Hasil Pencarian  ::  Simpan CSV :: Kembali

"The majority of 0D/1D knock models available today are known for their poor accuracy and the great effort needed for their calibration. Alexander Fandakov presents a novel, extensively validated phenomenological knock model for the development of future engine concepts within a 0D/1D simulation environment that has one engine-specific calibration parameter. Benchmarks against the models commonly used in the automotive industry reveal the huge gain in knock boundary prediction accuracy achieved with the approach proposed in this work. Thus, the new knock model contributes substantially to the efficient design of spark ignition engines employing technologies such as full-load exhaust gas recirculation, water injection, variable compression ratio or lean combustion.Contents: Experimental Investigations and Thermodynamic Analysis Unburnt Mixture Auto-Ignition PredictionKnock Occurrence CriterionKnock Model Validation"

"Agent-Based Computational Economics (ACE) melihat interaksi dalam ekonomi dapat memberikan hasil yang tidak ekuilibrium sedangkan paham neoklasik melihat interaksi selalu menghasilkan ekuilibrium di dalam perekonomian. Dengan menggunakan sudut pandang ACE, salah satu asumsi dasar dalam ekonomi, yaitu asumsi constant returns to scale, dapat dilepas. Penelitian ini bertujuan melihat dampak pelepasan asumsi constant returns pada perilaku konsumen di dalam model Monocentric City melalui simulasi menggunakan model berbasis agen. Hasil penelitian menunjukkan bahwa penggunaan asumsi constant, increasing, atau decreasing returns pada model Monocentric City tidak memberikan hasil berbeda. Dengan demikian, bentuk preferensi konsumen tidak berpengaruh di dalam model Monocentric City.

---

Agent-based Computational Economics (ACE) sees interactions in the economy can produce outcome beside equilibrium whereas in Neoclassical views interactions always produce equilibrium. By using ACE standpoint, one of the basic assumptions in economics, namely the assumption of constant returns to scale, can be relaxed. This study examines the impact of relaxing constant returns assumption on consumer behavior in the Monocentric City model through simulation using agent-based model. The results showed that the use of constant, increasing, or decreasing returns assumptions did not produce different results. Thus, the different forms of consumer preferences have no effect on the Monocentric City model."

"Penelitian ini menganalisa dan membuat suatu model dalam mengoptimalkan rute dan jadwal pengiriman RMC ke pelanggan. Selama ini pendistribusian RMC ke pelanggan sangat tidak efisien, sehingga perlu dilakukan penelitian agar didapat jalur distribusi RMC yang optimal. Selain itu penentuan jadwal pengiriman truk juga dioptimalkan karena jika bisa mempersingkat waktu pengiriman maka perusahaan akan menghemat biaya overtime yang diakibatkan dari keterlambatan pengiriman. Untuk menyelesaikan permasalahan meminimalisir jarak distribusi digunakan metode Network Flow Model dengan subbab Shortest Route Problem, dimana metode ini mampu memecahkan permasalahan dalam menentukan rute distribusi yang tepat. Sedangkan penentuan jadwal distribusi truk mixer diselesaikan dengan metode longest processing time. Kemudian juga dilakukan pengkajian mengenai kelayakan perencanaan penambahan depot. Penambahan depot ini bertujuan untuk mengurangi keterlambatan jam kerja dan juga mempersingkat jarak tempuh pengiriman truk mixer ke pelanggan. Sehingga hasil yang diharapkan adalah rute distribusi yang optimal dan jadwal distribusi yang tepat waktu agar bisa menghemat biaya operasional distribusi.

---

This study analyzes and create a model in optimizing routes and delivery schedules to customers RMC. All this time the distributions of RMC to customers is not very efficient, so it is necessary to study in order to obtain the optimal distribution channels RMC. Besides determining the schedule of delivery trucks also are optimized because of if could shorten the delivery time, the company will save on overtime costs caused from delays in delivery. To solve the problems of the method used to minimize the distance distribution is Network Flow Models with section Shortest Route Problem, where the method is capable of solving the problems in determining the appropriate distribution routes. Meanwhile determination of the distribution schedule mixer truck solved by the method of longest processing time. Then also carried out studies on the feasibility of additional planning depot. The addition of depot aims to reduce delays and shorten working hours delivery mileage mixer trucks to customers. So the expected result is an optimal distribution routes and schedules on-time distribution in order to save operating costs of distribution."

