Miracle-dz/UniFAR-FTUs huggingface dataset:
Cloud Computing with Linux

The goal of the book is to provide an extensive introduction to virtualization and cloud computing from the Linux and open-source perspective (to increase its accessibility), as well as to provide the necessary information to build cloud computing systems and applications. The book also presents cloud storage and scale-out management methods along with open source solutions.FEATURES* Provides detailed coverage of virtualization from the Linux perspective, including related topics such as hypervisors, virtual machines, and device emulation* Covers the entire ecosystem of the cloud, from the core Linux/virtualization all the way to large scale management* Provides a practical grounding of cloud computing and storage through its exploration from Linux and the open source perspectiveTABLE OF CONTENTS Part 1. Cloud Computing Introduction. The Road to the Cloud. Cloud Enablers. Conceptual Architectures for Clouds. Cloud Computing Challenges. Part 2. Virtualization and the Computing Ecosystem. Introduction to Virtualization. Linux-based Virtualization. Virtual I/O and Device Emulation. Cloud Ecosystem Management. Part 3. Cloud Computing Ecosystem. Physical Architectures for Cloud Computing. Physical Architectures for Cloud Storage. Linux, Open-Source, and the Cloud. Open Source Hypervisors and Device Models. Part 4. Inside the Public Clouds. Cloud Computing and Storage Implementations. Amazon's Elastic Compute Cloud (EC2). Google's AppEngine. Cloud Protocols. Web-Services. Part 5. Open Source Cloud Computing. Infrastructures. Application Servers. Management. Domain Specific Applications. On the Website Chapters. Installing and Using KVM.
E-Shopping Community Structure Analysis Using Data Clustering

: The E-Shopping Experience has opened the new ways of business and shopping. The conventional terms of shopping have been changed and new terms to shop online emerge into customers' online shopping behaviors and preferences. Extort interesting shopping patterns from ever increasing data is not a inconsequential mission. It require intelligent association rule mining of the available data, that can be practically knowledgeable for the online retail stores, so that they can make viable business decisions . The fast development of online shopping, the ability to segment e-shoppers basing on their preferences and characteristics has become a key source of competitive advantage for firms. This paper presented the pragmatic algorithms for clustering e-shoppers in e-commerce applications. Various multi-dimensional range search is presented to solve the range-searching problem.In addition, in this paper, the global clustering algorithm is presented which is an incremental approach to clustering that dynamically adds one cluster center at a time through a deterministic global search procedure The basic idea underlying the proposed method is that an finest solution for a clustering problem with other clusters can be obtained using a series of location based clustering and segmentation.
La estrategia de retorno de la industria española: El caso del sector calzado en Alicante, su importancia y determinantes/Reshoring the Spanish Production of Footwear: Its Importance and Determinants

Este trabajo analiza los procesos de retorno al pais de origen de algunas de las fases del proceso productivo que previamente se habian deslocalizado a paises extranjeros en el sector del calzado. La metodologia empleada consiste en un estudio de casos a empresas del sector. Los resultados del estudio revelan que la estrategia de relocalizacion responde a los cambios en el entorno de las empresas derivados de la reciente crisis economica y que no estaban presentes cuando se adoptaron las decisiones de deslocalizacion. En el nuevo contexto, la reduccion de los plazos de entrega y los aumentos de flexibilidad en la distribucion se revelan como las principales razones que motivan el aumento de produccion nacional y la disminucion en el extranjero. This paper analyzes the processes of return to the country of origin of some of the phases of the productive process that in the past had been relocated to foreign countries in the footwear sector. The methodology used is a case study with qualitative information from companies in the sector The results of the study reveal that the relocation strategy adopted responds to changes in the business environment resulting from the recent economic crisis that were not present when the delocalization strategy was adopted. In the new economic situation, the need of more reduced delivery times as well as flexibility in the distribution are revealed as the reasons that justify the increase in domestic production and the reduction of production abroad.
Social Circle-Based Algorithm for Friend Recommendation in Online Social Networks

