Discovering Regression Rules with Ant Colony Optimization

The majority of Ant Colony Optimization (ACO) algorithms for data mining have dealt with classification or clustering problems. Regression remains an unexplored research area to the best of our knowledge. This paper proposes a new ACO algorithm that generates regression rules for data mining applications. The new algorithm combines components from an existing deterministic (greedy) separate and conquer algorithm—employing the same quality metrics and continuous attribute processing techniques—allowing a comparison of the two. The new algorithm has been shown to decrease the relative root mean square error when compared to the greedy algorithm. Additionally a different approach to handling continuous attributes was investigated showing further improvements were possible

Exact results for the Kardar--Parisi--Zhang equation with spatially correlated noise

We investigate the Kardar--Parisi--Zhang (KPZ) equation in $d$ spatial dimensions with Gaussian spatially long--range correlated noise --- characterized by its second moment $R(\vec{x}-\vec{x}') \propto |\vec{x}-\vec{x}'|^{2\rho-d}$ --- by means of dynamic field theory and the renormalization group. Using a stochastic Cole--Hopf transformation we derive {\em exact} exponents and scaling functions for the roughening transition and the smooth phase above the lower critical dimension $d_c = 2 (1+\rho)$. Below the lower critical dimension, there is a line $\rho_*(d)$ marking the stability boundary between the short-range and long-range noise fixed points. For $\rho \geq \rho_*(d)$, the general structure of the renormalization-group equations fixes the values of the dynamic and roughness exponents exactly, whereas above $\rho_*(d)$, one has to rely on some perturbational techniques. We discuss the location of this stability boundary $\rho_* (d)$ in light of the exact results derived in this paper, and from results known in the literature. In particular, we conjecture that there might be two qualitatively different strong-coupling phases above and below the lower critical dimension, respectively.Comment: 21 pages, 15 figure

Scaling regimes and critical dimensions in the Kardar-Parisi-Zhang problem

We study the scaling regimes for the Kardar-Parisi-Zhang equation with noise correlator R(q) ~ (1 + w q^{-2 \rho}) in Fourier space, as a function of \rho and the spatial dimension d. By means of a stochastic Cole-Hopf transformation, the critical and correction-to-scaling exponents at the roughening transition are determined to all orders in a (d - d_c) expansion. We also argue that there is a intriguing possibility that the rough phases above and below the lower critical dimension d_c = 2 (1 + \rho) are genuinely different which could lead to a re-interpretation of results in the literature.Comment: Latex, 7 pages, eps files for two figures as well as Europhys. Lett. style files included; slightly expanded reincarnatio

Consumer Willingness-To-Pay for Different Organic Certification Logos in Turkey

Using data from focus group discussions with consumers and a choice experimentconducted in some of Turkey’s major cities, this study investigates whetherTurkish consumers prefer certain organic labelling schemes over others attemptsand to elicit their willingness to pay (WTP) for different organic certificationlogos. Although the level of awareness regarding organic certification logos waslow, consumers’ perceptions of the logos were generally positive. The results ofthe random parameter logit models indicated a positive WTP for the presence ofone of the three tested certification body logos in addition to the mandatorygovernmental logo. Given the low level of certification logo awareness, theconclusion is that both purchasing decisions and perceptions regarding logoswere affected by subjective criteria. Both the government and certification bodiesshould develop measures to increase consumer awareness of their logos and formconsumer perceptions and attitudes regarding the quality of the certificationimplied by the logo

Factors influencing the perception of organic certification logos in Turkey

Consumers’ perceptions on organic certification logos and the factors influencing these perceptions were explored. Data from surveys conducted in major cities of Turkey revealed that organic food consumers had little knowledge about logos, although the declared level of trust in organic logos was high. According to ordered logit models, consumer’s perceptions on organic certification logos were influenced by purchasing frequency and weight of organic foods in total food consumption. Dummy variables representing additional private certification company logos as well were generally found to have a significant effect on logo perception. This result suggests that consumers’ attitudes towards these logos and towards the governmental logo are not the same. Female and older people were more sceptical about the trustworthiness of the logos. While the credibility of the logos and the standards and control systems underlying the logos increased as frequency of purchasing organic food increased, those consumers who prefer organic open markets for buying organic food were hesitant to trust the credibility of the organic certification logos. The mandatory governmental logo and the underlying standards are trusted more than the private company logos. However, the difference of the attitudes toward logos decreases when the control system is in question. When a comparison between perceptions towards labels including different additional certification companies’ logos is made, the additional logo was found to affect the stated preferences more negatively when the companies were foreign. Enhanced interest and trust in the organic certification logos among consumers would foment the development of the organic sector, and the findings of this paper serve as an input for the achievement of this aim

Microscopic Non-Universality versus Macroscopic Universality in Algorithms for Critical Dynamics

We study relaxation processes in spin systems near criticality after a quench from a high-temperature initial state. Special attention is paid to the stage where universal behavior, with increasing order parameter emerges from an early non-universal period. We compare various algorithms, lattice types, and updating schemes and find in each case the same universal behavior at macroscopic times, despite of surprising differences during the early non-universal stages.Comment: 9 pages, 3 figures, RevTeX, submitted to Phys. Rev. Let

The impact of whole-body hyperthermia interventions on mood and depression - are we ready for recommendations for clinical application?

