Glassy Chimeras could be blind to quantum speedup: Designing better benchmarks for quantum annealing machines

Recently, a programmable quantum annealing machine has been built that minimizes the cost function of hard optimization problems by adiabatically quenching quantum fluctuations. Tests performed by different research teams have shown that, indeed, the machine seems to exploit quantum effects. However experiments on a class of random-bond instances have not yet demonstrated an advantage over classical optimization algorithms on traditional computer hardware. Here we present evidence as to why this might be the case. These engineered quantum annealing machines effectively operate coupled to a decohering thermal bath. Therefore, we study the finite-temperature critical behavior of the standard benchmark problem used to assess the computational capabilities of these complex machines. We simulate both random-bond Ising models and spin glasses with bimodal and Gaussian disorder on the D-Wave Chimera topology. Our results show that while the worst-case complexity of finding a ground state of an Ising spin glass on the Chimera graph is not polynomial, the finite-temperature phase space is likely rather simple: Spin glasses on Chimera have only a zero-temperature transition. This means that benchmarking optimization methods using spin glasses on the Chimera graph might not be the best benchmark problems to test quantum speedup. We propose alternative benchmarks by embedding potentially harder problems on the Chimera topology. Finally, we also study the (reentrant) disorder-temperature phase diagram of the random-bond Ising model on the Chimera graph and show that a finite-temperature ferromagnetic phase is stable up to 19.85(15)% antiferromagnetic bonds. Beyond this threshold the system only displays a zero-temperature spin-glass phase. Our results therefore show that a careful design of the hardware architecture and benchmark problems is key when building quantum annealing machines.Comment: 8 pages, 5 figures, 1 tabl

Using Color Spaces HSV, YIQ and Comparison in Analysis Hazy Image Quality

Analysis images hazy is difficult problem, thus these images need to determined quality the after dehazing. In this paper, were compared to, HSV, YIQ color spaces, adopted in analyze the dust images. we designed the system captured images which graded for high to very low dusty by using HeNe laser, in these images we calculated the normalize mean square error (NMSE) for each components in HSV, YIQ and RGB color space separately, and the basic components in the structure similarity Index (SSIM) are (contrast, structure and luminance) moreover the mean for all has been calculated. We noted from results spaces, HSV, YIQ chromatic that there is a similarity in analysis of images dusty when compared. This means that the use of any color space gives almost the same results Keywords: The hazy image, contrast, Image quality, Intensity, luminance HSV, YIQ and RGB color spaces. DOI: 10.7176/APTA/76-03 Publication date:March 31st 201

Determinants of Exclusive Breastfeeding and Patterns of Complementary Feeding Practices in Mecca City, Saudi Arabia

Background: The World Health Organization (WHO) recommends optimal feeding practices during infancy and early childhood for better health and growth of children. Objective: To determine the factors affecting exclusive breastfeeding (EBF) duration and the time of introducing complementary feeding (CF) in Mecca City, Saudi Arabia. Methods: This cross-sectional study recruited 814 Saudi mothers. All mothers filled out a closed questionnaire on family sociodemographics, health status of mothers and infants, and postpartum breastfeeding habits and patterns. The patterns of CF and bottle-feeding were examined, and binary logistic regression was performed. Results: The mean ± standard deviation EBF duration was 4.6 ± 2.5 months. The EBF rate showed a sharp decrease from 50.6% at birth to 14.4% at 6 months among children. Employment of mothers, weight at childbirth <2.5 kg, weight of 2.6–3 kg at child birth, postnatal disease in infants, and pacifier use for infants were associated with a low EBF rate. Intermediate education of the mother was found to increase EBF duration as compared to mothers with higher levels of education. Most mothers introduced plant-based CFs to infants at 4 months of age (median), but animal-based CFs were introduced only after 8 months (median). The median age of starting milk formula was 3 months. Conclusion and Recommendation: The reported rate of EBF is far below the current international recommendations. The patterns of CF practices and bottle-feeding differ widely from the WHO recommendations in Mecca City. National campaigns should be implemented to promote EBF in Saudi Arabia

Determine Image Quality Enhanced by Using the Suggested Algorithm

In this research has been improved the brightness and contrast through a new algorithm suggestion based on the algorithm retinex and algorithm settle histogram. Use retinex algorithm for homogeneous regions and algorithm settle histogram for edge regions and using effective Sobel. The comparison showed between the three methods by calculating the quality standards (μ, σ) and by observing the results that the Suggested method has successfully in enhancement brightness and contrast are almost equal compared with other methods. Keywords: Image quality, Scale retinex, Histogram, Mean, Standard deviation, Brightness, Contrast. DOI: 10.7176/APTA/76-04 Publication date:March 31st 201

A Domain-Region Based Evaluation of ML Performance Robustness to Covariate Shift

Most machine learning methods assume that the input data distribution is the same in the training and testing phases. However, in practice, this stationarity is usually not met and the distribution of inputs differs, leading to unexpected performance of the learned model in deployment. The issue in which the training and test data inputs follow different probability distributions while the input-output relationship remains unchanged is referred to as covariate shift. In this paper, the performance of conventional machine learning models was experimentally evaluated in the presence of covariate shift. Furthermore, a region-based evaluation was performed by decomposing the domain of probability density function of the input data to assess the classifier's performance per domain region. Distributional changes were simulated in a two-dimensional classification problem. Subsequently, a higher four-dimensional experiments were conducted. Based on the experimental analysis, the Random Forests algorithm is the most robust classifier in the two-dimensional case, showing the lowest degradation rate for accuracy and F1-score metrics, with a range between 0.1% and 2.08%. Moreover, the results reveal that in higher-dimensional experiments, the performance of the models is predominantly influenced by the complexity of the classification function, leading to degradation rates exceeding 25% in most cases. It is also concluded that the models exhibit high bias towards the region with high density in the input space domain of the training samples