Recommending friends to registered users is a crucial personal service of Online Social Networks(OSN). OSN will recommend a friend to a user if they share some common attributes or neighbors.But the recommendation accuracy is usually not so good since users' profile information may be incomplete and the relationships between neighbors are ignored.In fact,users can group their friends into several social circles and two users are more likely to become friends if they share similar social circles.Therefore,a social circle detection algorithm is suggested at first,and then the social circle similarity is defined.Based on this similarity,we can recommend friends to a user.Our hypothesis is verified by statistically analyzing the YouTube dataset.To verify the efficiency of the social circle detection algorithm,the ego networks of Facebook are used.The experimental results show that compared with three typical detection methods,our approach can identify social circles efficiently and accurately.We utilize social circle similarity, common neighbor similarity and Jaccard similarity to predict friend relationships in Facebook New Orleans network.The experimental results provide strong evidence that our algorithm is more precise in friend recommendation.
An Optimal Load Balancing Technique for Cloud Computing Environment using Bat Algorithm

Background/Objectives: In this research, load balancing algorithm based on Bat Algorithm is implemented to achieve the goals of load balancer. Methods/Statistical Analysis: The proposed algorithm is implemented using “Parallel Processing toolbox” in Mat lab and the results are compared with other techniques, namely, Round Robin and Fuzzy GSO. Findings: Results are discussed in the context of response time and based on the number of tasks. While balancing the load among the virtual machines, job migration to another virtual machine will affect the response time. In future, further work is on the development of job migration algorithm.
Problem oriented analysis and decision expert system

The ultimate goal of the expert system is to provide strong ability of analysis and decision for the practical problems.Based on the problem analysis and decision thought got by human for long practical activities,this paper showed a problem oriented analysis and decision expert system which used problem objects as core,correlated objects as problem meta-objects,problem phenomena as expression form,causalitied as problem transformation driver,procedure knowledge and principle knowledge as reference object.The knowledge base of the expert system is built around the application problems without using the rules,so the system is more rational and clear,and is not easy to generate the knowledge conflicts and is convenient to build large scale knowledge base.At the same time,problem based inference is used in this system,which accords with the human thinking habits and has higher inference efficiency.Moreover,domain experts can develop this kind of expert systems without mastering artificial intelligent language and needing the participation of knowledge engineers,and only concentrate on the analysis and codification of the domain-specific knowledge completely.
Documento de trabajo. El impacto en el desarrollo local de las políticas educativas en el municipio de medellín entre 2004 – 2011 [Working document. The impact on local development of educational policies in the municipality of medellin between 2004-2011]

This study is inspired by determining the scope of the public policy of the city of Medellin in the education component and its impact on the index of quality of life of its citizens. Progress identified in the local development of the city taking as a reference the policies implemented in municipal administrations 2004 - 2007 and 2008 - 2011 investment in education through observation initially mentioned index.
Spin-independent elastic WIMP scattering and the DAMA annual modulation signal

We discuss the interpretation of the annual modulation signal seen in the DAMA experiment in terms of spin-independent elastic WIMP scattering. Taking into account channeling in the crystal as well as the spectral signature of the modulation signal we find that the low-mass WIMP region consistent with DAMA data is confined to WIMP masses close to m� ≃ 12GeV, in disagreement with the constraints from CDMS and XENON. We conclude that even if channeling is taken into account this interpretation of the DAMA modulation signal is disfavoured. There are no overlap regions in the parameter space at 90% CL and a consistency test gives the probability of 1.2 ×10 −5 . We study the robustness of this result with respect to variations of the WIMP velocity distribution in our galaxy, by changing various parameters of the distribution function, and by using the results of a realistic N-body dark matter simulation. We find that only by making rather extreme assumptions regarding halo properties can we obtain agreement between DAMA and CDMS/XENON.
PORTABLE AUTOMATIC RADIOTELEMETRY RECORDING SYSTEM

