes. The main goal of this work was to analyze the effect of functionalization of the properties of hot melt copolyamide. The rheological properties of the nanocomposites were examined by the dynamic oscillatory test using an oscillatory rheometer. Macrodispersion of both types of multi-walled carbon nanotubes within the copolyamide matrix was examined qualitatively by a light microscope and quantitatively using ImageJ Software. The thermal stability and characteristic temperatures such as the melting point and crystallization temperature were determined by thermogravimetric analysis and differential scanning calorimetry, respectively. It was found that the addition of 7 wt. % functionalized multi-walled carbon nanotubes increases the viscosity of copolyamide but to a lesser extent than in the case of non-functionalized multi-walled carbon nanotubes. Moreover, mixing copolyamide with amine functionalized multi-walled carbon nanotubes resulted in larger agglomerates which resulted in worse thermal stability than for non-modified multi-walled carbon nanotubes. Finally, the electrical conductivity measured by dielectric spectroscopy was lower in the case of nanocomposites with amine-functionalized multi-walled carbon nanotubes which indicates that the affinity to copolyamide was not improved by the amine groups.
Strong lensing probability in TeVeS theory

We recalculate the strong lensing probability as a function of the image separation in TeVeS (tensor-vector-scalar) cosmology, which is a relativistic version of MOND (MOdified Newtonian Dynamics). The lens is modeled by the Hernquist profile. We assume an open cosmology with $\Omega_b=0.04$ and $\Omega_\Lambda=0.5$ and three different kinds of interpolating functions. Two different galaxy stellar mass functions (GSMF) are adopted: PHJ (Panter-Heavens-Jimenez, 2004) determined from SDSS data release one and Fontana (Fontana et al., 2006) from GOODS-MUSIC catalog. We compare our results with both the predicted probabilities for lenses by Singular Isothermal Sphere (SIS) galaxy halos in LCDM (lambda cold dark matter) with Schechter-fit velocity function, and the observational results of the well defined combined sample of Cosmic Lens All-Sky Survey (CLASS) and Jodrell Bank/Very Large Array Astrometric Survey (JVAS). It turns out that the interpolating function $\mu(x)=x/(1+x)$ combined with Fontana GSMF matches the results from CLASS/JVAS quite well.
Business Process Verification using Formal Language Petri Net: An Approach

In this paper, we propose an approach of verification of business processes shown in semiformal modeling notation BPMN, by transforming it into petri net a formal language. This paper covers the transformation of BPMN to petri net using model transformation language ATL available in Model Driven Engineering along with introduction of BPMN and petri net. Refer ences Stephen A. white, "Introduction to BPMN", IBM Corporation.
The Effect of Leadership Style, Work Environment and Organization Culture on Employee Performance: a Case Study at Kawasan Industri Makassar (Kima), Indonesia

This paper aims to identify three indicators; leadership style, work environment and organization culture, which significantly influence the employee performance at Kawasan Industri Makassar (Makassar industrial region or KIMA). The fact has shown that the quality of human resources in Indonesia is considered low compared to neighbour countries which affected by various indicatiors that might effect the organization performance. The condition at Kawasan Industri Makassar has shown degradation in practical indicators of human resources management, yet escalation for the other. The other fact has indicated that employee performance fluctuation has decreased in 2009 with the avarage of work accomplishment has never been up to 100%. This study employed quantitave approcah with Structural Equation Model (SEM) as the tool to associate the exogeneous and endogeneous variables to discover the correlation and effect of every variable. Proportional Stratified Sampling Method was applied and involving 450 determined samples. The study revealed that dominant exogeneous variable which affected the employee performance is leadership, for the highest total effect of 0,292. However, total effect of work environment towards employee performance is 0,171. Meanwhile, total effect for organization culture on employee performance is about 0,160. The findings also reveal that those variables have significant correlation and positively influence the employee performance.
Robust identification of Takagi-Sugeno-Kang fuzzy models using regularization