"Sampai saat ini, sketsa wajah buatan tangan masih secara luas digunakan dalam kepolisian, terutama untuk menggambarkan karakter wajah seseorang dengan cepat pada proses pencarian tersangka maupun orang hilang. Polisi akan menggunakan sketsa wajah tersebut untuk mencari orang yang digambarkan. Telah banyak penelitian yang dilakukan untuk membuat cara ini semakin efektif. Salah satunya adalah membandingkannya dengan Database Pencarian Orang (DPO) ataupun membuat komposit wajah. Namun, pembuatan komposit wajah dengan aplikasi membutuhkan waktu yang cukup lama dan perbandingan dengan DPO secara langsung memiliki tingkat akurasi yang perlu dikembangkan lebih lanjut. Penelitian ini mengaplikasikan Generative Adversarial Networks (GAN) untuk mengubah gambar sketsa menjadi citra berwarna, menerapkan Total Variation (TV) pada loss function untuk meningkatkan performa model, dan menerapkan koreksi warna untuk memperbaiki warna kulit yang dihasilkan. Tujuan penelitian ini yaitu agar dapat menggambarkan karakter orang pada sketsa dengan lebih akurat dan cepat dibandingkan metode terdahulu. GAN sendiri adalah sebuah machine learning framework yang menggunakan dua buah network yaitu, generator dan diskriminator. Generator akan membuat sampel baru berdasarkan pola sampel dataset dan diskriminator akan menentukan apakah sampel yang dihasilkan nyata atau hasil dari generator. Sistem akan mengulang proses ini sampai generator dapat menghasilkan sampel yang sangat mirip dengan sampel dari dataset. Dataset yang digunakan dikumpulkan dari beberapa dataset lain dengan konfigurasi jumlah training 1355, validation 10, dan testing 68. Beberapa skenario dengan parameter berbeda dilakukan dan hasil terbaik didapati dengan menggunakan Lambda L1 sebesar 100 dan Lambda TV sebesar 0.00001 dengan nilai evaluasi SSIM 0.83 dan FID 94.705. Setelah diimplementasikan dengan koreksi warna, GAN menghasilkan citra yang lebih realistis dengan hasil evaluasi yang didapatkan adalah 0.76 dan 78.944 untuk SSIM dan FID. Dengan metode tersebut, GAN dapat menghasilkan citra yang realistis secara visual dari sketsa wajah dan memiliki warna yang sesuai dengan citra aslinya.

---

Until now, hand-drawn face sketches are still widely used in Indonesia's police force, especially to quickly describe the character of a person's face in the process of searching for suspects and missing persons. Police will use the face sketch to search for the respected person. A lot of research has been done to make this method more effective. One of them is to compare it with the People Search Database (DPO) or create a facial composite. However, making facial composites by application takes quite a long time, and direct comparison with DPO has a level of accuracy that needs to be developed further. This study applies a Generative Adversarial Networks (GAN) to convert a sketch image into a color image, applies a Total Variation (TV) to the loss function to improve model performance, and applies a color correction to improve the resulting skin tone. The purpose of this study is to be able to describe the character of the people on the sketch more accurately and quickly than the previous method. GAN itself is a machine learning framework that uses two networks, namely, generator and discriminator. The generator will create a new sample based on the sample dataset pattern, and the discriminator will determine whether the resulting sample is real or the result of the generator. The system repeats this process until the generator can generate a sample that is very similar to the sample from the dataset. The dataset used is gained from several other datasets with the split configuration of 1355 for training, 10 for validation, and 68 for testing. Several scenarios with different parameters were carried out, and the best results were obtained using Lambda L1 of 100 and Lambda TV of 0.00001 with an evaluation value of SSIM 0.83 and FID 94,705. After being implemented with color correction, GAN produces a more realistic image with the evaluation results obtained are 0.76 and 78.944 for SSIM and FID. GAN can produce visually realistic images from facial sketches and have colors that match the original image with this method."

"This book introduces and describes in detail the SEQUAL framework for understanding the quality of models and modeling languages, including the numerous specializations of the generic framework, and the various ways in which this can be used for different applications. Topics and features : contains case studies, chapter summaries, review questions, problems and exercises throughout the text, in addition to appendices on terminology and abbreviations, presents a thorough introduction to the most important concepts in conceptual modeling, including the underlying philosophical outlook on the quality of models, describes the basic tasks and model types in information systems development and evolution, and the main methodologies for mixing different phases of information system development, provides an overview of the general mechanisms and perspectives used in conceptual modeling, predicts future trends in technological development, and discusses how the role of modeling can be envisaged in this landscape."