No abstract

A geomagnetic survey aims to obtain a model related to geological conditions based on the magnetic properties of the rock. Forward modeling techniques can estimate the anomalies that will be observed based on anomalous bodies below the surface. The rectangular prism body forward modeling approach can approximate a complex anomaly body to be a prism group, thus simplifying the computational process of forward modeling. In this research, a program for computing the forward calculation of magnetic data with a rectangular prism approach is arranged. The program is applied to perform forward modeling of the Karangsambung geological conceptual model. Based on the modeling carried out, the magnetic anomaly range in the Karangsambung area was obtained, namely -3200 nT to 2700 nT with the smallest wavelengths based on the simulation results shown in the range of 200 meters. In addition, the forward modeling program is also used to transform geomagnetic data in the Karangsambung area. The transformations applied are the reduction to the poles and the upward continuation transformation by utilizing the equivalent source technique. Based on the transformation result, it can be interpreted that the area of the intrusion rock in Karangsambung is indicated by a magnetic anomaly value of up to 400 nT, While the area of sedimentary rocks, especially the Karangsambung Formation, is shown by a low magnetic anomaly value reaching -400 nT.

<p>The growing utilization of smartphones equipped with various sensors to collect and analyze information around us highlights a paradigm called mobile crowdsensing. To motivate citizens’ participation in crowdsensing and compensate them for their resources, it is necessary to incentivize the participants for their sensing service. There are several studies that used the Stackelberg game to model the incentive mechanism, however, those studies did not include a budget constraint for limited budget case. Another challenge is to optimize crowdsourcer (government) profit in conducting crowdsensing under the limited budget then allocates the budget to several regional working units that are responsible for the specific city problems. We propose an incentive mechanism for mobile crowdsensing based on several identified incentive parameters using the Stackelberg game model and applied the MOOP (multi-objective optimization problem) to the incentive model in which the participant reputation is taken into account. The evaluation of the proposed incentive model is performed through simulations. The simulation indicated that the result appropriately corresponds to the theoretical properties of the model.</p>