The identification of fuzzy models can sometimes be a difficult problem, often characterized by lack of data in some regions, collinearities and other data deficiencies, or a sub-optimal choice of model structure. Regularization is suggested as a general method for improving the robustness of standard parameter identification algorithms leading to more accurate and well-behaved fuzzy models. The properties of the method are related to the bias/variance tradeoff, and illustrated with a semi-realistic simulation example.
Effect of Sustained Deficit Irrigation and Rice Straw Mulching on Vegetative Growth , Flowering , Yield and Water used Efficiency of Manzanillo Olive Trees

This investigation was carried out olive trees (Olea europaea L.) cv. Manzanillo grown in ElMaghara Experiment Station, Sinai, Egypt, during 2013, 2014 seasons. Selected trees were planted at 5x5 meters apart in sandy soil, watered from wells using drip irrigation system. The trial was conducted as split plot design based on randomized complete block design with three replication, sustained deficit irrigation in main plots (100%, 90%, 80%, 70%, 60%, or 50% from crop evapotranspiration (ETc) whole season, and rice straw mulching soil used (1680, 2520 and 3360 kg/f) located in the subplots, during summer months until harvest date, to compare affect on vegetative growth, flowering, yield and water used efficiency on olive trees. The results showed that vegetative growth i.e tree dimensions, shoot growth, leaf characteristics, flowering ( panicles number perfect, number of flower per panicle and perfect flower) and yield Kg/tree recorded the highest values with higher both irrigation level and mulching rate treatments. Furthermore, 70% Etc recorded the highest biennial bearing index and 3360 Kg/f rate rice straw mulching succeed in reducing the tendency of olive tree to alternative bearing. Irrigation at 50% Etc produced higher positive effect on water used efficiency. Key word: Manzanillo olive sustained deficit irrigation mulching vegetative growth flowering biennial bearing index yield water used efficiency.
ESTIMATION OF WATER QUALITY PARAMETERS IN LAKE NASSER USING REMOTE SENSING TECHNIQUES

The main objective of this research is to use remote sensing to estimate water quality parameters (WQPs) in Lake Nasser which is considered the sole strategic storage of fresh water in Egypt. The estimation of WQPs will support an integrated water management for lake Nasser and provide decision makers with the status of Lake water. The main problem for water quality monitoring in lake Nasser is that it is performed annually using traditional sampling where it is difficult to take more repetitive measurements in different seasons due to high cost of the field trips. So that, this research will provide a technique based on both field data and remote sensing to evaluate WQPs in Lake Nasser. Data of six field missions, executed in different seasons, are used with Envisat/MERIS matchup images to create and validate a regression model for various water quality parameters. The correlation between the different WQPs, optical and non-optical parameters, were calculated to show their behavior with the change of optical parameters. The correlation values indicate that non-optical WQPs have a strong correlation with the optical ones. Regression models can, therefore, be created to estimate many WQPs using remote sensing techniques. The stepwise regression was conducted between different WQPs and reflectance extracted from atmospherically corrected match-up MERIS images. Variation in WQPs resulted in different regression models for each water quality parameter depending on the season of measurement. Regression models was validated using statistical performance measures to select the suitable model for each water quality parameter, one for each season. The results indicated that bands 5 and 6 are found to be the common predictors for both optical and non-optical WQPs. It is recommended to make use of the regression models in studying the time series variation of WQPs in different seasons.
Absorptive capacity and new organisational capabilities: a TCS case study

The term 'absorptive capacity' (Cohen and Levinthal, 1990), which describes the ability to assimilate new knowledge and skills, has been widely adopted in the study of collaborative links between organisations. In this paper the concept is used to examine the process by which participation in a Teaching Company Scheme (now know as TCS) helped develop managerial capabilities in a small manufacturing company over a two-year period. RSL is a family-owned business which has been in existence for forty years, has approximately 70 employees, and manufactures office supply equipment. It is concluded that improving absorptive capacity requires the introduction of new organisational routines which help codify tacit knowledge. Within RSL, such changes helped increase turnover by almost 25 per cent during the two years the TCS programme was in operation.
Environment mobility: moving the desktop around

