LDA + U Study of Induced Half Metallicity in Cr-Doped GaN

Half-metallic ferromagnetism in the Ga_{1 ? x}Cr _x N compound at different concentrations, x = 25, 12.5 and 6.25 %, have been investigated using density functional theory as implemented in code Spanish Initiative for Electronic Simulations with Thousands of Atoms (SIESTA) using LDA + U as exchange-correlation (XC) potential, to find out the possibility of new diluted DMSs. The outcomes reveal that transition metal atom (Cr) doping in GaN induces ferromagnetism. The 3d levels of the TM ion originate a half-metallic gap at the Fermi level in the majority spin channel for all concentrations. Moreover, diluted magnetic semiconductor compounds retain the half-metallic nature at all concentrations, i.e., x = 0.25, 0.125 and 0.0625, with 100 % spin polarization at the Fermi level (E _F). The total magnetic moment of these compounds is due to Cr-3d states, and the existence of a small magnetic moment on Ga and N, non-magnetic atoms, for all doping concentrations is a consequence of p-d hybridization of Cr-d and N-p states. The calculated values of s-d exchange constant N α and p-d exchange constant N βconfirm the ferromagnetic character of the Cr-doped GaN compound.     

Hydrostatic Pressure Effect on Ga<Subscript>0.75</Subscript>Cr<Subscript>0.25</Subscript>As DMS: DFT Study

This paper studies the first-principles calculations of the effect of hydrostatic pressure on the structural, electronic and magnetic properties of Ga_0.75Cr_0.25As dilute magnetic semiconductor in zb (B3) phase. High-pressure behaviour of Ga_0.75Cr_0.25As has been investigated between 0 and 100 GPa. The calculations have been performed using DFT as implemented in code SIESTA using LDA + U as an exchange-correlation (XC) potential. The study of band structures shows half-metallic ferromagnetic nature with 100% spin polarization. Under application of external pressure, the valence band and conduction band are shifted from their positions which lead to modification of electronic structure.     

Monitoring the Coefficient of Variation Using the Side Sensitive Group Runs Chart

Many quality characteristics have means and standard deviations that are not independent. Instead, the standard deviations of these quality characteristics are proportional to their corresponding means. Thus, monitoring the coefficient of variation (CV), for these quality characteristics, using a control chart has gained remarkable attention in recent years. This paper presents a side sensitive group runs chart for the CV (called the SSGR CV chart). The implementation and optimization procedures of the proposed chart are presented. Two optimization procedures are developed, i.e. (i) by minimizing the average run length (ARL) when the shift size is deterministic and (ii) by minimizing the expected average run length (EARL) when the shift size is unknown. An application of the SSGR CV chart using a real dataset is also demonstrated. Additionally, the SSGR CV chart is compared with the Shewhart CV, runs rules CV, synthetic CV and exponentially weighted moving average CV charts by means of ARLs and standard deviation of the run lengths. The performance comparison is also conducted using EARLs when the shift size is unknown. In general, the SSGR CV chart surpasses the other charts under comparison, for most upward and downward CV shifts. Copyright © 2015 John Wiley & Sons, Ltd.     

Infrared Spectroscopy-Based Chemometric Analysis for Lard Differentiation in Meat Samples

One of the most pressing concerns for the consumer market is the detection of adulteration in meat products due to their preciousness. The rapid and accurate identification mechanism for lard adulteration in meat products is highly necessary, for developing a mechanism trusted by consumers and that can be used to make a definitive diagnosis. Fourier Transform Infrared Spectroscopy (FTIR) is used in this work to identify lard adulteration in cow, lamb, and chicken samples. A simplified extraction method was implied to obtain the lipids from pure and adulterated meat. Adulterated samples were obtained by mixing lard with chicken, lamb, and beef with different concentrations (10%–50% v/v). Principal component analysis (PCA) and partial least square (PLS) were used to develop a calibration model at 800–3500 cm⁻¹. Three-dimension PCA was successfully used by dividing the spectrum in three regions to classify lard meat adulteration in chicken, lamb, and beef samples. The corresponding FTIR peaks for the lard have been observed at 1159.6, 1743.4, 2853.1, and 2922.5 cm⁻¹, which differentiate chicken, lamb, and beef samples. The wavenumbers offer the highest determination coefficient R² value of 0.846 and lowest root mean square error of calibration (RMSEC) and root mean square error prediction (RMSEP) with an accuracy of 84.6%. Even the tiniest fat adulteration up to 10% can be reliably discovered using this methodology.     

The mask of (2b + 4)-point n-ary subdivision scheme

In this paper, we present general formulae for the mask of (2b + 4)-point n-ary approximating as well as interpolating subdivision schemes for any integers ${b\,\geqslant\,0}$ and ${n\,\geqslant\,2}$ . These formulae corresponding to the mask not only generalize and unify several well-known schemes but also provide the mask of higher arity schemes. Moreover, the 4-point and 6-point a-ary schemes introduced by Lian [Appl Appl Math Int J 3(1):18–29, 2008] are special cases of our general formulae.     

