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"Dibahan mengenai perencanaan dan penjadwalan jaringan proyek berdasarkan fungsi utilitas. Agar jaringan proyek diselesaikan dalam jangka waktu dan biaya yang minimum, maka utilitas setiap aktifitas pada proyek tersebut harus dimaksimumkan. Model matematis yang mendasarinya adalah pemogramana linear parametrik. Untuk mencari aktifitas yang akan dipercepat jangka waktunya digunakan metode Ford-Fulkerson, sedangkan algoritma Primal-Dual digunakan untuk menetapkan besarnya waktu percepatan."

"Tugas akhir ini menguji dan menganalisa perbandingan antara metode Sparse Representation baik melalui algoritma Lasso dan algoritma Primal-Dual untuk minimisasi L1, dengan metode Eigenface dalam sistem pengenalan wajah berbasis komputer. Komponen yang diperbandingkan adalah tingkat akurasi yang dicapai dan tingkat kecepatan yang digunakan kedua metode. Hasil pengujian menunjukkan bahwa metode Sparse Representation melalui algoritma Lasso memiliki tingkat akurasi yang paling baik dan stabil, serta memiliki tingkat efisiensi terbaik dalam waktu komputasinya.

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This study tests and analyses two methods of face recognition, namely Sparse Representation via both Lasso algorithm and Primal-Dual algorithm for L1 minimisation, and Eigenface, in terms of their level of accuracy and level of resource efficiency. Test results conclude that Sparse Representation method is more stable and has a better level of accuracy and resource efficiency."

"As human beings, we are fascinated by what makes us tick. We know that nature gave us certain biological appetites to ensure our survival, among those the need for water, food, sex, and love, but meeting these alone is not enough to ensure happiness. Scientists, and now managers, are realizing that people have a biological need to experience social rewards like praise, the thrill of innovation, and the satisfaction of acquiring new skills. To succeed, every manager needs to realize that work must provide more than just a paycheck and that quenching these social appetites is the key to creating passionate emloyees whose productivity blows away the bottom line. Primal Management is the first book to bring together the five impulses at the core of human motivation (innovation, competency, attaining goals, cooperation, and self-protection). It reveals that to drive employees, the workplace has to satisfy these appetites, and offers practical tips on how to do it and metrics for measuring success. Respected consultant Paul Herr explodes the myth that emotions have no place on the job and explores how this belief actually harms employee performance. Using examples of companies that have benefited from the principles of primal management, he shows how businesses can measure their emotional health, address areas where they don't engage employees, and increase productivity by boosting the emotional paycheck. Based on groundbreaking scientific research, this book will change the way we inspire our people and show how fulfilled employees lead to incredibly profitable businesses."

"In the past decade, primal-dual algorithms have emerged as the most important and useful algorithms from the interior-point class. This book presents the major primal-dual algorithms for linear programming in straightforward terms. A thorough description of the theoretical properties of these methods is given, as are a discussion of practical and computational aspects and a summary of current software. This is an excellent, timely, and well-written work. The major primal-dual algorithms covered in this book are path-following algorithms (short- and long-step, predictor-corrector), potential-reduction algorithms, and infeasible-interior-point algorithms. A unified treatment of superlinear convergence, finite termination, and detection of infeasible problems is presented. Issues relevant to practical implementation are also discussed, including sparse linear algebra and a complete specification of Mehrotra's predictor-corrector algorithm. Also treated are extensions of primal-dual algorithms to more general problems such as monotone complementarity, semidefinite programming, and general convex programming problems."

"The thesis focuses on the control of blood glucose devices and design of implantable devices, and offers valuable insights on diabetes mellitus and related physiology and treatments. Diabetes mellitus is a widespread chronic disease in the modern world that affects millions of people around the globe. In Singapore, one in ten of the population has diabetes, and the severity of the problem has prompted the country’s prime minister to talk about the disease at the National Day Rally in 2017. Designing an artificial pancreas that can provide effective blood glucose control for individuals with diabetes is one of the most challenging engineering problems. The author reports on research into the development of an implantable artificial pancreas that can regulate blood glucose levels by delivering appropriate dosages of insulin when necessary. By sensing blood glucose and injecting insulin directly into the vein, the implantable device aims to remove delays that occur with subcutaneous blood glucose sensing and insulin delivery. Preliminary in-vitro and in-vivo experimental results suggest that the implantable device for blood glucose control could be a clinically viable alternative to pancreas transplant."