A sequential GRASP for the therapist routing and scheduling problem

This paper presents a new model and solution methodology for the problem faced by companies that provide rehabilitative services to clinic and home-bound patients. Given a set of multi-skilled therapists and a group of geographically dispersed patients, the objective is to construct weekly tours for the therapists that minimize the travel, treatment, and administrative costs while ensuring that all patients are seen within their time windows and that a host of labor laws and contractual agreements are observed. The problem is complicated by three factors that prevent a daily decomposition: (i) overtime rates kick in only after 40 regular hours are worked during the week, (ii) new patients must be seen by a licensed therapist on their first visit, and (iii) for some patients only the frequency and not the actual days on which they are to be seen is specified. The problem is formulated as a mixed-integer linear program but after repeated attempts to solve small instances with commercial software failed, we developed an adaptive sequential greedy randomized adaptive search procedure. The phase I logic of the procedure builds one daily schedule at a time for each therapist until all patients are routed. In phase II, several neighborhoods are explored to arrive at a local optimum. Extensive testing with both real data provided by a U.S. rehab company and datasets derived from them demonstrated the value of the purposed procedure with respect to current practice. The results indicated that cost reductions averaging over 18.09 % are possible.     

Linear model-based estimation of blood pressure and cardiac output for Normal and Paranoid cases

Provisioning a generic simple linear mathematical model for Paranoid and Healthy cases leading to auxiliary investigation of the neuroleptic drugs effect imposed on cardiac output (CO) and blood pressure (BP). Multi-input single output system identification in consistency with the Z-Transform is considered an essential role in the exploration of linear discrete system identification. Twenty Paranoid and 20 Healthy peer cases have been chosen to lie under study. The generated CO model forming two poles and two zeros produced a root–mean-squared error (RMSE) of 0.109 and an average RMSE of 1.39 due to Paranoid cases. On the other hand, Healthy cases obtained model held three poles and two zeros with RMSE equal to 0.17 and an average of 0.63. The BP model with four poles and two zeros showed a 2.15 and 21.69 for RMSE and an average RMSE, respectively, for Paranoid cases, whereas seven poles and two zeros provided an RMSE of 5.7 and an average RMSE of 17.19 for Healthy cases. The obtained results were provided a generic models of CO with promising outcomes for Paranoid and Healthy cases. Moreover, the BP model has less and yet acceptable results in both Paranoid and Healthy cases.     

Comparison of the Magnetic Ordering in Sr2Yb1Ru0.9Cu0.1O6 and Ru1Sr2Gd1Cu2O8 Superconductors

Ru₁Sr₂Gd₁Cu₂O₈ and Sr₂Yb₁Ru_0.9Cu_0.1O₆ were synthesized using a solid-state reaction. X-ray diffraction showed that Ru₁Sr₂Gd₁Cu₂O₈ crystallized into the tetragonal Ru-1212 structure (space group P4/mmm), whereas the Sr₂Yb₁Ru_0.9Cu_0.1O₆ had a monoclynic structure (space group P2₁/n). Sr₂Yb₁Ru_0.9Cu_0.1O₆ showed a possible magnetic transition ( T _{m a g} ) at 44 K with a superconducting transition temperature T _c at 30 K. In contrast, Ru₁Sr₂Gd₁Cu₂O₈ showed a magnetic transition at 140 K with a T _c at 25 K. The magnetization data for Sr₂Yb₁Ru_0.9Cu_0.1O₆ suggests that this sample exhibits antiferromagnetic ordering in zero-field-cooled (ZFC) magnetization, whereas it reveals a weak ferromagnetic component during field-cooled (FC) cycles. In addition, larger diamagnetic signals were observed during FC cycle compared to the ZFC. These results suggest that the valence state of the Yb ion have a significant effect on the magnetic state of the Sr₂Yb₁Ru_0.9Cu_0.1O₆ superconductor.     

