Automation of Global Hiring Process

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COMPUTATIONAL EVALUATION OF SOME BASIC MATERIAL PARAMETERS IN COBALT-ALUMINUM ALLOYS

The First Principles Density Functional Theory study is conducted on BCC Co-Al based solid solution which obeys Vegard’s law. Chemical bond energies are calculated beyond 1NN interactions as second-nearest-neighbor and third-nearest-neighbor chemical bond energy values are significant and contribute to the total energy of the alloy. Elastic energy developed in the alloys due to the atomic radius misfit between solute and solvent atoms is also considered. Effects of atomic ordering on 1NN, 2NN, and 3NN chemical ordering energies and lattice parameters are investigated

Multilevel Converter-Based Dual-Frequency Induction Heating Power Supply

Most existing power supplies for induction heating equipment produce voltage at a single (adjustable) frequency. Recently, however, induction heating power supplies that produce voltage at two (adjustable) frequencies have been researched and even commercialized. Dual-frequency power supplies are a significant development for heat-treating workpieces with uneven geometries, such as gears, since different portions of such workpieces are heated dissimilarly at a single frequency and so require a two step process using a single-frequency power supply. On the other hand, a dual-frequency power supply can achieve the desired result for such workpieces in a one step process. However, the existing approaches to dual-frequency voltage generation could be improved to achieve higher efficiency, improved control, reduced electromagnetic interference and greater reliability. This paper proposes the use of multilevel converters for providing induction heating power at two frequencies simultaneously. It also describes how the stepping angles for the desired output from this converter were determined. Furthermore, experimental results are presented as a verification of the analysis

Multilevel Inverter-Based Dual-Frequency Power Supply

Most existing power supplies for induction heating equipment produce voltage at a single (adjustable) frequency. Recently, however, induction heating power supplies that produce voltage at two (adjustable) frequencies simultaneously have been introduced and commercialized. These represent a significant development particularly for heat-treating workpieces with uneven geometries, such as gears. Still, the existing approaches to dual-frequency voltage generation could be improved upon to achieve better control, higher efficiency, and reduced electromagnetic interference. This letter proposes the use of multilevel inverters for providing power at two frequencies simultaneously. It describes how the stepping angles for the desired output from such inverters can be determined. Furthermore, experimental results are presented as verification of the concept and to demonstrate the achievement of improved harmonic level control and reduced device switching frequency

Multilevel Inverters with Equal or Unequal Sources for Dual-Frequency Induction Heating

Most existing power supplies for induction heating equipment produce voltage at a single (adjustable) frequency. Recently, however, induction heating power supplies that produce voltage at two (adjustable) frequencies have been researched and even commercialized. Dual-frequency power supplies are a significant development for heat-treating workpieces with uneven geometries, such as gears, since different portions of such workpieces are heated dissimilarly at a single frequency and so require a two step process using a single-frequency power supply. On the other hand, a dual-frequency power supply can achieve the desired result for such workpieces in a one step process. This paper proposes the use of multilevel converters for providing induction heating power at two frequencies simultaneously, which may achieve higher efficiency, improved control, reduced electromagnetic interference and greater reliability than existing dual-frequency power supplies. It also describes how the stepping angles for the desired output from such converters can be determined for both the equal and unequal source cases. Furthermore, experimental results are presented as a verification of the analysis

Timing Synchronization at the Relay Node in Physical Layer Network Coding

In recent times, there has been an increased focus on the problem of information exchange between two nodes using a relay node. The introduction of physical layer network coding has improved the throughput efficiency of such an exchange. In practice, the reliability of information exchange using this scheme is reduced due to synchronization issues at the relay node. In this thesis, we deal with timing synchronization of the signals received at the relay node. The timing offsets of the signals received at the relay node are computed based on the propagation delays in the transmitted signals. However, due to the random attenuation of signals in a fading channel, the near far problem is inherent in this situation. Hence, we aim to design near far resistant delay estimators for this system. We put forth four algorithms in this regard. In all the algorithms, propagation delay of each signal is estimated using a known preamble sent by the respective node at the beginning of the data packet. In the first algorithm, we carefully construct the preamble of each data packet and apply the MUSIC algorithm to overcome the near far problem. The eigenstructure of the correlation matrix is exploited to estimate propagation delay. Secondly, the idea of interference cancellation is implemented to remove the near far problem and delay is estimated using a correlator. Thirdly, a modified decorrelating technique is presented to negate the near far problem. Using this technique we aim to obtain an estimate of the weak user's delay that is more robust to errors in the strong user's delay estimate. In the last algorithm, pilot signals with desired autocorrelation and cross correlation functions are designed and a sliding correlator is used to estimate delay. Even though this approach is not near far resistant, performance results demonstrate that for the length's of preamble considered, this algorithm performs similar to the other algorithms

