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Pencahayaan merupakan salah satu hal terpenting dalam dunia sinematografi. Ada beberapa parameter yang harus diperhatikan untuk menghasilkan pencahayaan yang baik. Ada begitu banyak permutasi dalam pengaturan pencahayaan ini. Hal ini menyebabkan rumitnya proses tersebut dan tidak ada cara yang cukup mudah untuk melakukan perhitungannya. Kerumitan ini ditambah lagi dengan kenyataan bahwa setiap sutradara memiliki gaya masing-masing dalam pengaturan tata cahaya dalam proses produksi film. Makalah ini mengacu pada tabulasi dari hasil wawancara terhadap tiga sutradara dan kemudian diambil kesamaan dari ketiganya. Pada makalah ini dibangun suatu struktur logika fuzzy dengan lima parameter pengaturan pencahayaan, yaitu situasi dari set, point of view kamera, intensitas cahaya terpasang, posisi dan arah kamera, serta emosi dari karakternya. Uji coba dilakukan menggunakan dua puluh scene film animasi yang dibangun menggunakan Unity. Penilaian hasil keluaran dilakukan secara manual oleh beberapa desainer film animasi. Sebagai hasilnya, desainer menilai bahwa 80% tata cahaya yang dihasilkan sudah sesuai dengan keinginan.

Future power systems with a high penetration level of inverter-based renewable sources (IBRSs) will be vulnerable to severe grid faults because of the noticeable reduction in the total system inertia. Particularly, challenges will arise in securing the transient stability limits of synchronous generators in the systems. Fortunately, the stability limits can be extended by utilizing the existing inverter-based units as virtual damping devices. This paper proposes the utilization of an inverter-based supercapacitor (IBSC) to extend the critical clearing time (CCT) of a power system with a high penetration level of IBRSs; thus, it makes it possible to secure the transient stability limits of SGs. In order to utilize an IBSC, the controllability of the IBSC is explored by considering two factors: control scheme and location of the IBSC. First, to determine an effective control scheme for the IBSC, three control schemes, which are power-damping control, speed-damping control, and power and speed-damping control, are tested under severe fault conditions. Then, using each control scheme, the location of the IBSC is chosen in a certain power system by the most extended CCT. The proposed utilization strategy was validated under various scenarios in a modified IEEE 14-bus system using the PSCAD simulator.

Determining the right class on student achievement is important in an evaluation process, because placing students in the right class helps lecturer in reflecting the successfullness of learning process. This problem relates to the performance of classification method which is measured by the classifier metrics. High performance is indicated by the optimality of these classifier's metrics. Besides, meta-algorithm adaptive boosting has been proven to be able to improve the performance of classifier in various fields. Therefore, this paper employs adaptive boosting to reduce the number of incorrect student placement in a class. The experimental results of implementing adaptive boosting in classifying student achievement shows that there is an increase of performance of all classification metrics, i.e., Kappa, Precision, Recall, F-Measure, ROC, and MAE. In terms of accuracy, J-48 is able to rise about 3.09%, which means this method reduces three misclassified students. Additionally, decisionStump increases 12.37% of accuracy. This also means this method is able to decrease 12 misclassified students. Finally, Simple Cart reaches the highest accuracy of about 23.71%, while the number of misclassified students is reduced to 24 students. However, there is no improvement in Random Forest method by using this adaptive boosting.

Segmentation of moving objects is one of the challenging research areas for video surveillance application. The success of object changing position for segmentation is when the moving object completely separate the foreground from its background of frame. It depends on many factors, including the use of suitable clustering method to differentiate the pixels of the foreground and background. This paper propose to use k-means as clustering method for moving object segmentation. The method is evaluated on several distance measures. Several steps are performed to conduct the moving object segmentation, such as frame subtraction, median filtering, and noise removal. These steps are proposed to improve the achievement of moving object segmentation. The performance are evaluated by using Mean of Square Error and Peak Signal to Noise Error. The value of both measurement are 135.02 and 25.52. The experimental result shows that the moving object segmentation performs the best result on Minkowski distance.

Analytical models have been developed to diminish test procedures for product realization, but they have only been partially successful in predicting the performance of battery systems consistently. The complex set of interacting physical and chemical processes within battery systems has made the development of analytical models of significant challenge. Advanced simulation tools are needed to be more accurately model battery systems which will reduce the time and cost required for product realization. As an alternative approach begun, the development of cell performance modeling using non-phenomenological models for battery systems were based on artificial neural networks (ANN) using Matlab 7.6.0(R2008b). ANN has been shown to provide a very robust and computationally efficient simulation tool for predicting state of charge for Lead Acid cells under a variety of operating conditions. In this study, the analytical model and the neural network model of lead acid battery for electric vehicle were used to determinate the battery state of charge. A precision comparison between the analytical model and the neural network model has been evaluated. The precise of the neural network model has error less than 0.00045 percent.

The accuracy level of the student determination in a class often has been paid less attention in educational data mining. So, this paper studies how to improve the performance of classification method to reach the higher of level accuracy. Therefore, we optimize logistic regression using equal frequency discretization method. Here, we test the student data by three intervals, four intervals, and five intervals. For logistic regression, we implement two regularization types, namely: lasso, ridge. Furthermore, to evaluate the results, we use the random sampling technique. Additionally, we measure the results by four classifier metrics, namely: F1, precision, accuracy, and recall. The experimental result shows that this method can be applied to optimize the logistic regression. On logistic regression_lasso and logistic regression_ridge, the three intervals achieve the highest of accuracy level. They can improve the accuracy level about 9% - 9.4%, respectively.

Nowadays, the proliferation of game technology especially in intelligent human-like NPCs (Non-Player Characters) leads to more adaptive behavior of NPCs maneuvers. Providing smoother behaviors require comprehensive rules base which can respond to players behaviors. Addressing this requirement we propose NPCs which had tactical behaviors based on fuzzy logic. The fuzzy logic defines four type behaviors for the NPCs, which depend on NPC health, ammo, and distance of the enemy.Those behaviors implemented on two intelligent agents employed Hierarchical Finite State Machine to express the maneuver actions of NPC during combat scenes. Using First Person Game Engine, the performance of NPCs with fuzzy behavior compared with NPC without fuzzy behavior. The results of experiment showed the performance of the NPC with Fuzzy behavior outperform 80% better than the NPC without fuzzy behavior.

In order to achieve the optimization of the production process, power continuity is needed. The most important is the protection system, overcurrent relays are widely used as a primary relay to protect overload and short circuit. However, in some cases due to the nonlinearity pattern of the system, overcurrent relays does not grant the protection system. To overcome this problem, under-frequency and under-voltage relay are installed as a backup relay, but it also do not give the best result. This paper focused on the addition of reverse power relay to improve the system performance. Transient stability analysis is necessary to set reverse power relay because optimal power flow analysis cannot give proper parameter when a failure in grid happen. By arranging the delay time between those relays according to IEEE 242-2001, adequate coordination can be done. Moreover, the frequency and the voltage of the system stable at 100.04%, and 100.01%. [ABSTRACT FROM AUTHOR]