Comparative Analysis of Control Techniques for PWM Rectifiers in Grid Connected Distributed Generation Systems Based on VOC and DPC

This paper presents Virtual flux based and Voltage based control schemes for PWM rectifiers in grid connected distributed generation systems from renewable sources are presented. In particular, the so-called Voltage Oriented Control (VOC), Direct Power Control (DPC), two DPC based techniques to minimize the Common Mode (CM) emissions called DPC-EMC1 and DPC-EMC2 set up by the authors and their versions based on virtual flux. All the described techniques have been implemented using MATLAB/Simulink® (Classic version 8.2 Release name (R2013b)) and compared with each other. Theoretical background with results of simulations is provided. The advantages and disadvantages of the individual control strategies are documented

Computational Fluid Dynamics: Science of the Future

This paper will answer a list of questions regarding the computational fluid dynamics (CFD). It will give a brief discussion regarding the significance of CFD and will recount the pros and cons of applying CFD. The following assignment will also give an overview of the terms that come under the ambit of CFD like discretization, numerical grid, initial conditions, boundary conditions, sweep, convergence, and turbulence modeling. The researchers such as Guang Xu et al. (2017), Raase and Nordström (2015), and Frigg et al. (2009) concluded that CFD is the science of the future as it cares in all aspects of life in the present and the future, CFD science treats the fluids mainly the air and the water as good and bad, bad when the CFD tries to find a way through the air and the water to get the minimum resistant for cost-effective and less fuel burning for greener, healthier and better world in many applications such submarines, air crafts, automobiles, ships, trains, motorbikes and too many other applications

Assessment of Impacts of Climate Change on Hydro-meteorological Ecosystem Services and Water Stress in Lake Kyoga Catchment

Through review of several studies on climate change, an attempt was made to investigate the sensitivity of water resources to climate change over Lake Kyoga catchment. Climate change is predicted to increase the frequency of climatic extremes that can lead to loss of life and property. This study was mainly to analyze the water stress arising from the impacts of climate change on hydro-meteorological ecosystem services. The methodology of the study consists of analysis of available meteorological and hydrological observations, analysis of Global Weather Data for ArcGIS/SWAT output data and finally seasonal performance of precipitation and temperature using Climate Predictability Tool outputs. The Correlation Percentage change was used to estimate the rate of change of flow and water levels under a changed climate. The outputs for different stations showed that climate change has already affected water resources in Lake Kyoga catchment with continuous reduction in water levels of 6%. The results of the study revealed that climate change is likely to increase precipitation by 10-20% received during the wet seasons resulting in higher stream flow and a reduction of 20-40% of precipitation during the dry seasons. The GCMs also demonstrated an increase in maximum and minimum temperatures of 1 to 30C by 2065 with minimum temperatures increasing more rapidly compared to the maximum temperatures for the two scenarios (RCP4.5 and RCP8.5). The strategies for adaptation and mitigation measures have been identified

Time-aware Traffic Shaper using Time-based Packet Scheduling on Intel I210

By 2015, the Institute of Electrical and Electronics Engineers (IEEE) time-sensitive networking (TSN) task group has released several TSN standards. Amongst them is 802.1Qbv, also known as a time-aware shaper, aiming to provide performance assurances of latency and delivery variation to enable applications in a TSN network. While there are several products and evaluation kits that employ 802.1Qbv in the market now, it is still not widely adopted yet due to the maturity of the standard. Hardware-enabled 802.1Qbv use hardware queues and timers to achieve accurate transmission of packets in the switch and bridge. This research aims to investigate the feasibility of using an existing end-station Ethernet controller, Intel I210, and its launch time control feature (commonly known as time-based packet scheduling) to shape traffic compatible to 802.1Qbv-enabled network bridges. A software solution is developed by implementing a software configurable gate-control list and employing open-source Linux RFC patches for per-packet transmit time specification. By configuring the kernel and mapping kernel-layer traffic classes to the hardware queues, packets can be transmitted out at precise times while attaching 802.1Q VLAN tags, required by bridges to identify packets. Through analysis, it is found that this solution will require an additional 30 μs transmit offset to be used effectively. That is 55% more time is needed to transmit a packet in a back-to-back connection and 17.6% on a 3-switch network to improve period peak jitter performance to just 8.9  μs compared to 1 ms on solutions that send packets out periodically using software sleep functions

