Hasil Pencarian  ::  Simpan CSV :: Kembali

"The automotive industry is waking up to the fact that hybrid electric vehicles could provide an answer to the ever-increasing need for lower-polluting and more fuel-efficient forms of personal transport. This is the first book to give comprehensive coverage of all aspects of the hybrid vehicle design, from its power plant and energy storage systems, to supporting chassis subsystems necessary for realising hybrid modes of operation. Key topics covered include hybrid propulsion system architectures, propulsion system sizing, electric traction system sizing and design, loss mechanisms, system simulation and vehicle certification."

"Stochastic reachability analysis of hybrid systems is a self-contained and accessible introduction to this novel topic in the analysis and development of stochastic hybrid systems. Beginning with the relevant aspects of Markov models and introducing stochastic hybrid systems, the book then moves on to coverage of reachability analysis for stochastic hybrid systems. Following this build up, the core of the text first formally defines the concept of reachability in the stochastic framework and then treats issues representing the different faces of SRA, stochastic reachability based on Markov process theory, martingale methods, stochastic reachability as an optimal stopping problem, and dynamic programming. The book is rounded off by an appendix providing mathematical underpinning on subjects such as ordinary differential equations, probabilistic measure theory and stochastic modeling, which will help the non-expert-mathematician to appreciate the text. "

"The problem of viability of hybrid systems is considered in this work. A model for a hybrid system is developed including a means of including three forms of uncertainty : transition dynamics, structural uncertainty, and parametric uncertainty. A computational basis for viability of hybrid systems is developed and applied to three control law classes. An approach is developed for robust viability based on two extensions of the controllability operator. The three-tank example is examined for both the viability problem and robust viability problem.The theory is applied through simulation to an active magnetic bearing system and to a batch polymerization process showing that viability can be satisfied in practice. The problem of viable attainability is examined based on the controllability operator approach introduced by Nerode and colleagues. Lastly, properties of the controllability operator are presented."

"Traditional dwellings have undergone constant change in recent decades as a result of modernization. Though the change is physically visible, a theoretically indiscernible tradition is maintained as a way of sustaining social and cultural systems. A hypothetical assumption asserts that a symbolic cultural value, a ‘traditional core,’ exists as a sustainable system that functions within a modernized structure. This study begins by identifying the traditional core in question and proceeds to investigate its power over contemporary, modernized forms of dwelling. The study’s approach takes on the basic theory of physical change and the key ideas of structuralism. The main findings concern these two interrelated aspects, which are the result of a sustainable system, namely the hybrid dwelling, and the authoritative power that social and cultural systems have over house form."

"Arsitektur model deep learning kini sudah semakin kompleks setiap harinya. Namun semakin besar model maka dibutuhkan kekuatan komputasi yang cukup besar juga dalam menjalankan model. Sehingga tidak semua perangkat Internet of Things (IoT) dapat menjalankan model yang begitu besar secara efisien. Untuk itu teknik model optimization sangat diperlukan. Pada penelitian kali ini penulis menggunakan metode optimasi menggunakan layer weight regularization, serta penyederhanaan arsitektur model pada hybrid deep learning model. Dataset yang digunakan pada penelitian kali ini adalah N-BaIoT. Sementara evaluasi performa model yang digunakan adalah accuracy, confussion matrix, dan detection time. Dengan tingkat accuracy yang sama, model yang diusulkan berhasil meningkatkan waktu deteksi model lebih cepat 0,8 ms dibandingkan dengan model acuan.

---

The deep learning model architecture is getting more complex every day. However, the larger the model, the greater the computational power is needed to run the model. So not all Internet of Things (IoT) devices can run such a large model efficiently. For this reason, model optimization techniques are needed. In this study, the author uses an optimization method using layer weight regularization, as well as simplification of the model architecture on the hybrid deep learning model. The dataset used in this research is N-BaIoT. While the evaluation of the performance of the model used is accuracy, confusion matrix, and detection time. With the same level of accuracy, the proposed model succeeded in increasing the detection time of the model by 0.8 ms faster than the reference method."