Objective: To systematically summarize the findings from research studies examining the effects of whole-body hyperthermia (WBH) interventions on mood and symptoms of depression. Methods: Systematic literature search of online and offline databases (e.g., Pubmed, Web of Knowledge, Cochrane, academic libraries). Risk of bias assessment and secondary analysis of effect sizes. Study selection: Clinical studies with a pre/post-intervention design and outcome measures for mood and depression as accepted in the S-3 guidelines (Association of Scientific Medical Societies in Germany). Data extraction: Study characteristics and outcomes (means and standard deviations) from participants receiving at least one WBH intervention. Results: A total of 7 studies and 148 subjects with a mean age of 46 years (36-56 years) were identified. Three out of seven studies utilized hot baths and 4/7 infrared heating. Study duration ranged from 1 to 6 weeks with one or multiple interventions and an average treatment time of 66.37 min (42.55-140). Risk of bias analysis revealed small sample biases and lack of control groups in 3/7 studies. About 21 study end-points were extracted with 19 resulting in effects sizes (Cohen's d) of 0.8 or greater. Target temperatures between 38 °C and 39 °C and slower increase in core body temperature during the intervention resulted in larger treatment effects. Conclusion: WBH is a promising alternative treatment for depression with low risk for adverse reactions and side effects but still lacking sufficient evidence for general recommendations for clinical practice. However, as all other interventions have failed, the studies to date can provide a framework for clinical application.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Dynamical Relaxation and Universal Short-Time Behavior in Finite Systems: The Renormalization Group Approach

We study how the finite-sized n-component model A with periodic boundary conditions relaxes near its bulk critical point from an initial nonequilibrium state with short-range correlations. Particular attention is paid to the universal long-time traces that the initial condition leaves. An approach based on renormalization-group improved perturbation theory in 4-epsilon space dimensions and a nonperturbative treatment of the q=0 mode of the fluctuating order-parameter field is developed. This leads to a renormalized effective stochastic equation for this mode in the background of the other q=0 modes; we explicitly derive it to one-loop order, show that it takes the expected finite-size scaling form at the fixed point, and solve it numerically. Our results confirm for general n that the amplitude of the magnetization density m(t) in the linear relaxation-time regime depends on the initial magnetization in the universal fashion originally found in our large-$n$ analysis [J.\ Stat. Phys. 73 (1993) 1]. The anomalous short-time power-law increase of m(t) also is recovered. For n=1, our results are in fair agreement with recent Monte Carlo simulations by Li, Ritschel, and Zheng [J. Phys. A 27 (1994) L837] for the three-dimensional Ising model.Comment: 27 pages, 7 postscript figures, REVTEX 3.0, submitted to Nucl. Phys.

Using an Ant Colony Optimization Algorithm for Monotonic Regression Rule Discovery

Many data mining algorithms do not make use of existing domain knowledge when constructing their models. This can lead to model rejection as users may not trust models that behave contrary to their expectations. Semantic constraints provide a way to encapsulate this knowledge which can then be used to guide the construction of models. One of the most studied semantic constraints in the literature is monotonicity, however current monotonically-aware algorithms have focused on ordinal classification problems. This paper proposes an extension to an ACO-based regression algorithm in order to extract a list of monotonic regression rules. We compared the proposed algorithm against a greedy regression rule induction algorithm that preserves monotonic constraints and the well-known M5’ Rules. Our experiments using eight publicly available data sets show that the proposed algorithm successfully creates monotonic rules while maintaining predictive accuracy

Monte Carlo Simulation of the Short-time Behaviour of the Dynamic XY Model

Dynamic relaxation of the XY model quenched from a high temperature state to the critical temperature or below is investigated with Monte Carlo methods. When a non-zero initial magnetization is given, in the short-time regime of the dynamic evolution the critical initial increase of the magnetization is observed. The dynamic exponent $\theta$ is directly determined. The results show that the exponent $\theta$ varies with respect to the temperature. Furthermore, it is demonstrated that this initial increase of the magnetization is universal, i.e. independent of the microscopic details of the initial configurations and the algorithms.Comment: 14 pages with 5 figures in postscrip