Influence of Laser Irradiation Times on Properties of Porous Silicon

Porous silicon (P-Si) has been produced in this work by photoelectrochemical (PEC) etching process. The irradiation has been achieved using diode laser of (2 W) power and 810 nm wavelength. The influence of various irradiation times on the properties of P-Si material such as P-Si layer thickness, surface aspect, pore diameter and the thickness of walls between pores as well as porosity and etching rate was investigated by depending on the scanning electron micrograph (SEM) technique and gravimetric measurements

Pengembangan Multimedia E-Book 3D Berbasis Mobile Learning untuk Mata Pelajaran Geografi SMA Guna Mendukung Pembelajaran Jarak Jauh

Multimedia E-Book 3D berbasis Mobile Learningdi kembangkan karena dapat membantu penyampaian materi lebih mudah, lebih menarik untuk belajar secara mandiri, serta tidak terbatas dalam ruang dan waktu. Tujuan penelitian ini adalah memberi informasi dan referensi bagi guru. Model Pengembangan yang digunakan yaitu model ADDIE. Pengujian tingkat kesesuaian antara konten aplikasi dengan ekspektasi pengguna dilakukan melalui uji coba ahli media, materi, dan kelompok pengguna. Hasil akhir penelitian ini adalah aplikasi multimedia E-book 3D yang dapat di aplikasikan di dekstop dan smartphone (Mobile Learning). Teknik pengumpulan data dilakukan dengan observasi, wawancara, dan angket. Instrumen penelitian berupa panduan observasi dan wawancara untuk analisis kebutuhan, sedangkan untuk uji produk digunakan kuesioner. Berdasarkan hasil pengembangan produk ini diperoleh hasil uji kelayakan ahli media, ahli materi, dan siswa. Hasil uji coba menunjukkan hasil yang baik, yaitu  kategori layak sampai sangat layak dengan rincian: (1) uji ahli materi mendapat modus skor 4 dengan persentase 60% sangat layak untuk aspek pembelajaran dan modus skor 4 sangat layak dengan persentase 75%, (2) uji ahli media mendapatkan hasil dari modus skor 4 sangat layak dengan persentase 64,71%, (3) uji oleh siswa memperoleh hasil kategori layak dengan modus 3 dan persentase 58,49% untuk kelayakan media. Berdasarkan hasil uji kelayakan maka produk multimedia layak untuk digunakan sebagai media pembelajaran mata pelajaran geografi di SMA

Pembelajaran Musik Berbasis Aplikasi Musescore 3

This study aims to describe the effect of the MuseScore 3 application on music learning outcomes for school students. This study uses a quantitative method with a true experimental approach with a Post-test Only Control Design research design. This study used two groups of subjects as samples, namely the control group and the experimental group. The samples of this study were students of class X IPS and X IPA with a total sample of 49. The sampling technique used total sampling, and the data analysis technique used a different test (t-test). The results showed that there were differences in learning outcomes between students who were taught using the MuseScore 3 application media and students who were not taught using the MuseScore 3 application media. This was indicated by the post-test average score of the experimental group, which was 79.06 higher than the average score. the control group's post-test average was 73.57. The t-count value is 2.589 and the significance value () is 0.013. From these results, it can be concluded that Ho is rejected, and Ha is accepted, because t-count > t-table value, 2.589> 2.408, and the significance value <0.05 (two-party test), 0.013 <0.05.   Keywords: Application, Media, Music Learning, MuseScore

Applied multivariate analysis of variance in experiment of randomized design

The general aim of an experimental design in this paper was to estimate the different treatments effects on the responses by statistical methods. The estimates must be averting biases and the random errors minimized as much as possible. We used multivariate analysis of variance (MANOVA) to analyze design of experiments for several responses. In this paper, we provided three fertilizers (mineral, humic, micro-elements) applied on Yellow Maize experiment. This experiment was conducted by completely randomized design (CRD). We tested four responses (Chlorophyll in paper, total ton / ha, paper area / cm2 and plant height / cm) together to find significant test between them. The partial correlations are between Chlorophyll in paper and total ton of 0.77727. The difference between first fertilizers (mineral) and 3rd fertilizers (micro-elements) are significantly different for the total ton

Gradient Descent Localization in Wireless Sensor Networks

Meaningful information sharing between the sensors of a wireless sensor network (WSN) necessitates node localization, especially if the information to be shared is the location itself, such as in warehousing and information logistics. Trilateration and multilateration positioning methods can be employed in two-dimensional and three-dimensional space respectively. These methods use distance measurements and analytically estimate the target location; they suffer from decreased accuracy and computational complexity especially in the three-dimensional case. Iterative optimization methods, such as gradient descent (GD), offer an attractive alternative and enable moving target tracking as well. This chapter focuses on positioning in three dimensions using time-of-arrival (TOA) distance measurements between the target and a number of anchor nodes. For centralized localization, a GD-based algorithm is presented for localization of moving sensors in a WSN. Our proposed algorithm is based on systematically replacing anchor nodes to avoid local minima positions which result from the moving target deviating from the convex hull of the anchors. We also propose a GD-based distributed algorithm to localize a fixed target by allowing gossip between anchor nodes. Promising results are obtained in the presence of noise and link failures compared to centralized localization. Convergence factor issues are discussed, and future work is outlined

Deep learning control for digital feedback systems: Improved performance with robustness against parameter change

Training data for a deep learning (DL) neural network (NN) controller are obtained from the input and output signals of a conventional digital controller that is designed to provide the suitable control signal to a specified plant within a feedback digital control system. It is found that if the DL controller is sufficiently deep (four hidden layers), it can outperform the conventional controller in terms of settling time of the system output transient response to a unit-step reference signal. That is, the DL controller introduces a damping effect. Moreover, it does not need to be retrained to operate with a reference signal of different magnitude, or under system parameter change. Such properties make the DL control more attractive for applications that may undergo parameter variation, such as sensor networks. The promising results of robustness against parameter changes are calling for future research in the direction of robust DL control