In this position paper, we focus on issues related to middleware support for software mobility in ad hoc and pervasive systems. In particular, we are interested in moving the computational environment of a mobile user following his or her trajectory. We present details of WAIFARER, a prototype implementation that automatically saves and restores application level state to support this mobility. Security, integrity, and fault-tolerance are just some of the key problems that need to be addressed in the future.
Seismic Characterisation of Gas Hydrates in the Lüderitz Basin , Offshore Namibia : Investigating Shallow Heat Flow and Fluid Flow Phenomena

Exploration of frontier basins carries significant uncertainty regarding the maturity of source rocks due to the lack of temperature data available for thermal modelling. Previous studies have developed methods to calculate subsurface temperature and shallow geothermal gradients using the depth of the base hydrate stability zone (BHSZ), often indicated in seismic data by a bottom simulating reflector (BSR). Here, this method is applied to a high-quality 3D seismic reflection data set from the Lüderitz Basin to estimate a BHSZ temperature and shallow geothermal gradient. Seismic interpretation shows two BSRs (BSRN and BSRS) that cover 1000 and 500 km2, respectively. Their distribution is controlled by an antiform structure of draped fine grained deposits above a structural high. Shallow geothermal gradients were estimated for both BSRs using a constant overburden velocity, resulting in BHSZ temperatures between 8-21 °C and a mean shallow geothermal gradient of 7.2 °C 100 m-1. Assuming a thermal conductivity of 0.67 W m-1 K-1, measured at the nearby ODP Site 1084, heat flow ranges from 28-56 mW m-2 (BSRN x̅ = 46 mW m2, BSRS x ̅ = 48 mW m-2). Uncertainty analysis propagating forwards from first Shallow Heat Flow in the Lüderitz Basin 17 principles estimates a heat flow uncertainty of ~37%. This case study provides another example that BSRs can successfully be used to estimate heat flow and proves a cost-effective method when direct temperature measurements are not present or are widely spaced across a margin.
Covert Network Analysis for Key Player Detection and Event Prediction Using a Hybrid Classifier

National security has gained vital importance due to increasing number of suspicious and terrorist events across the globe. Use of different subfields of information technology has also gained much attraction of researchers and practitioners to design systems which can detect main members which are actually responsible for such kind of events. In this paper, we present a novel method to predict key players from a covert network by applying a hybrid framework. The proposed system calculates certain centrality measures for each node in the network and then applies novel hybrid classifier for detection of key players. Our system also applies anomaly detection to predict any terrorist activity in order to help law enforcement agencies to destabilize the involved network. As a proof of concept, the proposed framework has been implemented and tested using different case studies including two publicly available datasets and one local network.
Distributed Scheduling Policy in Service Oriented Environments

Service oriented architectures become more and more popular with the emergence and consolidation of new paradigms such as Clouds and Grids. In this context scheduling becomes an important and difficult problem as services hide their actual implementation, requirements or efficiency and are spread across multiple institutions and geographical locations. This paper proposes a distributed scheduling approach based on agents where each agent handles a certain domain and manages independently the policies inside it. In its frame several scheduling algorithms are also studied, compared and some results are given.
Automatic High-Level Synthesis of Multi-Threaded Hardware Accelerators Hidden for review

Abstract—With the growing maturity of high-level synthesis systems, the attractive capabilities of architectures relying on reconfigurable computing have become accessible to a wider range of developers. A promising next step of research is the efficient mapping of the high-level descriptions in languages such as C to more powerful micro-architecture templates. One scheme that can be explored here is that of Single Instruction MultiThreaded (SIMT) execution, re-using the chip area dedicated to computation for different threads to hide memory latencies. We describe extending the hardware/software co-compiler Nymble to automatically generate such multi-threaded hardware accelerators. In contrast to prior work that simply duplicated complete compute units for each thread, Nymble-MT reuses the actual computation elements, and adds just the required data storage and context switching logic. Evaluated using the CHStone benchmark suite and a sample configuration of four threads, the existing prototype can reach up to quadruple the throughput, but with a chip area just 5% larger than that of a single-threaded accelerator.
Economic assesment and socio-economic evaluation of water use efficiency in artichoke cultivation

