Denoising of EEG signal based on word imagination using ICA for artifact and noise removal on unspoken speech

The purpose of this research is to observe the effectiveness of independent component analysis (ICA) method for denoising raw EEG signals based on word imagination, which will be used for word classification on unspoken speech. The electroencephalogram (EEG) signals are signals that represent the electrical activities of the human brain when someone is doing activities, such as sleeping, thinking or other physical activities. EEG data based on the word imagination used for the research is accompanied by artifacts, that come from muscle movements, heartbeat, eye blink, voltage and so on. In previous studies, the ICA method has been widely used and effective for relieving physiological artifacts. Artifact to signal ratio (ASR) is used to measure the effectiveness of ICA in this study. If the ratio is getting larger, the ICA method is considered effective for clearing noise and artifacts from the EEG data. Based on the experiment, the obtained ASR values from 11 subjects on 14 electrodes amounted are within the range of 0,910 to 1,080. Thus, it can be concluded that ICA is effective for removing artifacts from EEG signals based on word imagination

MONITORING PERJALANAN MOBIL ANGKUT BERBASIS INTERNET OF THINGS (IOT)

Pada saat ini banyak orang yang menggunakan jasa pengiriman barang, khususnya pengiriman menggunakan mobil angkut. Oleh karena itu dibutuhkan perangkat yang dapat memantau kondisi serta posisi mobil angkut selama proses pengiriman barang berlangsung dan dapat menyimpan seluruh riwayat perjalanan. Hal ini dapat diwujudkan dengan menerapkan sistem pemantauan berbasis Internet of Things pada mobil angkut. Pengujian dilakukan menggunakan mobil angkut dengan daya angkut 1.500kg, panjang kendaraan 4.760 mm, lebar kendaraan 1.730mm dan tinggi kendaraan 2.570 mm, dengan menggunakan fitur GPS dan hotspot pada smartphone android.Setelah dilakukan pengujian sensor suhu yang digunakan masih memiliki galat sebesar 4,08 % dan sensor kelembapan sebesar 3,28 %. Sensor akselerometer dapat digunakan untuk mendeteksi barang yang jatuh. Sistem dan alat yang dibuat juga telah diuji dapat memantau perjalanan mobil angkut dari Kota Surabaya ke Kota Malang dengan jarak tepuh 81 Km dan waktu yang dibutuhkan sekitar 3 jam. Dengan dikembangkannya alat ini penyedia jasa pengiriman barang dapat memantau perjalanan kendaraan dan kondisi barang yang dibawanya hingga sampai ke tempat tujuan. ==================================================================================================== At this time many people use freight forwarding services, especially shipping using vehicles. the vehicles must always be considered so that it can reduce the possibility of things that are not desirable. This can be realized by implementing an Internet of Things monitoring system on vehicles. Tests are carried out using vehicle with a 4,760 mm length and 1,730 mm width. the temperature sensor used still has an error of 4.08 % and a humidity sensor of 3.28 %. The accelerometer sensor can detect items that have been fallen. The systems have been tested to monitor the vehicle and its goods from Surabaya city to Malang city with a distances of 81 Km and the time needed is around 3 hours. Supervisor can monitor the journey of the vehicle and its goods to reach the destination by using the monitoring devices and applications that used in this research

THE EFFECTS OF TRANSFER PRICING, THIN CAPITALIZATION, FIRM SIZE, AND TAX HAVEN COUNTRY UTILIZATION ON TAX AGGRESSIVENESS

This research aims to examine the effects of transfer pricing, thin capitalization, firm size, and tax haven country utilization on tax aggressiveness. This study uses manufacturing sector companies listed on Indonesia Stock Exchange (IDX) during 2017 – 2021 period. The total of samples used were 14 manufacturing sector companies for 5 years. This study used multiple linear regression analysis with the assistance of SPSS 25. The results of this research indicated that transfer pricing and thin capitalization have no effect on tax aggressiveness. While, firm size has a positive and significant effect on tax aggressiveness. Also, tax haven country utilization has negative and significant effect on tax aggressiveness This research have an implication for related parties, especially the Directorate General of Taxes of the Republic of Indonesia and taxpayers in minimizing tax aggressiveness Keywords : Aggressiveness, Transfer Pricing, Capitalization, Firm, Haven, Ta

Denoising of EEG signal based on word imagination using ICA for artifact and noise removal on unspoken speech

&lt;span&gt;The purpose of this research is to observe the effectiveness of independent component analysis (ICA) method for denoising raw EEG signals based on word imagination, which will be used for word classification on unspoken speech. The electroencephalogram (EEG) signals are signals that represent the electrical activities of the human brain when someone is doing activities, such as sleeping, thinking or other physical activities. EEG data based on the word imagination used for the research is accompanied by artifacts, that come from muscle movements, heartbeat, eye blink, voltage and so on. In previous studies, the ICA method has been widely used and effective for relieving physiological artifacts. Artifact to signal ratio (ASR) is used to measure the effectiveness of ICA in this study. If the ratio is getting larger, the ICA method is considered effective for clearing noise and artifacts from the EEG data. Based on the experiment, the obtained ASR values from 11 subjects on 14 electrodes amounted are within the range of 0,910 to 1,080. Thus, it can be concluded that ICA is effective for removing artifacts from EEG signals based on word imagination.&lt;/span&gt;</jats:p