A MIP based heuristic for capacitated MRP systems

Although Material Requirements Planning (MRP) is the most widely used production planning tool in today’s manufacturing companies, its inability to perform an exhaustive capacity planning, lack of a comprehensive and integrated shop floor extension and using constant and inflated lead times necessitate intelligent methods for developing cost effective production plans. A single optimization model might be employed to overcome these limitations, but it would be intractable to use it in large manufacturing systems. Hence, in this paper, we propose a heuristic method called Capacity Allocater and Scheduler, CAS, to eliminate drawbacks of MRP systems and provide solutions for large-scale instances. The CAS procedure, based on iteratively solving relaxed Mixed Integer Programming (MIP) models, is built on a lot sizing and scheduling framework, which considers both supply alternatives and lot size restrictions simultaneously. Finally, we give a detailed numerical example to demonstrate how CAS may be used in practice, and provide our concluding remarks.     

Development of an Expert System for Selection of Dam Type on Alluvium Foundations

. A knowledge-based expert system was developed to aid in the selection of the type of dam. The dam type selector expert system (DTSA ES) was designed to determine the type of dam on the alluvium foundations. Detailed expert knowledge is required to estimate the type of dam and to develop an expert system. The DTSA ES utilizes rules of thumb used by an expert for determining the selection of the type of dam. The DTSA ES was developed using a shell program. The expert system was tested on several dam sites in order to validate the decision obtained. The use of this expert system, containing knowledge about the selection of dam type, can be helpful to students, potential owners or contractors in selecting dam types. The current prototype always needs additional parameters for more detailed analyses of new developments. However, the current DTSA ES is designed to include existing information about dam types.     

A new approach based on a discrete hidden Markov model using the Rocchio algorithm for the diagnosis of heart valve diseases

Abstract: Application of the Doppler ultrasound technique in the diagnosis of heart diseases has been increasing in the last decade since it is non‐invasive, practicable and reliable. In this study, a new approach based on the discrete hidden Markov model (DHMM) is proposed for the diagnosis of heart valve disorders. For the calculation of hidden Markov model (HMM) parameters according to the maximum likelihood approach, HMM parameters belonging to each class are calculated by using training samples that only belong to their own classes. In order to calculate the parameters of DHMMs, not only training samples of the related class but also training samples of other classes are included in the calculation. Therefore HMM parameters that reflect a class's characteristics are more represented than other class parameters. For this aim, the approach was to use a hybrid method by adapting the Rocchio algorithm. The proposed system was used in the classification of the Doppler signals obtained from aortic and mitral heart valves of 215 subjects. The performance of this classification approach was compared with the classification performances in previous studies which used the same data set and the efficiency of the new approach was tested. The total classification accuracy of the proposed approach (95.12%) is higher than the total accuracy rate of standard DHMM (94.31%), continuous HMM (93.5%) and support vector machine (92.67%) classifiers employed in our previous studies and comparable with the performance levels of classifications using artificial neural networks (95.12%) and fuzzy‐C‐means/CHMM (95.12%).     

Medical application of information gain based artificial immune recognition system (AIRS): Diagnosis of thyroid disease

In this paper, we have made medical application of a new artificial immune system named the information gain based artificial immune recognition system (IG-AIRS) which minimizes the negative effects of taking into account all attributes in calculating Euclidean distance in shape–space representation which is used in many artificial immune systems. For medical data, thyroid disease data set was applied in the performance analysis of our proposed system. Our proposed system reached 95.90% classification accuracy with 10-fold CV method. This result ensured that IG-AIRS would be helpful in diagnosing thyroid function based on laboratory tests, and would open the way to various ill diagnoses support by using the recent clinical examination data, and we are actually in progress.     

Effects of growth rate and temperature gradient on the microstructure parameters in the directionally solidified succinonitrile–7.5 wt.% carbon tetrabromide alloy

Succinonitrile (SCN)–7.5 wt.% carbon tetrabromide (CTB) alloy was unidirectionally solidified with a constant growth rate (V = 33 μm/s) at five different temperature gradients (G = 4.1–7.6 K/mm) and with a constant temperature gradient (G = 7.6 K/mm) at five different growth rates (V = 7.2–116.7 μm/s). The primary dendrite arm spacings, secondary dendrite arm spacings, dendrite tip radius and mushy zone depths were measured. Theoretical models for the microstructure parameters have been compared with the experimental observations, and a comparison of our results with the current theoretical models and previous experimental results have also been made.     

