Network Literature Recommendation Technology Based on User-Based Collaborative Filter

2014 ◽  
Vol 926-930 ◽  
pp. 2362-2365
Author(s):  
Ran He ◽  
Guo Hui Song ◽  
Shu Tao Sun
Keyword(s):  
Full Advantage ◽  
K Value ◽  
Collaborative Filter ◽  
Personalized Services

With the development of web2.0, network literature website has become an import carrier of publishing literature and getting novel. At present, the increasing of the number of network literature brings great confusion for audience. Therefore, network literature website need to recommend potential interested literature according to readers’ different requirements to take full advantage of resource and provide personalized services. The thesis we use the user-based collaborative algorithm to recommend readers for interested literature. We analysis the influence of k-value on recommend result and utilize kinds of Measurements to evaluate the results.

Scalability of MOCVD-deposited Hafnium Oxide

2003 ◽  
Vol 765 ◽  
Author(s):  
S. Van Elshocht ◽  
R. Carter ◽  
M. Caymax ◽  
M. Claes ◽  
T. Conard ◽  
...  
Keyword(s):  
Hafnium Oxide ◽  
Interfacial Layer ◽  
Gate Dielectric ◽  
Deposition Process ◽  
Oxide Thickness ◽  
Process Conditions ◽  
Primary Concern ◽  
Gate Electrode ◽  
K Value ◽  
High K

AbstractBecause of aggressive downscaling to increase transistor performance, the physical thickness of the SiO2 gate dielectric is rapidly approaching the limit where it will only consist of a few atomic layers. As a consequence, this will result in very high leakage currents due to direct tunneling. To allow further scaling, materials with a k-value higher than SiO2 (“high-k materials”) are explored, such that the thickness of the dielectric can be increased without degrading performance.Based on our experimental results, we discuss the potential of MOCVD-deposited HfO2 to scale to (sub)-1-nm EOTs (Equivalent Oxide Thickness). A primary concern is the interfacial layer that is formed between the Si and the HfO2, during the MOCVD deposition process, for both H-passivated and SiO2-like starting surfaces. This interfacial layer will, because of its lower k-value, significantly contribute to the EOT and reduce the benefit of the high-k material. In addition, we have experienced serious issues integrating HfO2 with a polySi gate electrode at the top interface depending on the process conditions of polySi deposition and activation anneal used. Furthermore, we have determined, based on a thickness series, the k-value for HfO2 deposited at various temperatures and found that the k-value of the HfO2 depends upon the gate electrode deposited on top (polySi or TiN).Based on our observations, the combination of MOCVD HfO2 with a polySi gate electrode will not be able to scale below the 1-nm EOT marker. The use of a metal gate however, does show promise to scale down to very low EOT values.

Photostability Study on Character and Antioxidant Activity of Tomato Extract (Solanum lycopersicum l.) in Nanostructured Lipid Carrier (NLC) and Conventional Creame

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Noorma Rosita ◽  
Dewi Haryadi ◽  
Tristiana Erawati ◽  
Rossa Nanda ◽  
Widji Soeratri
Keyword(s):  
Antioxidant Activity ◽  
Physical Stability ◽  
Nanostructured Lipid Carrier ◽  
Uvb Radiation ◽  
K Value ◽  
Antioxidant Power ◽  
Solanum Lycopersicum L ◽  
Tomato Extract ◽  
Dpph Method ◽  
High Shear Homogenization

The aim of this study was to investigate the ability of NLC in increasing photostability of tomato extract in term of antioxidant activity. Photostability testing on antioxidant activity of samples were conducted by accelerating method using UVB radiation 32.400 joule for 21 hours radiation. Antioxidant activity was measured by DPPH method. NLC was made by High Shear Homogenization (HPH) method at 24000 rpm for 4 cycles, while conventional creame was made by low speed at 400 rpm. The product were characterized include: pH, viscosity, and particle size. There were had difference characters and physical stability. NLC had smaller size, more homogenous and more stable than conventional creame. It was known that stability of antioxidant activity of tomato extract in NLC system higher than in conventional creame. That was showed with k value, as constanta of rate scavenging activity decreasing in antioxidant power between time (Sigma 2-tail less than 0.005) of NLC and conventional creame were: 2.03x10-2 %/hour ±0.08 (3.94) and 4.71x 10-2 %/ hour ±0.23 (4.88) respectively.

