Miracle-dz/UniFAR-FTUs huggingface dataset:
DE NEGOCIOS PARA ACUEDUCTO Y ALCANTARILLADO BUSINESS INTELLIGENCE SYSTEM FOR WATER AND SEWERAGE

Much of the success of modern enterprises depends on the use of intangible resources. The flow of data and information is vital to the successful decision making process. Due to the increased volume of data stored, the managers face an environment of uncertainty and increasing complexity. Many times we do not have the tools to handle this data efficiently into information and to generate the necessary knowledge. The main goal of this work is to develop a Business Intelligence System that allows to store, process, analyze and display efficiently the data generated in the departments of a random company, and thereby, to improve the decision making process. It is proposed to use the HEFESTOS methodology for developing data warehouses and the Pentaho Suite Community Edition (version 4.8.0 or a higher stable version). The practical study object is the Enterprise of Water and Sewerage Granma.
FABRICATION AND CHARACTERIZATION OF POTENT BIOLARVICIDE SYNTHESIZED FROM METALLIC NANOPARTICLES USING LEAVES OF TINOSPORA CORDIFOLIA

Green synthesis of AgNPs has been reported as safe, low cost and ecofriendly. This methodology uses extracts originating from different plants to reduce silver ions from AgNO3 into nano-sized particles. Bioactive constituents present in plants were analysed by means of phytochemical analysis. Surface Plasmon peak at 430 nm confirms the presence of silver nanoparticles. The presence of the plant-origin capping agents surrounding AgNPs was proven by Fourier-transform infrared spectroscopy. Microbicidal potential of synthesized AgNps using T. cordifolia suggest that 400μl, 300 μl was resistant against B.subtilis(22.5 mm), whereas least inhibition was found against K. pneumoniae(14.5 mm), M. luteus(13 mm). Therefore results suggest that T. cordifolia act as a potent larvicide and it is a suitable plant for the development of novel natural insecticides.
UPFC Integrated With Battery Energy Storage Systems for Stability Improvement

In Electrical Power network, consumer loads are time to time variation in existing transmission system. Loads will not constant means, power quality issues there such as voltage have been flickering and deviations in power supply which make some of the electronic equipments and domestic devices highly sensitive to it . Unified Power Flow Controller (UPFC) is most promising new technologies among the many FACTS devices which can improve the power system operation and power quality problems. To avoid such problems need to find out devices that can provide a backup during the time of voltage sags and such deviations. UPFC joined with batteries through dc-dc chopper have been introduced to improve their ability to exchange real power. The active power injected into the DC-bus is controlled by varying the duty cycle of the switches in the dc-dc chopper while the battery is discharging.
Organisational Citizenship Behaviour and Knowledge Sharing:An Empirical Study

The objective of present study is to examine the relationship between organisational citizenship behaviourand knowledge sharing among employees working in private organisation in Dehradun (U.K). The study aims at examining the relationship between dimension of organisational citizenship behaviour and knowledge sharing.Organisational citizenship behaviour is extrarole behaviour and done voluntarily by the employees with the aim of helping others or supporting the organisation. Knowledge sharing is the process through which experience, ideas and information is shared.Organisational citizenship behaviour promotes good working environment, knowledge sharing among employees, productivity and contributes toorganisational effectiveness. The sample of the study consists of 40 employees working in private organisation in Dehradun (UK). Correlation is used as a tool for analysis and the results show dimensions of OCB i.e. civic virtue, conscientiousness,altruism and courtesy have significant positivecorrelation with knowledge sharing. The composite scores of organisational citizenship behaviour and knowledge sharing are positively related with correlation co-efficient.
A Dynamic MapReduce: Scheduling in Large Cluster

: MapReduce is the program model and an association implementation for processing and generating large data sets. User specify a map function that process a key/value pair to generate a set of intermediate key/value pairs and a reduce function that merge all intermediate values associated with the same intermediate key. MapReduce is important Programming model for building data centres containing ten thousands of nodes. In a Practical data, I/O bound jobs and CPU-bounds jobs, which demand different resources, run simultaneously in the same cluster. In this Paper we gives a new view of the MapReduce model and classify the MapReduce workload into three categories based on their CPU and I/O Utilization. We Design a new dynamic MapReduce workload predict mechanism, MR-Predict mechanism, which detect the workload types on the fly. We propose a Triple-Queue scheduler based on the MR-Predict mechanism. The Triple-Queue could improve the usage of both CPU and disk I/O resources under heterogeneous workload.
AN ANOMALY BASED INSIDER THREAT DETECTION FROM CYBER ACTIVITIES

