Analyzing IT maintenance outsourcing decision from a knowledge management perspective

IT outsourcing is a complex and opaque decision problem. Managers facing a decision about IT outsourcing have difficulty in framing what needs to be thought about further in their discourses. Framing is one of the most crucial steps of human decision making and needs to be assisted to better understand a decision situation. In this research, we examine a number of decision primitives in the context of an IT outsourcing decision situation. We demonstrate how the decision primitives can be employed so that managers can probe deep to better understand a decision situation and to establish a decision basis. In the organizational setting, we exemplify the use of the decision primitives in relation to the perceived outsourcing implications for the managers looking for assistance in accommodating a knowledge management perspective on IT outsourcing. Consequently, we induce insight and a guideline on how to use knowledge management for effective outsourcing in one of the leading financial institutes in Europe.

Coordinating metaheuristic agents with swarm intelligence

Coordination of multi agent systems remains as a problem since there is no prominent method suggests any universal solution. Metaheuristic agents are specific implementations of multi-agent systems, which imposes working together to solve optimisation problems using metaheuristic algorithms. An idea for coordinating metaheuristic agents borrowed from swarm intelligence is introduced in this paper. This swarm intelligence-based coordination framework has been implemented as swarms of simulated annealing agents collaborated with particle swarm optimization for multidimensional knapsack problem. A comparative performance analysis is also reported highlighting that the implementation has produced much better results than the previous works.     

The hydro-abrasive erosion wear behavior of duplex-treated surfaces of AISI H13 tool steel

The influence of duplex surface treatments consisting of a DC-pulsed plasma nitriding process and subsequent coatings of CrN and TiAlN deposited by physical vapor deposition(PVD)on AISI H13 tool steel was studied in this article.The treated samples were characterized using metallographic techniques,SEM,EDS,and microhardness methods.Hydro-abrasive erosion wear tests were performed in a specifically designed wear tester in which the samples were rotated in a wear tank containing a mixture of distilled water and ceramic abrasive chips with a fixed rotational speed.The wear rates caused by the abrasive particle impacts were assessed based on accumulated weight loss measurements.The worn surfaces were also characterized using optical microscopy,SEM,and EDS.Microhardness measurements indicated a significant increase in the surface hardness of the duplex-treated samples.The surfaces of the samples with the TiAlN coating were approximately 15 times harder than that of the untreated samples and 3 times that of the plasma nitrided samples.Hydro-abrasive erosion wear results showed that the duplex surface treatments,especially the CrN coating,displayed the highest erosion wear resistance.     

Electrophoretic deposition of nano-sized BaTiO3

In this study, a non-aqueous method in a simple one pot reaction process was employed to synthesize nano-sized BaTiO₃ particles and then electrophoretic deposition technique was employed for thin film coatings. In the first step of the preparation, metallic barium is directly dissolved in benzyl alcohol at slightly elevated temperatures. Then titanium isopropoxide was added following by a solvothermal treatment. At the end of the reaction, nearly spherical BaTiO₃ nanoparticles were obtained typically 5 nm in diameter. After establishing the stability of the BaTiO₃ suspension in ethanol, electrophoretic deposition process was performed without any additional operation. Alumina with platinum plating was used as substrate. To achieve the optimal process parameters, various voltages were applied by altering the cathode to anode distance as well as deposition time. High voltages application was possible without causing hydrolysis, because of the non-aqueous ethanol medium with higher surface charge of the nanoparticles. The deposited surface coatings were dried in air and sintered at various temperatures. SEM, EDX and XRD analysis were employed for the investigation of the coating.     

A simulated annealing algorithm for multi-agent systems: a job-shop scheduling application

In this paper, a parallel implementation of the modular simulated annealing algorithm for classical job-shop scheduling is presented. The implementation is for a multi agent system running on the distributed resource machine, which is a novel, scalable, distributed virtual machine based on Java technology. The problems tackled are well known, difficult benchmarks, widely used to measure the efficiency of metaheuristics with respect to both the quality of the solutions and the central processing unit time. The empirical results obtained show that the method proposed is successful in comparison with a sequential version of modular simulated annealing algorithm and other methods described in the literature.     

Adaptive Q control for tapping-mode nanoscanning using a piezoactuated bimorph probe

A new approach, called adaptive Q control, for tapping-mode atomic force microscopy (AFM) is introduced and implemented on a homemade AFM setup utilizing a laser Doppler vibrometer and a piezoactuated bimorph probe. In standard Q control, the effective Q factor of the scanning probe is adjusted prior to the scanning depending on the application. However, there is a trade-off in setting the effective Q factor of an AFM probe. The Q factor is either increased to reduce the tapping forces or decreased to increase the maximum achievable scan speed. Realizing these two benefits simultaneously using standard Q control is not possible. In adaptive Q control, the Q factor of the probe is set to an initial value as in standard Q control, but then modified on the fly during scanning when necessary to achieve this goal. In this article, we present the basic theory behind adaptive Q control, the electronics enabling the online modification of the probe's effective Q factor, and the results of the experiments comparing three different methods: scanning (a) without Q control, (b) with standard Q control, and (c) with adaptive Q control. The results show that the performance of adaptive Q control is superior to the other two methods.     

Sources and mitigation of methane emissions by sectors: A critical review

The environmental community rightly recognizes global warming as one of the gravest threats to the planet. Methane (CH₄), one of the greenhouse gases causing global warming, is emitted from a variety of sources and its concentration in atmosphere has increased dramatically over the last few centuries. Therefore, the increasing concentrations of methane are of special concern because of its effects on climate and atmospheric chemistry. Anthropogenic sources of methane can be collected under the titles of agriculture, energy, waste and industry on the basis of sectors. This paper aims at examining the past trends in emissions, the sources and mitigation strategies of the methane. As a result of the study, it is determined that the agricultural sector is the biggest source of methane emissions among the sectors. The energy, waste and industry follow the agricultural sources respectively.     

Uncertainties in estimating the roughness coefficient of rock fracture surfaces

Joint roughness has a critical role in the deformation behavior of discontinuous rock masses. Several subjective (visual comparison) and quantitative (statistical and fractal) approaches have been proposed for estimating rock joint roughness coefficient (JRC). Using a large collection of 223 published joint profiles, this study investigates variability of the JRC estimates by these approaches. Among the profile parameters, maximum height (R _z), ultimate slope (λ), and fractal dimension (D _h–L, determined using the hypotenuse leg method) show a lower sensitivity to the sampling interval than the root mean square of the first deviation (Z ₂), profile elongation index (δ), fractal dimension (D _c, determined using the compass-walking method), and standard deviation of the angle i (σ _i ). Accordingly, this study proposes two separate sets of equations for quantitatively estimating JRC. The performances of these equations are examined by performing direct shear tests on 23 rock joint samples. The subjective approach is found to underestimate JRC by less than two units because it ignores (1) the main trend of the compared profile and (2) the limited scope of the standard profiles. Following these results, the visual comparison chart is updated by explicitly adding a scale bar for the y-axes of the standard profiles. Several basic rules for visual comparisons are also proposed.