Strategic project management approach to the study of large-scale software development using system dynamics

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 122-123).Large-scale software engineering organizations have traditionally used plan-driven, heavyweight, waterfall-style approaches for the planning, execution, and monitoring of software development efforts. This approach often results in relatively long development schedules that are susceptible to failure, especially in a rapidly changing environment: Schedule pressure, defects and requirements changes, can drive endless redesign, delay the project, and incur extra cost. Many in the commercial software world have dealt with these pressures by adopting Agile Software Development, an approach designed to be flexible and responsive to high-change environments. Software development teams that are said to employ "Agile development" in effect practice a variety of "agile methods". These practices are advertised to reduce coordination costs, to focus teams, and to produce stable product iterations that can be released incrementally. Agile software development has become a de-facto approach to the engineering of software systems in the commercial world, and is now entering the aerospace and defense sectors. The APD model developed in this research aids in the understanding of the impact that alternative combinations of Agile practices, combined with different management policies, have on project performance, compared to a waterfall approach. This research culminates in a formulation of insights and recommendations for how to integrate Agile practices into a large-scale software engineering organization.by Firas Glaiel.S.M

A simulation study of video conferencing system over IEEE 802.11n Wireless LAN

Wireless local area network (WLAN) is the core of the classic wireless communications systems and owns the infrastructure which wide spreads in many regions in the world. IEEE 802.11n is an attractive standard of WLAN and offers a data capacity of the cell. This paper estimates the maximum limits of the IEEE 802.11n standard cell as a term of number of users which are successfully served by the cell in case of video conference application. The results shown that, the cell of 802.11n could serve about 9 users under the service of video conference in case of 20MHz channel bandwidth before congestion occurs while the 40MHz channel could support 18 users

Agile Project Dynamics: A System Dynamics Investigation of Agile Software Development Methods

While Agile software development has many advocates, acceptance in the government and defense sectors has been limited. To address questions of meanings to the term “Agile,” we examine a range of Agile methods practiced and develop a framework of seven characteristics, which we call the Agile Genome. We gain insight into the dynamics of how Agile development compares to classic “waterfall” approaches by constructing a System Dynamics model for software projects. The Agile Project Dynamics (APD) model captures each of the Agile genes as a separate component of the model and allows experimentation with combinations of practices and management policies. Experimentation with the APD model is used to explore how different genes work in combination with one another to produce both positive and negative effects. The extensible design of the APD model provides the basis for further study of Agile methods and management practices

Pengaruh Jumlah Kredit dan Jumlah Simpanan terhadap Rentabilitas pada Kpri Balidita Gondol Periode 2008-2012

Penelitian ini bertujuan untuk mengetahui pengaruh jumlah pemberian kredit terhadap rentabilitas, pengaruh jumlah simpanan terhadap rentabilitas, dan pengaruh jumlah pemberian kredit dan jumlah simpanan secara simultan terhadap rentabilitas. Data dikumpulkan dengan metode dokumentasi, dan dianalisis dengan teknik kuantitatif. Hasil penelitian menunjukkan bahwa ada pengaruh positif dan signifikan antara jumlah pemberian kredit terhadap rentabilitas pada koperasi Balidita Gondol periode 2008-2012, tidak ada pengaruh antara jumlah simpanan terhadap rentabilitas pada koperasi Balidita Gondol periode 2008-2012, dan tidak adanya pengaruh antara jumlah pemberian kredit dan jumlah simpanan secara simultan terhadap rentabilitas pada koperasi Balidita Gondol periode 2008-2012.Kata Kunci : kredit, simpanan, rentabilitas This research aims to find out influence the amount of credit on profitability, influence the amount of deposits on profitability, and influence the amount of credit and total deposits simultaneously towards profitability. Data collected by documentation method, and analyzed by quantitative techniques. The results showed that there is a positive and significant effect between the amount of credit on profitability of the cooverative Balidita Gondol in 2008-2012 period, no influence on the profitability of the total deposits of the cooperative Balidita Gondol in 2008-2012 period, and not the influence of the number of credit and the amount of deposits simultaneously to profitability of the cooverative Balidita Gondol in 2008-2012 period.keyword : credit, deposits, profitabilit

DQSOps: Data Quality Scoring Operations Framework for Data-Driven Applications

Data quality assessment has become a prominent component in the successful execution of complex data-driven artificial intelligence (AI) software systems. In practice, real-world applications generate huge volumes of data at speeds. These data streams require analysis and preprocessing before being permanently stored or used in a learning task. Therefore, significant attention has been paid to the systematic management and construction of high-quality datasets. Nevertheless, managing voluminous and high-velocity data streams is usually performed manually (i.e. offline), making it an impractical strategy in production environments. To address this challenge, DataOps has emerged to achieve life-cycle automation of data processes using DevOps principles. However, determining the data quality based on a fitness scale constitutes a complex task within the framework of DataOps. This paper presents a novel Data Quality Scoring Operations (DQSOps) framework that yields a quality score for production data in DataOps workflows. The framework incorporates two scoring approaches, an ML prediction-based approach that predicts the data quality score and a standard-based approach that periodically produces the ground-truth scores based on assessing several data quality dimensions. We deploy the DQSOps framework in a real-world industrial use case. The results show that DQSOps achieves significant computational speedup rates compared to the conventional approach of data quality scoring while maintaining high prediction performance.Comment: 10 Pages The International Conference on Evaluation and Assessment in Software Engineering (EASE) conferenc