A Puzzle of Quantum Phase Transition on Gd-IMC by Tuning of Conduction Electron Concentration

Based on the critical unstable of both crystal and magnetic structure of Gd-intermetallic compound near the competition of two strongly independent subsystem （＂local 4f7＂ and ＂conduction electron concentration＂）, a new QPT （quantum point transition） is predicted by calculation of： （1） The band structure and density of state by density functional theory where a strong narrowing fluidity of fermions around EF with shifted to negative value ＂-0.8 eV ＂is observable in the Gd-intermetalliccompound system while in the Y-case, it is not dominated. An antiferromagnetic state on the fluidity of conduction band can be investigated; （2） The internal magnetic field due to short range exchange interaction Jij between the nearest neighbor of local magnetic moment of stable s-state of Gd （L = 0） through the mean field approximation and of Eigenvalue-Eigenfunction ~.（k） are calculated. While a strong negative value of Jy is predicted, the eigenvalue L（k） of the system shows a strong antiferromagnetic phase in the reciprocal lattice direction 〈010〉, 〈001〉 in the correlation length 3.38 ~A. Although the antiferromagnetic state at Rc 〈_ 3.38 °A is a puzzle but it is completely dominated at Rc = 9 °A after passing through the competition between ）.λmin（O） and λmin（π） in the ranger of 3.2 °A 〈 Rc 〈 9 °A. Since both of the antiferromagnetic subsystems are sensitive to the predicted KF, the effect of decreasing of conduction electron is proposed to investigate, the change of the antiferromagnetic ordering state to the competition of ferromagnetic state （in direction 〈010〉） and antiferromagnetic state （in direction 〈001 〉 and 〈 100〉） resulted to paramagnetic state in the long range Rc = 9 °A.     

A Zero-Pole Reposition Based, 0.95-mW, 68-dB,Linear-in-dB,Constant-Bandwidth Variable Gain Amplifier

A variable-gain amplifier with very low power consumption and wide tuning range is presented. The operational principle of this unique structure is discussed, its most important formulas are derived and its outstanding performance is verified by simulation in TSMC 0.18-μm N-well CMOS fabrication process. Owing to the novel zero-pole repositioning technique, the proposed circuit demonstrates very high frequency bandwidth of 79 MHz while drawing only 0.52 mA from 1.8 V power supply. The interesting results such as a very small core area of about 0.0025 mm² as well as a wide linear-in-dB and constant-bandwidth tuning range of 68.2 dB along with a very low power consumption of 0.95 mW are achieved utilizing standard CMOS technology. The stability of the proposed VGA is verified through transient sinusoidal response analysis. Full process, voltage and temperature (PVT) variation analysis of the circuit is also investigated through Monte Carlo and corner case analysis in order to approve the robustness of the structure. Monte Carlo simulations show standard deviation values of 4.6 dB and 78.3 MHz in gain and gain-bandwidth product, respectively. These results show that our zero-pole repositioning method would lend itself well for use in low-power and high-frequency applications, especially in high-speed automatic gain control amplifiers.     

Best Minimum Summation Scheduler for Long Term Evolution

Resource scheduling in Long Term Evolution (LTE) is an open and rising issue. It has an enormous impact on the entire system performance. Due to the nature of LTE system, the scheduler has to be designed carefully. It has to overcome many challenges such as limited processing time and the high dynamic behavior. This paper proposes a novel scheduling policy for the MAC layer in LTE called the Best Minimum Summation (BMS). The main aim of this scheduling policy is to achieve high performance with low complexity. Three sub-schedulers have been developed. Each one of these schedulers deals with scheduling table in different dimension. The first one operates on the scheduling table through the user dimension (BMS.UE); while the second one operates on the scheduling table through the resource block dimension (BMS.RB). The third scheduler operates on the scheduling table correlating both of these dimensions (BMS.2D). All of the proposed solutions were intensively evaluated in a system level simulator. Three performance metrics were used which are throughput, error rate and fairness. The results have shown that the ability of the BMS.UE scheduler to outperform other existing schedulers of LTE.     

