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"This book draws from the everyday experiences as well as the harsh realities confronting behavioral care providers on the frontline. The book recounts the stories and sometimes disturbing emotions of people whose lives have undergone sudden change or even drastic trauma; people whose feelings of comfort and safety have been shattered by exposure to illness, abuse, death and bereavement. The perspectives and experiences of nurses, social care staff, patients, children and families are at the core of understanding the importance, challenges and therapeutic vitality of emotions. The 55 individuals on the frontline who took part in the interviews on which this study is based discuss the emotions associated with care in mental health, pediatric oncology, AIDS/HIV, as well as child protection and abuse, racism, refugee exile, poverty, and social exclusion. "

"Wajah manusia adalah kumpulan 44 urat di tengkorak atau rangkuman identitas anda? setiap orang memiliki wajah tetapi apa yang kita ketahui tentangnya? inilah cerita mengenai wajah manusia di seluruh dunia. John Cheese-aktor komedi, Profesor di universitas lange ar corne dan pengarang buku psikologis terlaris-menggabungkan analisa intelektual dengan sentuhan humor untuk menyelidiki wajah, penciptaannya, fungsi, seksualitas, komunikasi, identitas, dan persepsi. "

"Dengan jumlah penduduk ratusan juta, tentunya Indonesia akan dihuni oleh berbagai suku, ras, dan agama. Karakter Emosi seseorang juga merupakan salah satu keragaman yang dimiliki oleh setiap orang. Emosi memainkan peran penting dalam proses komunikasi. Bentuk komunikasi nonverbal adalah ekspresi wajah, postur tubuh, dan gerak tubuh. Pengenalan ekspresi wajah memiliki banyak aplikasi, seperti interaksi manusia-komputer, robot sosial, sistem alarm, dan animasi. Dalam penelitian ini, penulis membahas machine learning pada perangkat aplikasi perangkat lunak dengan mengevaluasi arsitektur CNN DenseNet untuk mendeteksi emosi melalui wajah. Sehingga Anda akan mendapatkan akurasi, komputasi & Top One Score terbaik. Penulis berfokus pada beberapa model CNN modern antara lain Rensenet & Densenet. Rensenet sendiri merupakan arsitektur CNN modern sebelum Densenet perbedaannya terletak pada koneksi antar blok dimana Densenet mampu melewatkan informasi pada setiap input layer dengan menggunakan metode (.) sedangkan Rensesnet hanya melewatkan informasi inputan awal dengan menggunakan metode penambahan (+). Arsitektur terbaik dari variasi DenseNet yang ada terdapat pada DenseNet 121 dengan variasi learning rate 0,1 dengan waktu komputasi 5524s, accuracy 80.68%, validation accuracy 80.22% dan Top-1 accuracy rate sebesar 87,19%.

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With a population of hundreds of millions, of course, Indonesia will be inhabited by various ethnicities, races, and religions. Character Emotions of a person are also one of the diversity that is owned by everyone. Emotions play an important role in the communication process. Forms of nonverbal communication are facial expressions, body postures, and gestures. Facial expression recognition has many applications, such as human-computer interaction, social robots, alarm systems, and animation. In this study, the author discusses machine learning on software application devices by evaluating the CNN DenseNet architecture to detect emotions through faces. So that you will get the best accuracy, computing & Top One Score. The author focuses on several modern CNN models, including Rensenet & Densenet. Rensenet itself is a modern CNN architecture before Densenet, the difference lies in the connection between blocks where Densenet is able to pass information at each input layer using the (.) method while Rensesnet only passes the initial input information by using additive methods (+). The best architecture of the existing DenseNet variations is found in DenseNet 121 with a learning rate variation of 0.1 with a computation time of 5524s, 80.68% accuracy, 80.22% validation accuracy, and Top-1 accuracy rate of 87.19%."