Continuous, accurate, and automatic collection of wildlife telemetry data with little human attention is highly desirable, but has been difficult to obtain. Studies by Cochran and Lord (1963), Deat et al. (1980), Kolz et al. (1980), Schweinsburg and Lee (1982), and Lemnell et al. (1983) used automatic telemetry systems for obtaining location data. Other telemetry studies investigating presence or absence, activity, and physiology have used strip chart recorders (Gilmer et al. 1971, Moen 1978, Ward and Cupal 1979, Cederlund and Lemnell 1980, Folk and Folk 1980). Disadvantages of strip chart recorders have been discussed by Mech (1983) and Cederlund and Lemnell (1980). An optimum data-acquisition system would record data with precision and resolution and be inexpensive, lightweight, simple to operate, computer compatible, tolerant of exposure, and functional with minimal human attention. Free-roaming wild animals can be monitored automatically with radiotelemetry using portable, battery-powered microcomputers, and data collected can be transferred to a computer without manual transcription (Howey et al. 1984, Cooper and Charles-Dominique 1985). This paper describes 1 such system used to automatically collect radio-telemetered data, evaluates its accuracy, and presents possible applications of the data.
High-resolution marine flood modelling coupling overflow and overtopping processes: framing the hazard based on historical and statistical approaches

Abstract. A modelling chain was implemented in order to propose a realistic appraisal of the risk in coastal areas affected by overflowing as well as overtopping processes. Simulations are performed through a nested downscaling strategy from regional to local scale at high spatial resolution with explicit buildings, urban structures such as sea front walls and hydraulic structures liable to affect the propagation of water in urban areas. Validation of the model performance is based on hard and soft available data analysis and conversion of qualitative to quantitative information to reconstruct the area affected by flooding and the succession of events during two recent storms. Two joint probability approaches (joint exceedance contour and environmental contour) are used to define 100-year offshore conditions scenarios and to investigate the flood response to each scenario in terms of (1) maximum spatial extent of flooded areas, (2) volumes of water propagation inland and (3) water level in flooded areas. Scenarios of sea level rise are also considered in order to evaluate the potential hazard evolution. Our simulations show that for a maximising 100-year hazard scenario, for the municipality as a whole, 38 % of the affected zones are prone to overflow flooding and 62 % to flooding by propagation of overtopping water volume along the seafront. Results also reveal that for the two kinds of statistic scenarios a difference of about 5 % in the forcing conditions (water level, wave height and period) can produce significant differences in terms of flooding like +13.5 % of water volumes propagating inland or +11.3 % of affected surfaces. In some areas, flood response appears to be very sensitive to the chosen scenario with differences of 0.3 to 0.5 m in water level. The developed approach enables one to frame the 100-year hazard and to characterize spatially the robustness or the uncertainty over the results. Considering a 100-year scenario with mean sea level rise (0.6 m), hazard characteristics are dramatically changed with an evolution of the overtopping ∕ overflowing process ratio and an increase of a factor 4.84 in volumes of water propagating inland and 3.47 in flooded surfaces.
The Public Health Importance of the Association between Componotus Consobrinus and Potential Bacterial Pathogens in Human Dwellings

Camponotus consobrinus, the banded sugar ant is a species in the ant family Camponotus. The ant is so called because of its liking for sweet food and the orange-brown band that goes round its gaster [1]. Ants are insects found in households, shops, hospitals and food service establishment. They are a nuisance when they occupy residence, restaurants and other places where food is prepared or eaten, yet they are considered as harmless small creatures [2,3].
Improved Genetic Programming Techniques For Data Classification

