Driving at high speed is among the frequent causes of accidents. In this research, a warning system was developed to warn drivers when their speed beyond the safety limit. Haar cascade classifier was proposed for the detection system which comprises Haar features, integral image, AdaBoost learning, and cascade classifier. The system was implemented using Python OpenCV library and evaluated on road traffic video collected in one way traffic. As a result, the proposed method yields 97.92% of car detection accuracy in daylight and MSE of 2.88 in speed measurement.
Stroke is one of the leading causes of morbidity and mortality in all ages. Ischemic stroke activates excitotoxic glutamate cascade leading to brain tissue injury. Saccharomyces cerevisiae is a unicellular yeast widely found in nature. S. cerevisiae is neuroprotective and able to increase the differentiation of hematopoietic stem cells (HSCs) into neuronal cells. it may increase levels of neuroprotectant BDNF in the brain tissue, therefore increase the protection of neurons. BDNF may prevent glutamate-driven excitotoxicity by reducing glutamate levels. This study uses a randomized post-test only controlled group design. In this in vivo study, rodent models of ischemic stroke were divided into five groups comprising of the negative control group, positive control group, intervention group 1 (18mg/kgBW), intervention group 2 (36mg/kgBW) and intervention group 3 (72 mg/kgBW). Groups treated with Saccharomyces cerevisiae extract showed significantly increased BDNF levels in the brain tissue, and the expression of the glutamate level was significantly reduced (P <0.05) compared to the positive control group. Thus Saccharomyces cerevisiae has a promising potential to become a therapy against ischemic stroke disease. however further research is needed regarding the efficacy and toxicity of Saccharomyces cerevisiae.
Background: Stroke is the leading cause of morbidity and mortality in Indonesia. Dyslipidemia is one of the main risk factors of ischemic stroke. Atherogenic index of plasma (AIP) is the logarithm of the triglyceride’s plasma ratio concentration to high density lipoprotein cholesterol (HDL-C) plasma concentration. Previous studies showed that the high AIP at hospital admission was associated with deterioration of neurological deficits in patients with acute ischemic stroke.Methods: This is a cross sectional study with 82 sample of acute ischemic stroke subjects that consecutively collected from the medical records of Haji Adam Malik general hospital Medan from January to December 2019, AIP assessment performed at the 1st day of hospitalization and then at the 7th -onset the national institutes of health stroke scale (NIHSS) score assessment was count. Data analysis is conducted with Spearman test.Results: Demographic characteristics showed that most subjects were female (51.2%), at age range between 60 -68 years (30.5%), had high school education level (48.8%), self-employed (35.4%) and Bataknese (68.3%). The mean of AIP was 0.15±0.26 and the mean NIHSS score was 6.70±3.6. There was a positive significant and mild power of correlation between AIP and the NIHSS score (p=0.017; r=0.262).Conclusions: There is a significant relationship between AIP and the NIHSS score. The higher the AIP of acute ischemic stroke patients was associated with the increase in the NIHHS scores.
Kecelakaan lalu lintas sering terjadi disebabkan kendaraan yang melaju dengan kecepatan tinggi. Penelitian ini mengembangkan sistem penegakan speed bump (polisi tidur) yang dapat memberikan peringatan bagi pengemudi dalam memperlambat laju kendaraan dan memberikan kenyamanan saat melaju dengan kecepatan rendah. Penegakan speed bump dilakukan berdasarkan kecepatan kendaraan yang terdeteksi menggunakan metode Haar Cascade Classifier, yang merupakan gabungan beberapa konsep yaitu Haar Features, Integral Image, AdaBoost Learning, dan Cascade Classifier. Pengujian dilakukan menggunakan video jalan raya pada satu jalur. Sistem dibuat menggunakan interpreter python dengan library OpenCV. Pendeteksian didapatkan hasil yang cukup baik apabila dilakukan pada intensitas cahaya tinggi, dan didapatkan tingkat akurasi deteksi sebesar 97,92%. Perhitungan kecepatan kendaraan didapatkan dengan membandingkan hasil kecepatan pada sistem dengan video dalam keadaan real time, yang dibuktikan dari tingkat error dengan nilai MSE yaitu 2,88.
Mesin Open Top Roller (OTR) adalah suatu mesin penggulung daun teh yang terdapat pada pabrik PT Perkebunan Nusantara IV Unit Bah Butong yang berfungsi untuk mengeluarkan cairan sel pucuk layu dengan menggulung teh pucuk layu. Untuk mengetahui tingkat keefektifan dari mesin penggulung Open Top Roller (OTR) maka dilakukan analisa dengan metode OEE (Overall Equipment Effectiveness), Six Big Losses, dan menganalisa tingkat resiko kegagalan pada komponen mesin penggulung Open Top Roller (OTR) digunakan metode FMEA (Failure Mode and Effect Analysis) sehingga didapatkan nilai Risk Priority Number (RPN) yang tertinggi sebagai penyebab dominan kegagalan yaitu komponen Silinder penggulung, meja penggiling, Poros engkol, Elektro motor dan V-belt. Berdasarkan analisa didapat hasil perhitungan dengan nilai rata-rata availability 89.74%, performa efficiency 75.79%, rate of quality product 100% dan OEE (Overall Equipment Effectiveness) yaitu 67.99% dan nilai Risk Priority Number (RPN) pada komponen-komponen Silinder penggulung 21, meja penggiling 105, Poros engkol 120, Elektro motor 63 dan V-belt 30. Dengan adanya analisa ini dapat dirancang pencegahan sehingga dapat mengurangi terjadinya breakdown pada mesin penggulung Open Top Roller (OTR).
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