Equalization for discrete multitone transceivers to maximize bitrate

In a discrete multitone receiver, a time-domain equalizer (TEQ) reduces the intersymbol interference (ISI) by shortening the effective duration of the channel impulse response. Current TEQ design methods such as the minimum mean-squared error (MMSE), maximum shortening SNR (MSSNR), and maximum geometric SNR (MGSNR) do not directly maximize bit rate. We develop two TEQ design methods to maximize the bit rate. First, we partition an equalized multicarrier channel into its equivalent signal, noise, and ISI paths to develop a new subchannel SNR definition. Then, we derive a nonlinear function of TEQ taps that measures the bit rate, which the proposed maximum bit rate (MBR) method optimizes. We also propose a minimum-ISI method that generalizes the MSSNR method by weighting the ISI in the frequency domain to obtain higher performance. The minimum-ISI method is amenable to real-time implementation on a fixed-point digital signal processor. Based on simulations using eight different carrier-serving-area loop channels, (1) the proposed methods yield higher bit rates than MMSE, MGSNR, and MSSNR methods; (2) the proposed methods give three-tap TEQs with higher bit rates than 17-tap MMSE, MGSNR, and MSSNR TEQs; (3) the proposed MBR method achieves the channel capacity (as computed by the matched filter bound using the proposed subchannel SNR model) with a five-tap TEQ; and (4) the proposed minimum-ISI method achieves the bit rate of the optimal MBR method     

A bis-selenophene substituted alkoxy benzene derivative as a highly stable novel electrochromic polymer

Up to date there are few studies reporting the use of selenophene derivatives as electrochromic polymers. This report highlights the synthesis of a selenophene containing multi-ring aromatic polymer which possesses reasonable optical contrasts at both visible and near-IR regions. Electrochemical synthesis of a conducting polymer from a multi-ring aromatic monomer, 2-(2,5-bis(hexyloxy)-4-(selenophen-2-yl)phenyl)selenophene (BSB(OC₆H₁₃)₂), was achieved at a lower potential than its corresponding parent, selenophene. The strong absorption band for the undoped polymer was 474 nm and the onset energy for the π–π^* transition (Eg) was 1.9 eV (645 nm).A novel dual-polymer electrochromic device was constructed in sandwich configuration where poly(BSB(OC₆H₁₃)₂) was used as the anodically coloring material. It is the first electrochromic device where a selenophene-containing polymer was used as an active layer. The device switches between a rose-colored state and a blue-colored state with a fast response time (less than 1 s).     

Natural fibers and zinc hydroxystannate 3D microspheres based composite paper sheets for modern bendable energy storage application

For modern high-tech flexible energy storage devices, it becomes important to synthesize micro-/nanostructures as per the required shape and morphology with superior physical and electro-active characteristics. This work shares the fabrication and characterization of ZnSn(OH)₆ (Zinc hydroxystannate [ZHS]) prepared by facile microwave-assisted technique and furthermore converted into flexible sheets by employing lignocelluloses (LC) known as natural fibers, collected from Carica papaya leaf petiole as a substrate to provide the flexible matrix. X-ray diffraction measurements confirm the successful crystalline structure of ZHS. Scanning electron microscopy and transmission electron microscopy showed the solid spherical structure of ZHS microspheres. Fourier transform infrared spectrometry and Raman spectroscopy confirmed the composite formation of ZHS and LC-based composite sheets (ZHS/LC sheets). Electrochemical measurements that is, cyclic voltammetry (CV), Galvanostatic charge/discharge, and electrochemical impedance (EIS) spectroscopy revealed the electroactive behavior of ZHS/LC paper sheets as working electrode for energy storage applications. CV measurements revealed the specific capacitance of 100 F/g and EIS measurements confirmed the decrease in the resistance of LC fiber after the growth of ZHS microspheres. Presented flexible ZHS based paper sheets will be highly feasible for the modern bendable/flexible/disposable energy storage applications.     

Nanoconfinement of spider silk fibrils begets superior strength, extensibility, and toughness

Silk is an exceptionally strong, extensible, and tough material made from simple protein building blocks. The molecular structure of dragline spider silk repeat units consists of semiamorphous and nanocrystalline β-sheet protein domains. Here we show by a series of computational experiments how the nanoscale properties of silk repeat units are scaled up to create macroscopic silk fibers with outstanding mechanical properties despite the presence of cavities, tears, and cracks. We demonstrate that the geometric confinement of silk fibrils to diameters of 50 ± 30 nm is critical to facilitate a powerful mechanism by which hundreds of thousands of protein domains synergistically resist deformation and failure to provide enhanced strength, extensibility, and toughness at the macroscale, closely matching experimentally measured mechanical properties. Through this mechanism silk fibers exploit the full potential of the nanoscale building blocks, regardless of the details of microscopic loading conditions and despite the presence of large defects. Experimental results confirm that silk fibers are composed of silk fibril bundles with diameters in the range of 20-150 nm, in agreement with our predicted length scale. Our study reveals a general mechanism to map nanoscale properties to the macroscale and provides a potent design strategy toward novel fiber and bulk nanomaterials through hierarchical structures.