Evolutionary algorithms are one category of optimization techniques that are inspired by processes of biological evolution. Evolutionary computation is applied to many domains and one of the most important is data mining. Data mining is a relatively broad field that deals with the automatic knowledge discovery from databases and it is one of the most developed fields in the area of artificial intelligence. Classification is a data mining method that assigns items in a collection to target classes with the goal to accurately predict the target class for each item in the data. Genetic programming (GP) is one of the effective evolutionary computation techniques to solve classification problems. GP solves classification problems as an optimization tasks, where it searches for the best solution with highest accuracy. However, GP suffers from some weaknesses such as long execution time, and the need to tune many parameters for each problem. Furthermore, GP can not obtain high accuracy for multiclass classification problems as opposed to binary problems. In this dissertation, we address these drawbacks and propose some approaches in order to overcome them. Adaptive GP variants are proposed in order to automatically adapt the parameter settings and shorten the execution time. Moreover, two approaches are proposed to improve the accuracy of GP when applied to multiclass classification problems. In addition, a Segment-based approach is proposed to accelerate the GP execution time for the data classification problem. Furthermore, a parallelization of the GP process using the MapReduce methodology was proposed which aims to iii shorten the GP execution time and to provide the ability to use large population sizes leading to a faster convergence. The proposed approaches are evaluated using different measures, such as accuracy, execution time, sensitivity, specificity, and statistical tests. Comparisons between the proposed approaches with the standard GP, and with other classification techniques were performed, and the results showed that these approaches overcome the drawbacks of standard GP by successfully improving the accuracy and execution time.
Sedimentary alkalinity generation and long-term alkalinity development in the Baltic Sea

Abstract. Enhanced release of alkalinity from the seafloor, principally driven by anaerobic degradation of organic matter under low-oxygen conditions and associated secondary redox reactions, can increase the carbon dioxide (CO2) buffering capacity of seawater and therefore oceanic CO2 uptake. The Baltic Sea has undergone severe changes in oxygenation state and total alkalinity (TA) over the past decades. The link between these concurrent changes has not yet been investigated in detail. A recent system-wide TA budget constructed for the past 50 years using BALTSEM, a coupled physical–biogeochemical model for the whole Baltic Sea area revealed an unknown TA source. Here we use BALTSEM in combination with observational data and one-dimensional reactive-transport modeling of sedimentary processes in the Fårö Deep, a deep Baltic Sea basin, to test whether sulfate (SO42-) reduction coupled to iron (Fe) sulfide burial can explain the missing TA source in the Baltic Proper. We calculated that this burial can account for up to 26 % of the missing source in this basin, with the remaining TA possibly originating from unknown river inputs or submarine groundwater discharge. We also show that temporal variability in the input of Fe to the sediments since the 1970s drives changes in sulfur (S) burial in the Fårö Deep, suggesting that Fe availability is the ultimate limiting factor for TA generation under anoxic conditions. The implementation of projected climate change and two nutrient load scenarios for the 21st century in BALTSEM shows that reducing nutrient loads will improve deep water oxygen conditions, but at the expense of lower surface water TA concentrations, CO2 buffering capacities and faster acidification. When these changes additionally lead to a decrease in Fe inputs to the sediment of the deep basins, anaerobic TA generation will be reduced even further, thus exacerbating acidification. This work highlights that Fe dynamics plays a key role in the release of TA from sediments where Fe sulfide formation is limited by Fe availability, as exemplified by the Baltic Sea. Moreover, it demonstrates that burial of Fe sulfides should be included in TA budgets of low-oxygen basins.
Binaural auditory interaction without HRTF for humanoid robots: A sensor-based control approach

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Binaural auditory interaction without HRTF for humanoid robots: A sensor-based control approach Aly Magassouba, Nancy Bertin, François Chaumette
Assessment of Contaminated Soil with Some Heavy Metals in Selected Auto Repair Shops in Katsina North Western, Nigeria