: The threat of penetrating a company's end result in a collection of actions aimed at violently misusing systems, networks, data and resources. Preventing internal threats is not difficult, as the trusted partner of the concerned company, who allows access to those confidential services. Progressive analysis in identifying internal threat specifically focuses on retrieving methods of uncontrolled behavioral injury for detective task discomfort or abnormal changes in user behavior over time. However, the unpleasant task is that one does not earn honestly in a threatening environment. We propose an improvement logging strategy, a technology that detects internal threats from the user activity chain. Initially, a single-day selection area unit calculated from the user activity log. The array of feature attribute selectors is predefined over the data for each feature over time. Each label sets the data attribute and extracts from the truth below. The XG-boost classifier is used to classify whether the user is malicious or not, and its performance has been compared to various popular methods such as random forest. The CMU Insider Threat Dataset is only used for internal threat notification, providing approximately 14-GB browsing logs for the general public such as logon, application connection, file transfer and e-mail log files.
Monaural adaptive mechanisms in human sound localization

Human sound localization results primarily from the processing of binaural differences in sound level and arrival time for locations in the horizontal plane and of spectral shape cues generated by the head and pinnae for positions in the vertical plane. Both types of cues have to be weighted and mapped to form a single percept of sound location. The experiments in this thesis take a behavioral approach to elucidate several aspects of this cue convergence and mapping. This was done by observing the localization behavior of monaural listeners or by actively manipulating the various localization cues of normal-hearing binaural listeners. The monaural listeners strongly rely on the ambiguous head shadow effect, which may help them to cope with familiar acoustic environments. Only some of these listeners could incorporate spectral cues to localize the sound-source azimuth, but those listeners were also able to localize sound-source elevation. Normal-hearing binaural listeners seem to disregard the spectral cues and the head shadow cues as valid localization cues. However, when faced with degraded binaural cues (as when one of their ears is plugged, at low sound levels), spectral cues do seem to play a role in sound azimuth localization. At normal sound levels, when binaural cues are present, new spectral cues (through application of a mold in one ear) do not degradate sound-azimuth performance. Sound-elevation performance, however, is degradated at the mold-side. Listeners can adapt to these new spectral cues by relearning and remapping these cues to valid locations.
AN ENVELOPE TYPE MODULE: ASYMMETRIC MULTILEVEL INVERTER WITH REDUCED COMPONENTS

This paper presents a new E-Type module for asymmetrical multilevel inverters with reduced components. Each module produces 13 levels with four unequal DC sources and 10 switches. The design of the proposed module makes some preferable features with a better quality than similar modules such as the low number of semiconductors and DC sources and low switching frequency. Also, this module is able to create a negative level without any additional circuit such as an H-bridge which causes reduction of voltage stress on switches. Cascade connection of the proposed structure leads to a modular topology with more levels and higher voltages.MATLAB simulations are presented to validate the proposed module good performance. IndexTerms Asymmetric, components,Matlab, E-Type, multilevel inverter, power electronics. __ ___________________________________________________________________________________________
Consumer learning behavior in choosing electric motorcycles

Abstract The purpose of this paper is to understand the effect of the learning process on consumers' choice behavior for electric motorcycles in Taiwan. The electric motorcycle is a new technological product so consumers need to gather all kinds of information – performance, operating cost, government subsidy policy, etc. – to reduce their uncertainty about the product. In this paper, a four-stage stated preference experiment is designed and a survey applied. At each stage, the survey gives respondents new information about the electric motorcycle. In this process, respondents gather information and update their expectation about electric motorcycles in a Bayesian manner. This paper calibrates a Bayesian learning process model to the data. The results show that respondents have a higher quality perception of the electric motorcycle than the gasoline motorcycle and there is heterogeneous learning across respondents. The manufacturers can use these to target specific consumers to promote the electric motorcycle.
Viscous holographic f(Q) cosmology with some versions of holographic dark energy with generalized cut-offs