Hybrid Power Systems for Commercial Application in Kenya

The cost, availability and stability of power are parameters that greatly define the quality of energy supplied by a generating system. A hybrid power system with different sources of energy must be properly designed in order to capitalize on the positive features of the deployed resources. Hybrid power system optimization is a process that allows for deliberate attainment of desired output from a power system. In this paper, a learning institution, East African School of Aviation (EASA) was selected as a case study for investigating the outcome of harnessing local energy resources to serve a commercial consumer in Kenya. A cost competitive hybrid power system was obtained through Simulation and optimization processes

Method and Apparatus for a Differential Localized Microscopy System Based on Position Sensitive Detector

A precise measurement of position using a Position Sensitive Detector (PSD) is fundamental in mitigating the geometric error factors that are caused by the pincushion-type distortion of these sensors. These errors can be addressed by implementing a differential localized method to significantly reduce signal to noise ratio (SNR) in PSD and the microscopy system. The differential method based on Time difference of Arrival (TDoA) is proposed and implemented in this research. The simulation and the actual results of the system further confirm the significant improvement in accuracy and precision of the system

MapReduce : Simplified Data Processing on Large Cluster

MapReduce is a data processing approach, where a single machine acts as a master, assigning map/reduce tasks to all the other machines attached in the cluster. Technically, it could be considered as a programming model, which is applied in generating, implementation and generating large data sets. The key concept behind MapReduce is that the programmer is required to state the current problem in two basic functions, map and reduce. The scalability is handles within the system, rather than being handled by the concerned programmer. By applying various restrictions on the applied programming style, MapReduce performs several moderated functions such fault tolerance, locality optimization, load balancing as well as massive parallelization. Intermediate k/v pairs are generated by the Map, and then fed o the reduce workers by the use of the incorporated file system. The data received by the reduce workers is then merged using the same key, to produce multiple output file to the concerned user (Dean & Ghemawat, 2008). Additionally, the programmer is only required to master and write the codes regarding the easy to understand functionality

Face Recognition System Based on Kernel Discriminant Analysis, K-Nearest Neighbor and Support Vector Machine

Although many methods have been implemented in the past, face recognition is still an active field of research especially after the current increased interest in security. In this paper, a face recognition system using Kernel Discriminant Analysis (KDA) and Support Vector Machine (SVM) with K-nearest neighbor (KNN) methods is presented. The kernel discriminates analysis is applied for extracting features from input images. Furthermore, SVM and KNN are employed to classify the face image based on the extracted features. This procedure is applied on each of Yale and ORL databases to evaluate the performance of the suggested system. The experimental results show that the system has a high recognition rate with accuracy up to 95.25% on the Yale database and 96% on the ORL, which are considered very good results comparing with other reported face recognition systems

Risk Assessment and Management in Construction Industries

This paper aims to deal with construction industry risks. It deals with all type of construction industry types such as small house, malls, and huge buildings. Many accidents can be happened in the sites, so it is important that appropriate measure are taken into consideration to help in curbing the menace to improve safety in the working environment both within and the surrounding. The researchers concluded that the risks which can be avoided should be avoided to reduce the number of accidents that happen in the working environment. Rules and regulations that are clear and well understood by the workers are important in eliminating or reducing hazards experienced within the working environment. With adequate training and strict policies put in place, it is possible to deal with the risks at the workplace. The management should take responsibility and consider it as a necessity to introduce adequate measures and policies that can govern all activities undertaken in construction sites

A Survey on Confidential Cloud Data under Secure Key Exposure

Latest records display a effective attacker which breaks facts confidentiality with the resource of obtaining cryptographic keys, by using the usage of way of coercion or backdoors in cryptographic software program. As soon as the encryption secrets uncovered, the only possible diploma to maintain information confidentiality is to restrict the attacker’s access to the ciphertext. This can be finished, as an instance, with the resource of spreading ciphertext blocks in the course of servers in a couple of administrative domain names, therefore assuming that the adversary cannot compromise them all. However, if data is encrypted with present schemes, an adversary prepared with the encryption key, can nevertheless compromise an unmarried server and decrypt the ciphertext blocks saved therein. On this paper, we observe records confidentiality in opposition to an adversary which knows the encryption key and has get admission to a massive fraction of the ciphertext blocks. To this quit, we advise Bastion, a singular and green scheme that ensures data confidentiality notwithstanding the reality that the encryption secrets leaked and the adversary has access to nearly all ciphertext blocks. We analyze the security of Bastion, and we examine its standard overall performance via manner of a prototype implementation. We also talk realistic insights with admire to the combination of Bastion in business dispersed garage structures. Our evaluation results endorse that Bastion is well-applicable for integration in existing structures since it incurs less than 5% overhead compared to existing semantically relaxed encryption modes