The aim of this work is to provide a methodology for analysing socioeconomic aspects of water resource management that will provide with an objective decision making tool. To validate the proposed analysis method here, we refer to three artichoke production options. The economic evaluations indicate that the drip irrigation systems are viable and profitable. The traditional method of flooding is not a viable option despite needing the lowest investment, but is close to the viability threshold. In reference to water use efficiency, option 1 is by far the most effective (3.60 kg·m-3 compared with 2.25 and 2.18 kg·m-3, respectively). In our analysis we find that the most productive systems generate the most employment per unit of surface area. Option 1 is the most competitive in relation with the water factor, since it could support prices up to 0.53 €·m-3 and still be economically viable. System 2 will not be viable if the price exceeds 0.22 €·m-3. Option 3 is viable up to 0.17 €·m-3, which is more than is paid at the present time in Sardinia, although such an option would not be viable in south-eastern Spain.
Are Chinese Residents Willing to Recycle Express Packaging Waste? Evidence from a Bayesian Regularized Neural Network Model

While enriching people’s lives, the rapid development of online shopping has posed a severe challenge to the environment. Questionnaires focusing on the intention to recycle packaging waste are designed. These questionnaires contain first-level variables such as recycling behavior attitude, recycling behavior cognition, situational factors, historical recycling behavior, and recycling behavior intention. With the collected questionnaire data, a regression analysis is first conducted on the selection of variables and the effect of variable prediction. After ensuring the validity of the variables, 15 second-level variables are extracted into eight principal components using principal component analysis. These components serve as input to a Bayesian regularized neural network. Subsequently, a three-layer (8-15-1) neural network model is constructed; the trained neural network model achieves a high degree of fit between the predicted and measured values of the test set, thus further proving the rationality of the selected variables and the neural network model. Finally, this study uses the connection weights matrix of the neural network model and the Garson formula to analyze in depth the specific impact of each second-level variable on the intention to recycle packaging waste. Note that given the particularity of packaging waste recycling behavior, the impact on social norms, recycling behavior knowledge, values, and publicity on behavioral intentions in second-level variables is different from that obtained in similar previous studies.
Simulating e-Commerce Client-Server Interaction for Capacity Planning

Abstract —Contemporary ways of doing business are heavily dependent on the e-Commerce/ e-Business paradigm. The highest priority of an e-Commerce Web site’s management is to assure pertinent Quality-of-Service (QoS) levels of their Web services continually, in order to keep the potential e-Customers satisfied. Otherwise, it faces an immense possibility of losing both e-Customers and revenues, along with a big possibility of gaining bad reputation due to either poor performance or unavailability of the e-Commerce Web site. In order to avoid numerous unpleasant consequences, by designing and implementing e-Commerce Web sites that will always meet e-Customer’s high expectations, a relevant performance models have to be utilized to obtain appropriate performance metrics. A continuous assessment of current performances and especially predicting future needs are the subjects of capacity planning methodologies. Within this paper, such a predictive model has been described and evaluated by using discrete-event simulation of both the client-side and server-side processes involved. In addition, the paper discusses the performance metrics obtained as a function of the intensity and quality of the workload parameters.
Interface tracking * nite volume method for complex solid – 4 uid interactions on * xed meshes

