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In many scheduling studies, researchers consider the processing times of jobs as constant numbers. This assumption sometimes is at odds with practical manufacturing process due to several sources of uncertainties arising from real-life situations. Examples are the changing working environments, machine breakdowns, tool quality variations and unavailability, and so on. In light of the phenomenon of scenario-dependent processing times existing in many applications, this paper proposes to incorporate scenario-dependent processing times into a two-machine flow-shop environment with the objective of minimizing the total completion time. The problem under consideration is never explored. To solve it, we first derive a lower bound and two optimality properties to enhance the searching efficiency of a branch-and-bound method. Then, we propose 12 simple heuristics and their corresponding counterparts improved by a pairwise interchange method. Furthermore, we set proposed 12 simple heuristics as the 12 initial seeds to design 12 variants of a cloud theory-based simulated annealing (CSA) algorithm. Finally, we conduct simulations and report the performances of the proposed branch-and-bound method, the 12 heuristics, and the 12 variants of CSA algorithm. [ABSTRACT FROM AUTHOR]

The objective of this paper is to minimize both the makespan and the total completion time. Since parallel-machine scheduling which contains the function constraint problem has been a new issue, this paper explored two parallel-machine scheduling problems with function constraint, which refers to the situation that the two machines have a same function but one of the machines has another. We pointed out that the function constraint occurs not only in the manufacturing system but also in the service system. For the makespan problem, we demonstrated that it is NP-hard in the ordinary sense. In addition, we presented a polynomial time heuristic for this problem and have proved its worst-case ratio is not greater than 5/4. Furthermore, we simulated the performance of the algorithm through computational testing. The overall mean percent error of the heuristic is 0.0565%. The results revealed that the proposed algorithm is quite efficient. For the total completion time problem, we have proved that it can be solved in O n 4 time. [ABSTRACT FROM AUTHOR]

Presents information on a study which described real-time image reconstruction for spiral magnetic resonance imaging (MRI) using fixed-point calculation. Reconstruction algorithm for spiral MRI; Issues concerning fixed-point representations; Conclusions.

Among image halftoning algorithms, direct binary search (DBS) minimizes the total squared perceived error instead of using heuristic approaches. Therefore, it can generate halftone output with the best quality. The limitation of DBS is that its halftone pattern is controlled by the autocorrelation filter, which corresponds to both the human visual system and the printer model. Because of the low-pass characteristics of the filter, DBS can only generate blue-noise-like halftone pattern and the only variation is the clustered-dot algorithm proposed in 2013. We use the results of theoretical bounds to show that halftone patterns in DBS can be controlled in both frequency and spatial domains through an approach called "noise shaping." This approach is achieved through an added term to the filtered error in DBS. We also show that DBS clustered-dot halftoning is a special case of this noise-shaping approach. Experimental results show that both the spatial-domain and frequency-domain characteristics of the generated halftone pattern can be manipulated freely using this approach. [ABSTRACT FROM AUTHOR]

The question of whether there are biological differences between male and female brains is a fraught one, and political positions and prior expectations seem to have a strong influence on the interpretation of scientific data in this field. This question is relevant to issues of gender differences in the prevalence of psychiatric conditions, including autism, attention deficit hyperactivity disorder (ADHD), Tourette's syndrome, schizophrenia, dyslexia, depression, and eating disorders. Understanding how gender influences vulnerability to these conditions is significant. Diffusion magnetic resonance imaging (dMRI) provides a non-invasive method to investigate brain microstructure and the integrity of anatomical connectivity. Generalized q-sampling imaging (GQI) has been proposed to characterize complicated fiber patterns and distinguish fiber orientations, providing an opportunity for more accurate, higher-order descriptions through the water diffusion process. Therefore, we aimed to investigate differences in the brain's structural network between teenage males and females using GQI. This study included 59 (i.e., 33 males and 26 females) age- and education-matched subjects (age range: 13 to 14 years). The structural connectome was obtained by graph theoretical and network-based statistical (NBS) analyses. Our findings show that teenage male brains exhibit better intrahemispheric communication, and teenage female brains exhibit better interhemispheric communication. Our results also suggest that the network organization of teenage male brains is more local, more segregated, and more similar to small-world networks than teenage female brains. We conclude that the use of an MRI study with a GQI-based structural connectomic approach like ours presents novel insights into network-based systems of the brain and provides a new piece of the puzzle regarding gender differences.

