scholarly journals Jaringan Syaraf Tiruan Perceptron untuk Pengenalan Pola Makanan Sehat Rendah Kolesterol

2018 ◽  
Author(s):  
Muhammad Khoiruddin Harahap ◽  
Nurul Khairina
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Human Brain ◽  
Input Pattern ◽  
Cholesterol Diet ◽  
Weight Changes ◽  
High Cholesterol ◽  
Cholesterol Levels ◽  
Human Nerve ◽  
Low Cholesterol

With the computer, the computing process has become easier. Computers are used to model the biological nerves of the human brain, computers are trained and are taught how to act as human nerve cells capable of recognizing simple patterns. The artificial neural network is able to recognize the input pattern and will issue output in accordance with the target to be achieved. In this research Perceptron method is used to recognize the input pattern in the form of healthy food low cholesterol. This method works by adjusting the input with the target and doing the weight changes until there are no more errors found in each epoch. The result of the introduction of low cholesterol diet was found that egg whites, freshwater fish, and cheese were foods that contained low to moderate cholesterol levels. However, quail eggs are foods that contain high cholesterol levels..

scholarly journals Effects of saponins on bile acids and plasma lipids in the rat

1979 ◽  
Vol 42 (2) ◽  
pp. 209-216 ◽  
Author(s):  
D. G. Oakenfull ◽  
Dorothy E. Fenwick ◽  
R. L. Hood ◽  
D. L. Topping ◽  
R. L. Illman ◽  
...  
Keyword(s):  
Bile Acids ◽  
Plasma Lipids ◽  
Plasma Lipid ◽  
High Cholesterol Diet ◽  
Cholesterol Diet ◽  
High Cholesterol ◽  
Faecal Excretion ◽  
Neutral Sterols ◽  
Low Cholesterol ◽  
Bile Acid Secretion

1. The effects of feeding isolated saponins on plasma lipid concentrations and on concentrations of biliary and faecal bile acids and neutral sterols were studied in the rat.2. The animals were given one of four diets, i.e. a standard low-cholesterol synthetic diet, the diet+10 g saponins/kg, the diet+10 g cholesterol/kg, the diet+10 g cholesterol+10 g saponins/kg.3. Saponins partially reversed the hypercholesterolaemia caused by the high-cholesterol diet and increased both the rate of bile acid secretion and the faecal excretion of bile acids and neutral sterols. The proportionate contribution of the primary bile acids (particularly chenodeoxycholic) to faecal excretion was also increased by saponins.4. The results are discussed in relation to the hypothesis that saponins act by inducing the adsorption of bile acids by dietary fibre.

scholarly journals Analisis Jaringan Syaraf Tiruan untuk Memprediksi Jumlah Narapidana pada Lembaga Pemasyarakatan Simalungun dengan Metode Backpropagation

2019 ◽  
Vol 1 ◽  
pp. 762
Author(s):  
Vicky Adriani ◽  
Irfan Sudahri Damanik ◽  
Jaya Tata Hardinata
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Artificial Neural Network ◽  
Artificial Neural Networks ◽  
Human Brain ◽  
Network Architecture ◽  
Accuracy Rate ◽  
Backpropagation Algorithm ◽  
Artificial Neural ◽  
Detention Facilities

The author has conducted research at the Simalungun District Prosecutor's Office and found the problem of prison rooms that did not match the number of prisoners which caused a lack of security and a lack of detention facilities and risked inmates to flee. Artificial Neural Network which is one of the artificial representations of the human brain that always tries to simulate the learning process of the human brain. The application uses the Backpropagation algorithm where the data entered is the number of prisoners. Then Artificial Neural Networks are formed by determining the number of units per layer. Once formed, training is carried out from the data that has been grouped. Experiments are carried out with a network architecture consisting of input units, hidden units, and output units. Testing using Matlab software. For now, the number of prisoners continues to increase. Predictions with the best accuracy use the 12-3-1 architecture with an accuracy rate of 75% and the lowest level of accuracy using 12-4-1 architecture with an accuracy rate of 25%.

scholarly journals New Method for Locker Door with Face Security System Using Backpropagation Algorithm

2018 ◽  
Vol 7 (2.13) ◽  
pp. 402
Author(s):  
Y Yusmartato ◽  
Zulkarnain Lubis ◽  
Solly Arza ◽  
Zulfadli Pelawi ◽  
A Armansah ◽  
...  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Pattern Recognition ◽  
Artificial Neural Network ◽  
Artificial Neural Networks ◽  
Human Brain ◽  
Back Propagation ◽  
The Face ◽  
Artificial Neural ◽  
Hidden Layer