A Layered-Encoding Cascade Optimization Approach to Product-Mix Planning in High-Mix–Low-Volume Manufacturing

High-mix-low-volume (HMLV) production is currently a worldwide manufacturing trend. It requires a high degree of customization in the manufacturing process to produce a wide range of products in low quantity in order to meet customers' demand for more variety and choices of products. Such a kind of business environment has increased the conversion time and decreased the production efficiency due to frequent production changeover. In this paper, a layered-encoding cascade optimization (LECO) approach is proposed to develop an HMLV product-mix optimizer that exhibits the benefits of low conversion time, high productivity, and high equipment efficiency. Specifically, the genetic algorithm (GA) and particle swarm optimization (PSO) techniques are employed as optimizers for different decision layers in different LECO models. Each GA and PSO optimizer is studied and compared. A number of hypothetical and real data sets from a manufacturing plant are used to evaluate the performance of the proposed GA and PSO optimizers. The results indicate that, with a proper selection of the GA and PSO optimizers, the LECO approach is able to generate high-quality product-mix plans to meet the production demands in HMLV manufacturing environments.     

RUSHES—an annotation and retrieval engine for multimedia semantic units

Multimedia analysis and reuse of raw un-edited audio visual content known as rushes is gaining acceptance by a large number of research labs and companies. A set of research projects are considering multimedia indexing, annotation, search and retrieval in the context of European funded research, but only the FP6 project RUSHES is focusing on automatic semantic annotation, indexing and retrieval of raw and un-edited audio-visual content. Even professional content creators and providers as well as home-users are dealing with this type of content and therefore novel technologies for semantic search and retrieval are required. In this paper, we present a summary of the most relevant achievements of the RUSHES project, focusing on specific approaches for automatic annotation as well as the main features of the final RUSHES search engine.     

Improving cache locking performance of modern embedded systems via the addition of a miss table at the L2 cache level

To confer the robustness and high quality of service, modern computing architectures running real-time applications should provide high system performance and high timing predictability. Cache memory is used to improve performance by bridging the speed gap between the main memory and CPU. However, the cache introduces timing unpredictability creating serious challenges for real-time applications. Herein, we introduce a miss table (MT) based cache locking scheme at level-2 (L2) cache to further improve the timing predictability and system performance/power ratio. The MT holds information of block addresses related to the application being processed which cause most cache misses if not locked. Information in MT is used for efficient selection of the blocks to be locked and victim blocks to be replaced. This MT based approach improves timing predictability by locking important blocks with the highest number of misses inside the cache for the entire execution time. In addition, this technique decreases the average delay per task and total power consumption by reducing cache misses and avoiding unnecessary data transfers. This MT based solution is effective for both uniprocessors and multicores. We evaluate the proposed MT-based cache locking scheme by simulating an 8-core processor with 2 levels of caches using MPEG4 decoding, H.264/AVC decoding, FFT, and MI workloads. Experimental results show that in addition to improving the predictability, a reduction of 21% in mean delay per task and a reduction of 18% in total power consumption are achieved for MPEG4 (and H.264/AVC) by using MT and locking 25% of the L2. The MT results in about 5% delay and power reductions on these video applications, possibly more on applications with worse cache behavior. For the FFT and MI (and other) applications whose code fits inside the level-1 instruction (I1) cache, the mean delay per task increases only by 3% and total power consumption increases by 2% due to the addition of the MT.     

Exploring the relationship between Internet ethics in university students and the big five model of personality

The widespread use of the Internet and the convenient mechanism it provides, such as easy access, easy downloads, and easy copy and paste functions have made many types of unethical behaviors easier, particularly those involving students in academic settings. Among the issues in ethics within the academic environment that can be triggered by the Internet are fraudulence, plagiarism, falsification, delinquency, unauthorized help, and facility misuse. Given these issues, the study seeks to investigate the extent to which students at a public university in Malaysia engage in such unethical behavior and their relationship with the big five personality model. This study was conducted using a survey method of 252 students in three different academic faculties. The results of factor analyses confirm and refine the reliability of the scales for both big five personality variables and unethical Internet behaviors as conceptualized through Internet triggered academic dishonesty (ITADS). The findings indicate that personality traits such as (1) agreeableness, (2) conscientiousness and (3) emotional stability are significantly and negatively correlated with unethical Internet behavior in university students. Significant differences in facility misuse are also observed between the three academic faculties investigated. This research should provide significant contributions to educators in designing the computer ethics curriculum and in allowing for educational institutions as well as other organizations in developing relevant policies and guidelines on matters pertaining to academic conduct, utilization of computers and Internet, and recruitment exercises.