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"Software tool to assist Mechanical and Aerospace Engineering students in courses involving design, manufacturing, and concurrent engineering skills.Provides online tutorials and instructional projects to link the capabalities of I-DEAS to course and project work; also interfaces with professional versions of I-DEAS"

"Aiming to reintroduce simplicity into the manufacturing process, the techniques explained in this volume substitute lightning-fast computer decision-making for human and mechanical agency in the production process, thus reducing disruptions and constraints."

"Penggunaan bahan bakar minyak bumi yang semakin tinggi sedangkan cadangan yang semakin berkurang membuat kaum akademi dan berbagai pihak yang bersangkutan berkompetisi melakukan penghematan bahan bakar. Eco-marathon salah satu kompetisi yang memperlombakan penghematan bahan bahan bakar diadakan oleh salah satu perusahaan minyak dunia. Kompetisi ini diikuti oleh akademisi dari berbagai belahan dunia termasuk mahasiswa Departemen Teknik Mesin Fakultas Teknik Universitas Indonesia. Mahasiswa yang mengikuti kompetisi ditantang untuk membuat, merancang, dan menguji kendaraan dan mesin yang teleh dibuat. Mesin hasil desain dan buatan mahasiswa Teknik Mesin Universitas Indonesia berkapasitas 65 cc dengan satu silinder dan Double Overhead Camshaft (DOHC). Mesin dengan desain DOHC lebih mudah dalam memvariasikan cam duration. Tiga variasi cam yang dilakukan penulis yaitu cam standar, advanced cam duration, dan retarded cam duration. Kondisi advanced cam duration memiliki overlap yang lebih besar dibanding kondisi cam standar, akan tetapi kondisi retarded cam duration tidak mempunyai overlap. Kondisi standar buka dan tutup yang digunakan adalah Intake Open 7˚ ATDC, Intake Close 20˚ BBDC, Exhaust Open 24˚ ABDC, dan Exhaust Close 9˚ ATDC. Cam Intake memiliki nilai puncak pada 80˚ ATDC sedangkan cam exhaust pada 112˚ ABDC. Dari pengukuran yang telah dilakukan didapat karakterisitik cam dari mesin 65 cc dengan intake valve memiliki durasi 153 derajat dan full lift pada 3,97 mm sedangkan untuk exhaust valve memiliki durasi 164 derajat dan full lift 3,85 mm.

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The use of petroleum fuels that higher while the amount of reserves is diminishing make the academics and various related parties compete to thrift on fuel. Eco marathon is one of competition which competed on the efficiency of fuel usage. This competition was hold by one of world’s oil company and followed by the academics from around the world, including the college students of Mechanical Engineering Department, Engineering Faculty of Universitas Indonesia. The college students which followed this competition were challenged to made, designed, and examined vehicles and machine that have been made. The machine has been designed and made by them had the 65 cc of capacities with a Double Overhead Camshaft and cylinder (DOHC). Machine with a DOHC design is easier to vary the cam duration. Considering the reason which is explained, the author is varying the cam duration and analyze its impact on power and torque. Three variations were done by the author are cam standard, advanced cam duration, retarded cam duration. The condition of advanced cam duration has a greater overlap than cam standard cam’s condition, whereas the condition of retarded cam duration doesn’t have an overlap. Open and close standard conditions are used Intake Open 7˚ ATDC, Intake Close 20˚ BBDC, Exhaust Open 24˚ ABDC and Exhaust Close 9˚ ATDC. Intake cam has a peak value at 80˚ ATDC while the exhaust cam at 112˚ ABDC. From the measurements that have been done cam characteristics obtained from 65 cc engine with intake valve has a duration of 153 degrees and at full lift of 3.97 mm while the exhaust valve has a duration of 164 degrees and a full lift of 3.85 mm."

"Salah satu organ tubuh yang paling penting adalah jantung. Darah dapat didistribusikan dengan baik ke seluruh tubuh jika terdapat jantung. Organ lain akan berhenti bekerja dan orang tersebut akan meninggal jika jantung di dalam tubuh tidak berfungsi dengan baik. Salah satu jenis penyakit jantung adalah terjadinya gejala arrhythmia, yaitu suatu bentuk kondisi jantung yang ditandai dengan laju atau irama detak jantung. Detak jantung bisa lebih cepat dari biasanya, atau terlalu lambat, atau bahkan memiliki pola yang tidak teratur. Metode yang paling umum dan banyak digunakan oleh ahli jantung dan praktisi medis untuk memantau dan mendeteksi penyakit atau kelainan pada jantung adalah dengan menggunakan elektrokardiogram (EKG) yang dianalisis secara manual, sehingga dapat memakan waktu yang lama dan rentan terhadap kesalahan. Penerapan Artificial Intelligence diharapkan mampu memberikan peranan penting dalam mempercepat kinerja kardiologi. Dalam penelitian ini digunakan Model CNN dengan Arsitektur ResNet-50 untuk mengklasifikasikan detak jantung normal dan detak jantung beberapa jenis arrhythmia yang akan divisualisasikan dengan algoritma Grad-CAM. Dari hasil eksperimen pengklasifikasian, didapatkan tingkat akurasi rata-rata sebesar 94% dan meningkat menjadi 99% untuk setiap kelas setelah dilakukan visualisasi dengan menggunakan algoritma Grad-CAM.

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One of the most important organs of the body is the heart. Blood can be well distributed throughout the body if there is a heart. Other organs will stop working and the person will die if the heart in the body is not functioning properly. One type of heart disease is the occurrence of symptoms of arrhythmia, which is a condition in which the heartbeat rate is too fast, to slow, or irregular. Currently, the most common and widely used method by cardiologists and other medical practitioners to monitor and detect diseases or abnormalities in the heart is to use an electrocardiogram (ECG), which is analyzed manually. where the task can take a long time and is prone to errors. The application of Artificial Intelligence is expected to play an important role in accelerating the performance of cardiologists. In this study, a CNN model with ResNet-50 architecture was used to classify normal heart rates and heart rates of several types of arrhythmia that would be visualized with the Grad-CAM algorithm. From the results of the classification experiment, an average accuracy rate of 94% was obtained and increased to 99% for each class after visualization using the Grad-CAM algorithm."