Penerapan nilai-nilaimurnidalam kalangan pelajar Sarjana muda pendidikan teknik dan vokasional semasa Menjalankan amali di makmal

Nilai murni ialah nilai yang menjadi asas kepada pembentukan akhlak dan amat penting untuk diserapkan kepada setiap individu khususnya kepada golongan pelajar. Namun demikian menurut kajian-kajian lepas, nilai murni masih kurang diterapkan dengan memuaskan dalam kalangan pelajar terutamanya semasa menjalankan keija amali di makmal. Oleh yang demikian kajian ini dijalankan bagi mengenal pasti sejauh mana pelajar dan pensyarah menerapkan nilai-nilai murni semasa proses pengajaran dan pembelajaran di makmal. Seramai 226 orang pelajar Saijana Muda Pendidikan Teknik dan Vokasional (PTV) menjadi responden dalam kajian ini. Soal selidik merupakan instrumen utama dalam kajian ini di samping temu bual dan pemerhatian sebagai instrumen sokongan. Data-data dikumpulkan dan dianalisis menggunakan perisian SPSS Versi 12.0 bagi mendapatkan min, sisihan piawai dan inferensi ANOVA manakala analisis kandungan bagi data temu bual dan pemerhatian. Dapatan kajian menunjukkan pelajar menerapkan kesemua nilai murni yang terlibat dalam kajian ini. Walau bagaimanapun didapati hanya sebahagian sahaja pensyarah menerapkan nilai-nilai murni kepada pelajar semasa proses pengajaran dan pembelajaran di makmal. Oleh yang demikian, pengkaji mengemukakan beberapa cadangan untuk memastikan pensyarah dan pelajar menerapkan nilai-nilai murni antaranya ialah pihak Universiti Tun Hussein Onn Malaysia (UTHM) perlu membuat penyeliaan dari masa ke semasa bagi memastikan pensyarah dan pelajar bersama-sama menerapkan nilai-nilai murni semasa proses pengajaran dan pembelajaran di makmal

Human Motion Trajectory Prediction: A Survey

With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots and advanced surveillance systems. This paper provides a survey of human motion trajectory prediction. We review, analyze and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual information used. We provide an overview of the existing datasets and performance metrics. We discuss limitations of the state of the art and outline directions for further research.Comment: Submitted to the International Journal of Robotics Research (IJRR), 37 page

Roadmap on optical security

Postprint (author's final draft

Machine Understanding of Human Behavior

A widely accepted prediction is that computing will move to the background, weaving itself into the fabric of our everyday living spaces and projecting the human user into the foreground. If this prediction is to come true, then next generation computing, which we will call human computing, should be about anticipatory user interfaces that should be human-centered, built for humans based on human models. They should transcend the traditional keyboard and mouse to include natural, human-like interactive functions including understanding and emulating certain human behaviors such as affective and social signaling. This article discusses a number of components of human behavior, how they might be integrated into computers, and how far we are from realizing the front end of human computing, that is, how far are we from enabling computers to understand human behavior