Direct binary search (DBS) produces the images of the best quality among half-toning algorithms. The reason is that it minimizes the total squared perceived error instead of using heuristic approaches. The search for the optimal solution involves two operations: (1) toggle and (2) swap. Both operations try to find the binary states for each pixel to minimize the total squared perceived error. This error energy minimization leads to a conjecture that the absolute value of the filtered error after DBS converges is bounded by half of the peak value of the autocorrelation filter. However, a proof of the bound's existence has not yet been found. In this paper, we present a proof that shows the bound existed as conjectured under the condition that at least one swap occurs after toggle converges. The theoretical analysis also indicates that a swap with a pixel further away from the center of the autocorrelation filter results in a tighter bound. Therefore, we propose a new DBS algorithm which considers toggle and swap separately, and the swap operations are considered in the order from the edge to the center of the filter. Experimental results show that the new algorithm is more efficient than the previous algorithm and can produce half-toned images of the same quality as the previous algorithm.

Symptoms of essential tremor (ET) are similar to those of Parkinson's disease (PD) during their initial stages. Presently, there are few stable biomarkers available on a neuroanatomical level for distinguishing between these two diseases. However, few investigations have directly compared the changes in brain volume and assessed the compensatory effects of a change in the parts of the brain associated with PD and with ET. To determine the compensatory and/or degenerative anatomical changes in the brains of PD and ET patients, the present study tested, via two voxel-based morphometry (VBM) approaches (Basic vs. DARTEL VBM processing), the anatomical brain images of 10 PD and 10 ET patients, as well as of 13 age-matched normal controls, obtained through a 3T magnetic resonance scanner. These findings indicate that PD and ET caused specific patterns of brain volume alterations in the brains examined. In addition, our observations also revealed compensatory effects, or self-reorganization, occurring in the thalamus and the middle temporal gyrus in the PD and ET patients, due perhaps in part to the enhanced thalamocortical sensorimotor interaction and the head-eye position readjustment, respectively, in these PD and ET patients. Such a distinction may lend itself to use as a biomarker for differentiating between these two diseases.

Carryover effects can contaminate ON/OFF BOLD contrasts designated in an fMRI experiment. Yet, the ON/OFF contrasts are essential to facilitate statistical analysis based on the significance of contrast levels. Here, we conducted an fMRI experiment with acupuncture stimulation applied on ST42 acupoint as well as with tactile stimulation on its skin surface. Experiment consisted of three two-block acupuncture and one two-block tactile fMRI runs. Each block started with 26-sec OFF period followed by either 26-sec needle manipulation in the acupuncture runs or by scratching skin surface with sand paper in the tactile. To test if carryover effects could alter the BOLD contrasts, we analyzed different portions of fMRI data using GLM method. Our results showed analyses on different portions of acupuncture fMRI data gave significantly different results. Statistical parametric maps of group random effects resulted from the analysis on the very first fMRI trial formed the broadest coverage of the active brain areas. BOLD model time course also best explained the adjusted raw time course at peak active voxel (coefficient of determination = 0.88). Analyses on other portions of fMRI data only selected subset of the active brain areas delineated by the analysis on the very first data trial and the BOLD model only mildly accounted for the adjusted raw time courses. In tactile runs, results were more consistent across analyses. Therefore, in fMRI experiments with strong carryover effects, a single-block experimental design with multiple repetitions, separated by long enough periods of time, should be more suitable to extract task BOLD effects.