Superconductivity in Lithium- and Sodium-Doped Mercury-Based Cuprates

The effect of Na- and Li-doping in Hg-based cuprates has been studied. It has been found that superconductivity can be achieved in samples containing small amount of Na or Li. While little change is found in the crystalline structure, the formed superconducting phase have the onset T_c typically above 140 K and zero-resistance T_c up to 136K. More interestingly, the processing temperature for the doped Hg-1223 can be reduced significantly to near 700 °C which is promising for thin films growth on many technologically compatible substrates.     

Use of genetic algorithms to solve production and operations management problems: A review

Operations managers and scholars in their search for fast and good solutions to real-world problems have applied genetic algorithms to many problems. While genetic algorithms are promising tools for problem solving, future research will benefit from a review of the problems that have been solved and the designs of the genetic algorithms used to solve them. This paper provides a review of the use of genetic algorithms to solve operations problems. Reviewed papers are classified according to the problems they solve. The basic design of each genetic algorithm is described, the shortcomings of the current research are discussed and directions for future research are suggested.     

Deposition and Characterization of Si Substituted Cu2ZnSnS4 Thin Films

Silicon - The influence of the Si substitution ratio on the structural, morphological, and optical properties of Cu2ZnSnS4 (CZTS) thin films was examined. The Cu2Zn(SixSn1–x)S4 thin films...     

A new approach for the computation of design shear force in reinforced concrete walls subjected to seismic loads

This paper investigates the dynamic shear amplification in reinforced concrete shear walls designed according to the seismic provisions of the current Turkish Building Earthquake Code (TBEC-2018). Shear walls with a high ductility level and different aspect ratios are examined to evaluate the design shear force calculated by using the dynamic amplification factor (β_v) and overstrength factor (D) defined in TBEC-2018. For this purpose, response spectrum analyses (RSAs) are first carried out on two-dimensional cantilever shear walls with heights of 30, 45, and 60 m and with lengths of 1.5, 3, and 4.5 m in the plan. Then, a total of 198 nonlinear time history analyses (NLTHAs) are performed with real and simulated ground motions matched to the elastic design spectrum defined in TBEC-2018. The comparison of the design shear forces obtained from RSA and the shear demands obtained from NLTHA along the heights of the walls reveals that the design shear forces calculated according to TBEC-2018 may underestimate the actual shear demands from studied ground motions. Moreover, the applicability of the updates proposed to TBEC-2018 for the design shear force and shear force diagram along the wall height in reinforced concrete shear wall-frame systems to cantilever shear walls is also examined.     

Measures of subproblem criticality in decomposition algorithms for shop scheduling

Work centre-based decomposition approaches, especially variants of the Shifting Bottleneck algorithm, have been very successful in solving job-shop-scheduling problems. These methods decompose the problem into subproblems involving a single work centre (usually a single machine), which they solve sequentially. We propose new measures of subproblem criticality and show via computational experiments that several of these provide solutions comparable in quality with those obtained from previous work in substantially less central processing unit time.     

Discovering subproblem prioritization rules for shifting bottleneck algorithms

Shifting bottleneck (SB) algorithms have been successful in solving most real-sized scheduling problems. However, it is known that under certain conditions, solution quality degrades because of subproblem interactions. Changing the order in which subproblems are solved greatly affects the solution quality. We demonstrate that for some class of problems it is possible to induce production (IF–THEN) rules that determine the subproblem solution order and lead to good quality solutions, matching the performance of the SB algorithm in most other instances.     

All-aerosol-jet-printed highly sensitive and selective polyaniline-based ammonia sensors: a route toward low-cost,low-power gas detection

Journal of Materials Science - We report the design and scalable fabrication of a low-cost and low-power polyaniline-based (PANI) ammonia (NH3) gas sensor on polyimide (PI) substrates using...     

Systems for strategic learning

An important decision support system component is machine learning/data mining. Classical machine learning methods implicitly assume that attributes of instances under classification do not change to acquire a positive classification. However, in many situations these instances represent people or organizations that can proactively seek to alter their characteristics to gain a positive classification. We argue that the learning mechanism should take this possible strategic learning into consideration during the induction process. We call this strategic learning. In this paper we define this concept, summarize related research, and present a number of future research areas. This article is part of the “Handbook on Decision Support Systems” edited by Frada Burstein and Clyde W. Holsapple (2008) Springer.     

A review of machine learning in scheduling

This paper has two primary purposes: to motivate the need for machine learning in scheduling systems and to survey work on machine learning in scheduling. In order to motivate the need for machine learning in scheduling, we briefly motivate the need for systems employing artificial intelligence methods for scheduling. This leads to a need for incorporating adaptive methods-learning