Augmented grasshopper optimization algorithm by differential evolution: a power scheduling application in smart homes

With the increasing number of electricity consumers, production, distribution, and consumption problems of produced energy have appeared. This paper proposed an optimization method to reduce the peak demand using smart grid capabilities. In the proposed method, a hybrid Grasshopper Optimization Algorithm (GOA) with the self-adaptive Differential Evolution (DE) is used, called HGOA. The proposed method takes advantage of the global and local search strategies from Differential Evolution and Grasshopper Optimization Algorithm. Experimental results are applied in two scenarios; the first scenario has universal inputs and several appliances. The second scenario has an expanded number of appliances. The results showed that the proposed method (HGOA) got better power scheduling arrangements and better performance than other comparative algorithms using the classical benchmark functions. Moreover, according to the computational time, it runs in constant execution time as the population is increased. The proposed method got 0.26?% enhancement compared to the other methods. Finally, we found that the proposed HGOA always got better results than the original method in the worst cases and the best cases.

     

A new dynamic cellular learning automata-based skin detector

Skin detection is a difficult and primary task in many image processing applications. Because of the diversity of various image processing tasks, there exists no optimum method that can perform properly for all applications. In this paper, we have proposed a novel skin detection algorithm that combines color and texture information of skin with cellular learning automata to detect skin-like regions in color images. Skin color regions are first detected, by using a committee structure, from among several explicit boundary skin models. Detected skin-color regions are then fed to a texture analyzer which extracts texture features via their color statistical properties and maps them to a skin probability map. This map is then used by cellular learning automata to adaptively make a decision on skin regions. Conducted experiments show that the proposed algorithm achieves the true positive rate of about 86.3% and the false positive rate of about 9.2% on Compaq skin database which shows its efficiency.     

Reconfigurable hardware implementation of a phase-correlation stereoalgorithm

This paper describes the implementation of a stereo-vision system using Field Programmable Gate Arrays (FPGAs). Reconfigurable hardware, including FPGAs, is an attractive platform for implementing vision algorithms due to its ability to exploit parallelism often found in these algorithms, and due to the speed with which applications can be developed as compared to hardware. The system outputs 8-bit, subpixel disparity estimates for 256× 360 pixel images at 30,fps. A local-weighted phase correlation algorithm for stereo disparity [Fleet, D. J.: {Int. Conf. Syst. Man Cybernetics 1:48–54 (1994)] is implemented. Despite the complexity of performing correlations on multiscale, multiorientation phase data, the system runs as much as 300 times faster in hardware than its software implementation. This paper describes the hardware platform used, the algorithm, and the issues encountered during its hardware implementation. Of particular interest is the implementation of multiscale, steerable filters, which are widely used in computer vision algorithms. Several trade-offs (reducing the number of filter orientations from three to two, using fixed-point computation, changing the location of one localized low-pass filter, and using L1 instead of L2 norms) were required to both fit the design into the available hardware and to achieve video-rate processing. Finally, results from the system are given both for synthetic data sets as well as several standard stereo-pair test images.     

Microstructure and High Temperature Impression Creep Properties of Mg–3Ca–xZr (x = 0.3, 0.6, 0.9 wt%) Alloys

The current study has investigated the influence of zirconium (Zr) addition to Mg–3Ca–xZr (x = 0.3, 0.6, 0.9 wt%) alloys prepared using argon arc melting on the microstructure and impression properties at 448–498 K under constant stress of 380 MPa. Microstructural analysis of as-cast Mg–3Ca–xZr alloys showed grain refinement with Zr addition. The observed grain refinement was attributed to the growth restriction effect of Zr in hypoperitectic Mg–3Ca–0.3 wt% Zr alloys. Heterogeneous nucleation of α-Mg in properitectic Zr during solidification resulted in grain refinement of hyperperitectic Mg–3Ca–0.6 wt% Zr and Mg–3Ca–0.9 wt% Zr alloys. The hardness of Mg–3Ca–xZr alloys increased as the amount of Zr increased due to grain refinement and solid solution strengthening of α-Mg by Zr. Creep resistance of Mg–3Ca–xZr alloys increased with the addition of Zr due to solid solution strengthening of α-Mg by Zr. The calculated activation energy (Q_a) for Mg–3Ca samples (131.49 kJ/mol) was the highest among all alloy compositions. The Q_a values for 0.3, 0.6 and 0.9 wt% Zr containing Mg–3Ca alloys were 107.22, 118.18 and 115.24 kJ/mol, respectively.