Lockers are one of the facilities that people use to store stuff. Artificial neural networks are computational systems where architecture and operations are inspired by the knowledge of biological neurons in the brain, which is one of the artificial representations of the human brain that always tries to stimulate the learning process of the human brain. One of the utilization of artificial neural network is for pattern recognition. The face of a person must be different but sometimes has a shape similar to the face of others, because the facial pattern is a good pattern to try to be recognized by using artificial neural networks. Pattern recognition on artificial neural network can be done by back propagation method. Back propagation method consists of input layer, hidden layer and output layer.  

scholarly journals Phaleria macrocarpa Boerl. (Thymelaeaceae) Leaves Increase SR-BI Expression and Reduce Cholesterol Levels in Rats Fed a High Cholesterol Diet

Molecules ◽  
2015 ◽  
Vol 20 (3) ◽  
pp. 4410-4429 ◽  
Author(s):  
Yosie Andriani ◽  
Tengku Tengku-Muhammad ◽  
Habsah Mohamad ◽  
Jasnizat Saidin ◽  
Desy Syamsumir ◽  
...  
Keyword(s):  
High Cholesterol Diet ◽  
Cholesterol Diet ◽  
High Cholesterol ◽  
Cholesterol Levels ◽  
Phaleria Macrocarpa

Pharmacological activation of LXR in utero directly influences ABC transporter expression and function in mice but does not affect adult cholesterol metabolism

2008 ◽  
Vol 295 (6) ◽  
pp. E1341-E1348 ◽  
Author(s):  
E. M. E. van Straten ◽  
N. C. A. Huijkman ◽  
J. F. W. Baller ◽  
F. Kuipers ◽  
T. Plösch
Keyword(s):  
Fetal Development ◽  
Cholesterol Metabolism ◽  
In Utero ◽  
Cholesterol Homeostasis ◽  
High Cholesterol Diet ◽  
Cholesterol Diet ◽  
High Cholesterol ◽  
High Fat ◽  
Hepatic Expression ◽  
Cholesterol Levels

Cholesterol is critical for several cellular functions and essential for normal fetal development. Therefore, its metabolism is tightly controlled during all life stages. The liver X receptors-α (LXRα; NR1H3) and -β (LXRβ; NR1H2) are nuclear receptors that are of key relevance in coordinating cholesterol and fatty acid metabolism. The aim of this study was to elucidate whether fetal cholesterol metabolism can be influenced in utero via pharmacological activation of LXR and whether this would have long-term effects on cholesterol homeostasis. Administration of the LXR agonist T0901317 to pregnant mice via their diet (0.015% wt/wt) led to induced fetal hepatic expression levels of the cholesterol transporter genes Abcg5/g8 and Abca1, higher plasma cholesterol levels, and lower hepatic cholesterol levels compared with controls. These profound changes during fetal development did not affect cholesterol metabolism in adulthood nor did they influence coping with a high-fat/high-cholesterol diet. This study shows that the LXR system is functional in fetal mice and susceptible to pharmacological activation. Despite massive changes in fetal cholesterol metabolism, regulatory mechanisms involved in cholesterol metabolism return to a “normal” state in offspring and allow coping with a high-fat/high-cholesterol diet.

scholarly journals Perancangan Sistem Pendukung Keputusan Untuk Prediksi Penerima Beasiswa Menggunakan Metode Neural Network Backpropagation

2018 ◽  
Vol 5 (2) ◽  
pp. 157 ◽  
Author(s):  
Ade Pujianto ◽  
Kusrini Kusrini ◽  
Andi Sunyoto
Keyword(s):  
Neural Network ◽  
Decision Making ◽  
Artificial Neural Network ◽  
Human Brain ◽  
Learning Rate ◽  
Neural Network Modeling ◽  
Complex Problems ◽  
Backpropagation Method ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