The work reported in this paper demonstrates the cosmology of f(Q) gravity and the reconstruction of various associated parameters with different versions of holographic dark energy with generalized cut-offs, where Q = 6 H 2. The Universe is considered to be filled with viscous fluid characterized by a viscous pressure Π = – 3 H ξ, where ξ=ξ0+ξ1H+ξ2(H˙+H2) and H is the Hubble parameter. Considering the power law form of expansion, we have derived the expression of f(Q) under a non-viscous holographic framework and it is then extended to viscous cosmological settings with extended generalized holographic Ricci dark energy. The forms of f(Q) for both the cases are found to be monotonically increasing functions of Q. In the viscous holographic framework, f(Q) is reconstructed as a function of cosmic time t and is found to stay at a positive level with Nojiri-Odintsov cut-off. In these cosmological settings, the slow roll parameters are computed and a scope of exit from inflation and quasi-exponential expansion are found to be available. Finally, it is observed that warm inflationary expansion can be obtained from this model.
Depressed collectors for high-power gyrotrons

An analytic and numerical study of the feasibility of depressed collectors for gyrotrons for accelerator applications is discussed, and a specific design for a 10-GHz 30-MW gyroklystron is realized. The conclusion of the study is that depressed collectors are feasible for gyrotrons of interest for accelerator applications (i.e. P >
Holistic enhancement of the production analysis of bituminous paving operations

The construction and repair of highways are becoming very important in these days of crumbling infrastructure. Costs for these projects have continued to increase. In order for contractors to stay competitive, it is essential that their construction operations be as productive as possible. Money for research usually does not exist for the average contractor. An inexpensive solution for production studies is process simulation, which can help improve the productivity of construction operations. This paper focuses on the paving cycle of a highway resurfacing project, using MicroCyclone simulation software. The process modelling using MicroCyclone is applied readily to any construction cyclic process, and aids the engineer in determining the most economical and efficient way to plan resources for processes. Different production parameters are measured and translated to a utility factor that indicates the performance of the system. Results from the utility factor perspective are considered more sensitive in decision making, owing to the holistic nature of the utility factor. Numerous statistical runs were undertaken, and parameters were weighted and averaged. Based on the holistic analysis, it was possible to establish that 12 trucks were optimal for the system, a determination that cannot be made using deterministic analysis, but that a 7% waste of resources was unavoidable with the existing system of resources. This paper highlights the analytical method of using MicroCyclone output to generate useful information that can be used to compare in detail the performance of different scenarios.
FloW: A Dataset and Benchmark for Floating Waste Detection in Inland Waters

Marine debris is severely threatening the marine lives and causing sustained pollution to the whole ecosystem. To prevent the wastes from getting into the ocean, it is helpful to clean up the floating wastes in inland waters using the autonomous cleaning devices like unmanned surface vehicles. The cleaning efficiency relies on a high-accurate and robust object detection system. However, the small size of the target, the strong light reflection over water surface, and the reflection of other objects on bank-side all bring challenges to the vision-based object detection system. To promote the practical application for autonomous floating wastes cleaning, we present FloW†, the first dataset for floating waste detection in inland water areas. The dataset consists of an image sub-dataset FloW-Img and a multimodal sub-dataset FloW-RI which contains synchronized millimeter wave radar data and images. Accurate annotations for images and radar data are provided, supporting floating waste detection strategies based on image, radar data, and the fusion of two sensors. We perform several baseline experiments on our dataset, including vision-based and radar-based detection methods. The results show that, the detection accuracy is relatively low and floating waste detection still remains a challenging task.
A study on the road friction coefficient estimation and motor torque control for an in-wheel electric vehicle

In this study, a motor torque control algorithm for improving the stability of an in-wheel electric vehicle is proposed. The longitudinal and normal forces acting on the tyre were estimated with the wheel speed, the vehicle acceleration and the motor torque, and a road friction coefficient estimation method based on these factors is suggested. Furthermore, a method for determining the control normal force of each wheel and for limiting the in-wheel motor torque is proposed by introducing the concept of virtual movement of the centre of gravity by the slip ratio. The performance of the proposed in-wheel motor torque control algorithm was validated through MATLAB/Simulink and CarSim co-simulation and real-vehicle tests. The simulations and experimental results show that the in-wheel motor torque control algorithm braked the vehicle with no spin on a slippery road.
Expert Distribution Similarity Model: Feedback methodology for non-imitation based handwriting practice

Learning ﬁne psychomotor skills such as handwriting is a tedious endeavour which requires close supervision of the teacher to master. However, the increasing number of students in classes means less time a teacher can allocate for each student. This adversely aﬀects the development of handwriting in students. Sensor-based technologies can help address this problem, as they are capable of providing feedback to the student whilst the teacher is not present during the student’s writing. While there are multiple sensor-based applications to date for handwriting practice, such applications provide feedback in only for simple tracing over practice tasks. In this paper, we present a conceptual methodology using AI and sensors, for providing feedback in non-tracking tasks that do not have a single correct solution and allow larger variations.
A Comparative Study of Moderate versus High Intensity Exercise Training for Short Duration on Strength and Physical Function in Type II Diabetes Patients: A Randomized Clinical Trial