We present a numerical technique for computing 4ow*elds around moving solid boundaries immersed in *xed meshes. The mixed Eulerian–Lagrangian framework treats the immersed boundaries as sharp solid–4uid interfaces and a conservative *nite volume formulation allows boundary conditions at the moving surfaces to be exactly applied. A semi-implicit second-order accurate spatial and temporal discretization is employed with a fractional-step scheme for solving the 4ow equations. A multigrid accelerator for the pressure Poisson equations has been developed to apply in the presence of multiple embedded solid regions on the mesh. We present applications of the method to two types of problems: (a) solidi*cation in the presence of 4ows and particles, (b) 4uid–structure interactions in 4ow control. In both these problems, the sharp interface method presents advantages by being able to track arbitrary interface motions, while capturing the full viscous, unsteady dynamics. Copyright ? 2001 John Wiley & Sons, Ltd.
THE APPLICATION OF FLUORESCENT SINGLE-STRAND CONFORMATION POLYMORPHISM (F-SSCP) TO ASSESS THE DIVERSITY OF BURKHOLDERIA SPECIES IN SUGARCANE RHIZOSPHERE

The genus Burkholderia is the dominant component of the sugarcane rhizosphere microbial community. The Burkholderia population is complex and assessments performed on these populations do not always reveal specific members. Moreover, current cultivation based methods are limited because they do not assess the non-culturable fraction of rhizosphere microbiota. The aim of this work was to develop root DNA-based PCR fluorescent singlestrand conformation polymorphism (F-SSCP), a molecular method for studying the diversity of microbial communities, for analysis of Burkholderia diversity in root samples. Speciesspecific primers for Burkholderia were developed, based on a small region of the 16S rRNA gene sequence. F-SSCP analyses of the PCR products obtained showed that there were sufficient differences in migration to distinguish all 39 Burkholderia species tested. For microbial rhizosphere community studies, six-month-old variety N29 from the existing Burkholderia field trial at Zinkwazi was used. Roots from plots inoculated with Burkholderia isolates N8.2 and LM1-376.8 and from a corresponding control plot were sampled. Total genomic DNA extracted from roots was subjected to PCR and assessed using F-SSCP. FSSCP profiles on amplicons generated from root DNA were aligned with Burkholderia reference species profiles. The root DNA exclusively revealed profiles affiliated with profiles of Burkholderia reference species, and demonstrated that the F-SSCP method befits the study of diversity in Burkholderia spp. in natural samples. The dominant Burkholderia spp. in the root samples were B. caledonica, B. saccharri, B. cepacia, B. graminis and B. ambifaria. No differences in profiles between control and Burkholderia inoculated plots were distinguished.
Zero-shot Object Prediction using Semantic Scene Knowledge

This work focuses on the semantic relations between scenes and objects for visual object recognition. Semantic knowledge can be a powerful source of information especially in scenarios with few or no annotated training samples. These scenarios are referred to as zero-shot or few-shot recognition and often build on visual attributes. Here, instead of relying on various visual attributes, a more direct way is pursued: after recognizing the scene that is depicted in an image, semantic relations between scenes and objects are used for predicting the presence of objects in an unsupervised manner. Most importantly, relations between scenes and objects can easily be obtained from external sources such as large scale text corpora from the web and, therefore, do not require tremendous manual labeling efforts. It will be shown that in cluttered scenes, where visual recognition is difficult, scene knowledge is an important cue for predicting objects.
Jelly Technique Applications in Evolution Study of Hydrodynamic Instabilities on Unstable Plane and Cylindrical Surfaces

VNIIEF has developed and is now using the method [1],[3],[4] for the investigation of geometrically complex hydrodynamic flows based on jelly models accelerated by compressed air or by explosion products of a gaseous explosive mixture (GEM). The jelly (gelatin water solution) turned out to be a very convenient material for visual imitation of hydrodynamic processes in metal shells and layers loaded by the pressures of solid explosive burst products. On one hand, the jelly has a sufficient strength allowing to fabricate the shells and layers of complicated form. On the other hand, it behaves as an incompressible fluid under low pressure loading. The jelly transparency permits to use photo recording methods. The objective of the work is to study hydrodynamic instabilities on plane and cylindrical surfaces development using the jelly technology and numerical simulation.