"One way to model fractal object is by IFS (Iterated Function Systems) model based on affine trans-formation functions. Rotational effect of star-like object in IFS fractal model can be exhibited by means of metamorphical animation method instead of by the affine rotational operation of non meta-morphical animation method. The metamorphical version has an advantage over the non metamor-phical version in the independency of object?s relative position to the fixed point as an absolute cen-troid. Therefore, the rotational effect can be exhibited at any positions. In addition, it can be combined with rotational effect of the local centroid itself around the absolute centroid as a fixed point by the primitive rotational operation to form an interesting behaviour of orbital trajectory. So based on the hybrid of both animation methods, the animation simulation of orbital trajectory on a twin stars rota-ting to each other as a system can be done. Both objects are rotated in the same angular direction, but started in the opposite position around two closely different fixed points. So, the orbital trajectory yielded forms an elliptical path. The two similar objects can be created efficiently by cloning-scaling technique. In general, the animation method can be modeled as an animation framework.

---

Salah satu cara memodelkan objek fraktal adalah dengan model IFS (Iterated Function Systems) berdasarkan transformasi affine. Efek rotasi objek yang menyerupai bintang dari fraktal IFS dapat dijalankan melalui metoda animasi metamorfik sebagai pengganti operasi rotasi affine pada metoda animasi non metamorfik. Kelebihan metoda animasi yang metamorfik dibandingkan metoda animasi yang non metamorfik adalah dalam hal ketidakbergantungan posisi objek terhadap titik tetap sebagai titik pusat (centroid) absolut, sehingga efek rotasi dapat terjadi di manapun objek berada dan selain itu memungkinkan dikombinasikan dengan efek rotasi di seputar centroid lokal dengan efek rotasi operasi rotasi affine objek tersebut terhadap centroid absolut, sehingga menghasilkan hasil animasi berbentuk jejak orbit objek yang menarik untuk diobservasi. Jadi berdasarkan hibrida kedua metoda animasi, maka memungkinkan simulasi animasi yang menghasilkan jejak orbit sistem bintang ganda dapat dilakukan. Kedua objek bintang berotasi dengan arah rotasi yang sama tetapi berada pada posisi berlawanan seputar dua titik tetap berbeda, maka jejak orbit kedua objek tersebut berbentuk lonjong. Kedua objek dapat dikonstruksi secara efisien dengan teknik cloning-scaling. Secara umum hibrida metoda animasi dapat dimodelkan sebagai framework animasi."

"Seiring berkembangnnya teknologi, energi listrik menjadi semakin penting. Setiap aspek yang menggerakan dunia pada era ini bergantung dengan adanya energi ini. Namun salah satu sumber terbesar dari energi ini menghasilkan gas rumah kaca yang memicu pemanasan global. Oleh karena itu, muncul banyak dorongan untuk meminimalisasi kegunaan bahan bakar tak terbarukan yang salah satunya adalah bahan bakar disel. Bahan bakar ini sangat penting untuk menggerakan transportasi. Maka dari itu diperlukannya perkembangan dalam kendaraan hibrid, dimana kegunaan mesin diesel dapat diturunkan dan secara langsung menurunkan emisi gas rumah kaca. Dalam ranah itu, Model Predictive Control mulai dikembangkan untuk mengendalikan distribusi daya pada kendaraan hibrid. Dengan mengoptimasi kegunaan mesin diesel maka konsumsi dari bahan bakar juga semakin minim. Dengan perkembangan strategi ini, sebuah long shrinking horizon diakomodasikan pada strategi MPC biasa dengan sampling time yang lebih panjang. Penambahan ini menghasilkan sebuah pengendali MPC yang dapat melakukan optimasi terhadap keseluruhan perjalanan dan mendapatkan hasil yang lebih efisien dengan dengan mengorbankan waktu komputas. Setelah melakukan simulasi, MH-MPC dapat menggunakan baterai untuk 44.13% perjalanan sedangakan MPC biasa hanya dapat mengguanakan 33.53%

---

With the development of technology, the need of electricity has been even more evident. Every aspect that governs the world revolves around this energy. However, one of the biggest sources of energy is also one of the biggest contributors to the emission of green house gasses. With that in mind, there has been a major push in the effort of minimizing the usage of these sources, one of them being diesel. This fuel is very important especially in the realms of transportation. With that being the case, the need of hybrid vehicles is becoming more relevant in which, the usage of the diesel engine will be reduced as will the emission of green house gasses. In this realm, the usage of Model predictive controllers has been heavily researched as a Energy Management System. One of the outcomes of this research is an additional shrinking horizon to add on the conventional MPCs. This addition creates a Model Predictive Controller that can essentially optimize the condition for the entire trip in exchange for computational effort. After the simulations, the MHMPC is able to use the battery for 44.13% of the trip while the conventional MPC is only able to achieve 33.53%."