<p class="Judul21">Seleksi di Amikom masih mengalami kendala pada proses pengambilan keputusan, banyaknya data menyebabkan pengambil keputusan membutuhkan tools yang dapat membantu dalam menentukan penerima beasiswa, salah satu metode yang sering digunakan adalah artificial neural network (ANN). Metode ini meniru jaringan pemodelan saraf otak manusia berupa neuron-neuron untuk menyelesaikan suatu permasalahan. Salah satu penerapan neural network adalah untuk melakukan prediksi atau peramalan terhadap suatu peristiwa tertentu serta dianggap mampu menyelesaikan masalah yang komplek seperti penalaran otak manusia. Untuk menyelesaiakn masalah yang komplek neural network memerlukan banyak neuron atau yang biasa disebut layer (lapis). Salah satu metode neural network multi lapis adalah backpropagation yang mampu mengoptimalisasi bobot pada neuron dan menyelesaikan masalah yang komplek. Hasil dari penelitian ini adalah sebuah perancangan sistem prediksi dengan menggunakan metode neural network backpropagation untuk melakukan peramalan terhadap mahasiswa yang mendaftar beasiswa. hasil akhir penelitian ini adalah nilai akurasi sebesar 90% dan nilai error terkecil sebesar 0,000101 pada epoch ke 329 dengan jumlah 3000 data dengan pembagian data training 2.250 dan 750 data testing serta konfigurasi learning rate sebesar 0,2 dan momentum 0,2.</p><p class="Abstrak"> </p><p><strong>Kata kunci</strong>: <em>Artificial Neural netwok</em><em>, </em><em>Backpropagarion, </em><em>Prediksi, beasiswa, Pengambilan Keputusan.</em></p><p><em> </em></p><p class="Judul21"><em>Abstract</em></p><p class="Judul21"><em>Selection in Amikom is still constrained in the decision-making process, the number of data causing decision makers need tools that can assist in determining scholarship recipients, one of the most commonly used method is artificial neural network (ANN). This method mimics the neural network modeling of the human brain in the form of neurons to solve a problem. One application of neural network is to make predictions or forecasting of a particular event and is considered capable of solving complex problems such as human brain reasoning. To solve the problem the complex neural network requires many neurons or so-called layers. One method of multi layer neural network is backpropagation that is able to optimize the weight of neurons and solve complex problems. The result of this research is a prediction system design using neural network backpropagation method to forecast the students who apply for scholarship. the final result of this research is the accuracy value of 90% and the smallest error value of 0.000101 on epoch to 329 with the amount of 3000 data with sharing training 2,250 and 750 data testing and learning rate configuration of 0.2 and momentum 0.2.</em></p><p><strong>Keywords</strong>: <em>Artificial Neural Netwok, Backpropagarion, Prediction, Scholarship, Decision Making.</em></p>

scholarly journals Ezetimibe and Simvastatin Reduce Cholesterol Levels in Zebrafish Larvae Fed a High-Cholesterol Diet

Cholesterol ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-5 ◽  
Author(s):  
Ji Sun Baek ◽  
Longhou Fang ◽  
Andrew C. Li ◽  
Yury I. Miller
Keyword(s):  
Low Cost ◽  
Vascular Pathology ◽  
High Cholesterol Diet ◽  
Cholesterol Diet ◽  
High Cholesterol ◽  
Lipoprotein Oxidation ◽  
Drug Candidates ◽  
Zebrafish Larvae ◽  
Cholesterol Levels ◽  
Human Atherosclerosis

Cholesterol-fed zebrafish is an emerging animal model to study metabolic, oxidative, and inflammatory vascular processes relevant to pathogenesis of human atherosclerosis. Zebrafish fed a high-cholesterol diet (HCD) develop hypercholesterolemia and are characterized by profound lipoprotein oxidation and vascular lipid accumulation. Using optically translucent zebrafish larvae has the advantage of monitoring vascular pathology and assessing the efficacy of drug candidates in live animals. Thus, we investigated whether simvastatin and ezetimibe, the principal drugs used in management of hypercholesterolemia in humans, would also reduce cholesterol levels in HCD-fed zebrafish larvae. We found that ezetimibe was well tolerated by zebrafish and effectively reduced cholesterol levels in HCD-fed larvae. In contrast, simvastatin added to water was poorly tolerated by zebrafish larvae and, when added to food, had little effect on cholesterol levels in HCD-fed larvae. Combination of low doses of ezetimibe and simvastatin had an additive effect in reducing cholesterol levels in zebrafish. These results suggest that ezetimibe exerts in zebrafish a therapeutic effect similar to that in humans and that the hypercholesterolemic zebrafish can be used as a low-cost and informative model for testing new drug candidates and for investigating mechanisms of action for existing drugs targeting dyslipidemia.

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