Anthropogenic activities of humans lead to heavy metals toxicity into the soils. Auto mechanic workshops are one of the major sources of increase in heavy metal concentration in soils in Katsina North western Nigeria. Katsina is located on latitude 12o59’N and longitude 7o36’E and it’s the capital city of Katsina state Nigeria. Five selected auto repair shops which include; Garejin Tsohuwar Tasha (TT), Albarkar Motors-Garage (AM), Garejin Abdulhadi (GA), Garejin Bebeji (GB) and Garejin KofarDurbi (GK) were considered for this study. Heavy metals in the soil samples at 0-15cm and 15-30cm depths were subjected to sequential extraction to ascertain the bioavailability of the metals in the soils. The percentage bioavailability of metals in the experimental sites at 0-15cm were; (GBCd-23.08%, Pb-38.48%, Cu-33.49%, Zn-44.15%, Cr-23.1%), (GK-Cd-57.38%, Pb 65.49%, Cu-71.59%, Zn-41.75%, Cr-57.02%), (TT-Cd 28.30%, Pb 31.70%, Cu26.93%, Zn-64.47%, Cr-27.24%), (AM-Cd 36.59%, Pb-47.67%, Cu-25.45%, Zn-54.26%, Cr-21.39%), (GA-Cd 58.43%,Pb 24.00%, Cu-12.17%, Zn-67.13% Cr-18.02%), while the percentage bioavailability at 15-30cm depth were (GBCd 10.53%, Pb 23.96%, Cu-76.51%, Zn-26.53%, Cr 52.23%), (GKi Cd 44.44%, Pb 23.19%, Cu 5.54% ,Zn 25.35%,Cr-59.80%), (TT-Cd 80.0%, Pb 34.97%, Cu31.79%, Zn 5.19%, Cr 50.24%),(AM-Cd 26.67%, Pb 39.74%, Cu 13.88%, Zn 2.45%, Cr 25.90%) and (GA-Cd 81.82%, Pb 88.69%, Cu-25.00%, Zn 5.23%, Cr 17.52%). The high level of concentration of the heavy metals in the soils from the five experimental sites were slightly higher than from the control sites and higher than the recommended limits given by European Commission and World Health Organization.
Determination of Energy Requirements, Plowed Soil Volume Rate and Soil Pulverization Ratio of Chisel Plow Under Various Operating Conditions

Abstract: A field experiments were conducted using a chisel plow in silty loam soil at Agricultural Research Station of Garmat Ali in 2017. Three different levels of forward speed (0.65, 0.87 and 1.65 m sec -1 ) and plowing depth (10, 20 and 30 cm) were used to study their effect on energy utilization efficiency, specific energy, plowed soil volume rate and soil pulverization ratio. The results showed that increasing the forward speed from 0.55 to 1.35 m sec -1 , the specific energy, plowed soil volume rate and soil pulverization ratio were increased by 139.43%, 85.10% and 51.72%, respectively, while decreased the energy utilization efficiency by 30.04%. Increasing plowing depth from 10 to 30 cm led to increasing the energy utilization efficiency and the plowed soil volume rate by 34.30% and 87.38%, respectively. In contrast, the soil pulverization ratio and the specific energy decreased by 45.83% and 19.86%, respectively. The interaction between the forward speed and the plowing depth had a significant effect on all parameters in this study.
Federated filter for fault-tolerant integrated navigation systems

An efficient, federated Kalman filtering method is presented, based on rigorous information-sharing principles. The method applies to decentralized navigation systems in which one or more sensor-dedicated local filters feed a larger master filter. The local filters operate in parallel, processing unique data from their local sensors, and common data from a shared inertial navigation system. The master filter combines local filter outputs at a selectable reduced rate, and yields estimates that are globally optimal or subset-optimal. The method provides major improvements in throughput (speed) and fault tolerance, and is well suited to real-time implementation. Practical federated filter examples are presented, and discussed in terms of structure, accuracy, fault tolerance, throughput, data compression, and other real-time issues. <<ETX>>