Perception of Macao Teachers and Students Regarding Gaming Operators\u27 Social Responsibility

The study brings to the forefront a discussion of corporate social responsibility of gaming operators. It assessed Macao high school students\u27 and teachers\u27 perceptions of the extent of social responsibility being exercised by the six local gaming operators, as well as their support for the operators, and desire for further gaming investment and work opportunities in the gaming sector. The majority of the respondents were not aware of gaming operators exercising socially responsible activities. Among those who were, the majority perceived that only one company was involved and none has participated in protecting the environment, beautifying the city, creating a harmonious environment, treating local staff fairly, and promoting responsible gambling. Five social responsibility factors were identified. Poisson regression analysis indicated that perception of gaming operators\u27 being considerate of Macao\u27s interests was influenced significantly by their contribution to three socially responsible activities

Proudly Agripreneurs! Learning from 24 young African business leaders

This booklet highlights key elements of the publication Ils l’ont fait ! published by CTA in collaboration with MediaProd from Burkina Faso, which outlines the achievements of 24 entrepreneurs that have been featured by Agribusiness TV. CTA wants to reveal the impacts these agripreneurs have had, and encourage other young people to take inspiration, so they too can better invest their efforts in agriculture. The booklet introduces the 24 young entrepreneurs and explains how they are addressing the key youth agripreneurship challenges they are facing

PEMBUATAN APLIKASI INTERAKTIF BERISI STIMULUS POSITIF UNTUK PERKEMBANGAN KARAKTER ANAK

Masa kanak-kanak adalah masa yang menyenangkan karena penuh dengan rasa ingin tahu dan selalu ingin bereksplorasi. Anak-anak selalu ingin melakukan dan mengetahui informasi yang baru. Tapi anak-anak masih belum dapat membedakan hal yang benar dan tidak benar jika belum diajarkan sebelumnya. Oleh karena itu dibutuhkan orangtua yang selalu mendampingi anak. Orangtua mengeajarkan hal benar dan tidak benar untuk dilakukan. Meskipun begitu, pada hasil interview pada beberapa responden, orangtua tidak sepenuhnya dapat mendampingi anak mereka. Pada saat orangtua tidak dapat mendampingi, mereka memberikan gadget agar dapat mengihibur anak. Gadget yang berisi permainan yang dapat merangsang pertumbuhan otak anak. Tapi masih kurangnya aplikasi pembelajaran interaktif dalam memberikan stimulus positif untuk perkembangan karakter anak. Dari permasalahan tersebut, maka dibuatlah sebuah aplikasi pembelajaran yang sifatnya interaktif agar dapat membantu anak-anak untuk menjadi anak yang mandiri. Aplikasi ini menyajikan contoh kasus yang sesuai dengan kehidupan sehari-hari yang ditunjang dengan gambar dan animasi. Selain itu, adanya interaktivitas pada aplikasi ini diharapkan dapat menarik perhatian serta meningkatkan kemudahan bagi anak untuk dapat memahami pesan yang disampaikan. &nbsp

Linear Prediction of Long-Memory Processes: Asymptotic Results on Mean-squared Errors

We present two approaches for linear prediction of long-memory time series. The first approach consists in truncating the Wiener-Kolmogorov predictor by restricting the observations to the last $k$ terms, which are the only available values in practice. We derive the asymptotic behaviour of the mean-squared error as $k$ tends to $+ \infty$. By contrast, the second approach is non-parametric. An AR($k$) model is fitted to the long-memory time series and we study the error that arises in this misspecified model

Linear Prediction of Long-Range Dependent Time Series

We present two approaches for next step linear prediction of long memory time series. The first is based on the truncation of the Wiener-Kolmogorov predictor by restricting the observations to the last $k$ terms, which are the only available values in practice. Part of the mean squared prediction error comes from the truncation, and another part comes from the parametric estimation of the parameters of the predictor. By contrast, the second approach is non-parametric. An AR($k$) model is fitted to the long memory time series and we study the error made with this misspecified model