Background: The purpose of the study was to compare between moderate v/s high intensity exercise training for short duration on physical fitness and physical function in people with Type 2 diabetes. It is a well-known fact that exercise training consisting of aerobic as well as resistance training have beneficial effects in Diabetes. However there is paucity of data, whether short duration training has similar benefits. Methods Sample size estimation after pilot study yielded a sample of 30. The subjects were allotted into two groups’ moderate intensity (20) and high intensity (20) group. Resistance training consisted of seated isolated knee extension with weight cuffs. Aerobic training consisted of cycling on static cycle. Statistical analysis: Pre and Post values of muscle strength, aerobic capacity in both the groups was done by paired T – Test. Unpaired T-test was used to compare the post values of muscle strength, aerobic capacity between groups. This test was used to compare pre and post values of Patient specific functional scale Wilcoxon sign rank test was used. Mann Whitney’s u test was used to compare post values of Patient specific functional scale. Conclusion: There was significant improvement in both the groups when training was done for shorter duration.
Summary Reactive oxygen species mediate Rac-induced loss of cell-cell adhesion in primary human endothelial cells

The endothelial lining of the vascular system represents an important barrier to plasma proteins, solutes and leukocytes. Vascular integrity is largely dependent on endothelial cell-cell adhesion mediated by vascular endothelial (VE)-cadherin (Cadherin-5, CD144) (Carmeliet, 2000; Dejana et al., 1999). VE-cadherin is a transmembrane glycoprotein that is complexed via its cytoplasmic tail to various proteins, such as the armadillo-family members βor γ-catenin, which are in turn associated with α-catenin, which links the complex to the actin cytoskeleton (Lampugnani et al., 1995). In addition, VEcadherin is associated with p120 catenin, which was recently shown to act as a negative regulator of the small GTPase Rho (Noren et al., 2000). Like the other cadherins, VE-cadherin mediates calciumdependent, homophylic intercellular adhesion and is an important regulator of endothelial permeability (Corada et al., 1999; Hordijk et al., 1999). Inhibition of VE-cadherinmediated cell-cell adhesion has pronounced effects on the organisation of the endothelial actin cytoskeleton and vice versa (Hordijk et al., 1999; Wojciak-Stothard et al., 1998). Transfection studies have shown that VE-cadherin is involved in endothelial cell migration (Breviario et al., 1995) and survival (Carmeliet et al., 1999) and appears to be required for the organisation of vascular structures in embryoid bodies, angiogenesis and tumor growth (Liao et al., 2000). The mechanisms that control the function of VE-cadherin are not well understood, but they have been suggested to involve indirect signaling through changes in the actin cytoskeleton and more direct signaling through tyrosine phosphorylation of VE-cadherin or its associated proteins (Esser et al., 1998; Lampugnani et al., 1997). Recent studies have underscored the important role for the actin cytoskeleton in regulating cadherin function and cell-cell adhesion in epithelial and endothelial cells. Consequently, Rho family GTPases have been identified as regulators of cadherinbased cell-cell adhesion. In epithelial cells, Rac, Rho and CDC42 have all been implicated in the formation and control of E-cadherin-mediated cell-cell adhesion (Braga et al., 1997; Braga et al., 1999; Hordijk et al., 1997; Takaishi et al., 1997). In endothelial cells, the functional link between Rho-like GTPases and VE-cadherin function is less clear. Inhibition of Rho-dependent contractility has been shown to prevent receptor-mediated increases in endothelial permeability 1837
Survey on Security based Watermarking Techniques in FPGA Design

: The Watermarking is an intellectual property (IP) protection technique. It can protect field-programmable gate array (FPGA) IPs from infringement. IP protection of hardware designs is the most important requirement for many FPGA intellectual property vendors. Digital watermarking has become an innovative technology for IP protection in recent years. This paper proposes the publicly verifiable watermarking for intellectual property protection in FPGA design. The chaos-based zero knowledge verification protocol is used in this watermarking detection technique. The time stamping is also used and it can resiliently resist the sensitive information leakage and embedding attacks, and is thus robust to the cheating from the prover, verifier, or third party. The synthesis tool Xilinx ISE 9.1 and different types of Xilinx FPGA chips are used to verify and implement the watermarking scheme. The zero-knowledge protocol proposed in this paper is implemented by MATLAB and C programming language, running on