Relation of proximate analysis with DTA due to spontaneous heating of some Indian coals

The auto oxidation of coal ultimately leads to spontaneous combustion which is the major root cause for the disastrous of coal mine. It has been a major problem in the leading producing coal countries like Australia, India and China. Therefore the assessment for this combustion is very much necessary. It depends upon different characteristics and properties of coal. Once if the combustion of coal has been occurred, it is very difficult to control which also disturbs the environment of the surroundings of the mine. The spontaneous heating susceptibility of different coals varies over a wide range and it is important to assess their degree of proneness for taking preventive measures against the occurrence of fires to avoid loss of lives and property, sterilization of coal reserves and environmental pollution and raise concerns about safety and economic aspects of mining etc. This B.Tech dissertation deals with the relation of proximate analysis of coal with DTA-TG and due to the spontaneous heating tendency of some Indian coal. Eight insitu coal samples for the project were collected from SECL and SCCL mines, both from opencast as well as underground workings. The project deals with determination of spontaneous heating susceptibility of coal samples by Differential thermal analysis and its relation with proximate analysis of coal samples. The intrinsic properties as well as susceptibility indices of the coal samples were determined by following experimental techniques: i) Proximate analysis ii) Differential thermal analysis (DTA-TG) It was observed that the Proximate analysis values can be obtained by using small amount of sample and the volatile matter increases with the reduction in the weight of sample and the Transition temperature obtained from the DTA-TG plot cannot be taken as a sole parameter to assess the spontaneous heating of coal, rather Stage IIB and Stage II slopes give a better idea

Hybrid Approach for Prediction of Cardiovascular Disease Using Class Association Rules and MLP

:  In data mining classification techniques are used to predict group membership for data instances. These techniques are capable of processing a wider variety of data and the output can be easily interpreted. The aim of any classification algorithm is the design and conception of a standard model with reference to the given input. The model thus generated may be deployed to classify new examples or enable a better comprehension of available data.  Medical data classification is the process of transforming descriptions of medical diagnoses and procedures used to find hidden information. Two experiments are performed to identify the prediction accuracy of Cardiovascular Disease (CVD).A hybrid approach for classification is proposed in this paper by combining the results of the associate classifier and artificial neural networks (MLP).  The first experiment is performed using associative classifier to identify the key attributes which contribute more towards the decision by taking the 13 independent attributes as input. Subsequently classification using Multi Layer Perceptrons (MLP) also performed to generate the accuracy of prediction using all attributes. In the second experiment, identified key attributes using associative classifier are used as inputs for the feed forward neural networks for predicting the presence or absence of CVD

AdaMD: Adaptive Mapping and DVFS for Energy-efficient Heterogeneous Multi-cores

Modern heterogeneous multi-core systems, containing various types of cores, are increasingly dealing with concurrent execution of dynamic application workloads. Moreover, the performance constraints of each application vary, and applications enter/exit the system at any time. Existing approaches are not efficient in such dynamic scenarios, especially if applications are unknown, as they require extensive offline application analysis and do not consider the runtime execution scenarios (application arrival/completion, and workload and performance variations) for runtime management. To address this, we present AdaMD, an adaptive mapping and dynamic voltage and frequency scaling (DVFS) approach for improving energy consumption and performance. The key feature of the proposed approach is the elimination of dependency on offline profiled results while making runtime decisions. This is achieved through a performance prediction model having a maximum error of 7.9% lower than the previously reported model and a mapping approach that allocates processing cores to applications while respecting performance constraints. Furthermore, AdaMD adapts to runtime execution scenarios efficiently by monitoring the application status, and performance/workload variations to adjust the previous DVFS settings and thread-to-core mappings. The proposed approach is experimentally validated on the Odroid-XU3, with various combinations of diverse multi-threaded applications from PARSEC and SPLASH benchmarks. Results show energy savings of up to 28% compared to the recently proposed approach while meeting performance constraints