Optimization of K Value in KNN Algorithm for Spam and Ham Email Classification

2020 ◽  
Vol 4 (2) ◽  
pp. 377-383
Author(s):  
Eko Laksono ◽  
Achmad Basuki ◽  
Fitra Bachtiar
Keyword(s):  
Frequency Distribution ◽  
Confusion Matrix ◽  
High Accuracy ◽  
K Value ◽  
A Value ◽  
Optimal Value ◽  
Classification Evaluation ◽  
Email Spam ◽  
Email Classification

There are many cases of email abuse that have the potential to harm others. This email abuse is commonly known as spam, which contains advertisements, phishing scams, and even malware. This study purpose to know the classification of email spam with ham using the KNN method as an effort to reduce the amount of spam. KNN can classify spam or ham in an email by checking it using a different K value approach. The results of the classification evaluation using confusion matrix resulted in the KNN method with a value of K = 1 having the highest accuracy value of 91.4%. From the results of the study, it is known that the optimization of the K value in KNN using frequency distribution clustering can produce high accuracy of 100%, while k-means clustering produces an accuracy of 99%. So based on the results of the existing accuracy values, the frequency distribution clustering and k-means clustering can be used to optimize the K-optimal value of the KNN in the classification of existing spam emails.

Towards a Standard for a Reliable Execution Environment for Security Protocols

2016 ◽  
Vol 2 (1) ◽  
pp. 78
Author(s):  
Mahalingam Ramkumar
Keyword(s):  
Information Systems ◽  
Full Advantage ◽  
Real World ◽  
Security Protocols ◽  
Low Complexity ◽  
High Integrity ◽  
Execution Environment ◽  
World Information ◽  
Digital Assets ◽  
Attack Models

Approaches for securing digital assets of information systems can be classified as active approaches based on attack models, and passive approaches based on system-models. Passive approaches are inherently superior to active ones. However, taking full advantage of passive approaches calls for a rigorous standard for a low-complexity-high-integrity execution environment for security protocols. We sketch broad outlines of mirror network (MN) modules, as a candidate for such a standard. Their utility in assuring real-world information systems is illustrated with examples.

A Clinical Decision Support System for Assessing the Risk of Cardiovascular Diseases in Diabetic Hemodialysis Patients

2020 ◽  
Vol 16 (3) ◽  
pp. 262-269
Author(s):  
Tahere Talebi Azad Boni ◽  
Haleh Ayatollahi ◽  
Mostafa Langarizadeh
Keyword(s):  
Decision Support ◽  
Cardiovascular Diseases ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Diabetic Patients ◽  
K Value ◽  
Care Plans

Background: One of the greatest challenges in the field of medicine is the increasing burden of chronic diseases, such as diabetes. Diabetes may cause several complications, such as kidney failure which is followed by hemodialysis and an increasing risk of cardiovascular diseases. Objective: The purpose of this research was to develop a clinical decision support system for assessing the risk of cardiovascular diseases in diabetic patients undergoing hemodialysis by using a fuzzy logic approach. Methods: This study was conducted in 2018. Initially, the views of physicians on the importance of assessment parameters were determined by using a questionnaire. The face and content validity of the questionnaire was approved by the experts in the field of medicine. The reliability of the questionnaire was calculated by using the test-retest method (r = 0.89). This system was designed and implemented by using MATLAB software. Then, it was evaluated by using the medical records of diabetic patients undergoing hemodialysis (n=208). Results: According to the physicians' point of view, the most important parameters for assessing the risk of cardiovascular diseases were glomerular filtration, duration of diabetes, age, blood pressure, type of diabetes, body mass index, smoking, and C reactive protein. The system was designed and the evaluation results showed that the values of sensitivity, accuracy, and validity were 85%, 92% and 90%, respectively. The K-value was 0.62. Conclusion: The results of the system were largely similar to the patients’ records and showed that the designed system can be used to help physicians to assess the risk of cardiovascular diseases and to improve the quality of care services for diabetic patients undergoing hemodialysis. By predicting the risk of the disease and classifying patients in different risk groups, it is possible to provide them with better care plans.

scholarly journals Emissions of an agricultural engine using blends of diesel and hydrous ethanol

2019 ◽  
Vol 40 (1) ◽  
pp. 7
Author(s):  
Marcelo Silveira de Farias ◽  
José Fernando Schlosser ◽  
Javier Solis Estrada ◽  
Gismael Francisco Perin ◽  
Alfran Tellechea Martini
Keyword(s):  
Internal Combustion Engines ◽  
Fossil Fuels ◽  
Renewable Energy Sources ◽  
Standard Procedure ◽  
Diesel Oil ◽  
K Value ◽  
Operating Modes ◽  
Diesel Cycle ◽  
Reduce Emissions ◽  
Hydrous Ethanol

The growing global demand of energy, the decrease of petroleum reserves and the current of environmental contamination problems, make it imperative to study renewable energy sources for use in internal combustion engines, in order to decrease the dependence on fossil fuels and reduce emissions of pollutant gases. This study aimed to evaluate the emissions of a diesel-cycle engine of an agricultural tractor that uses diesel S500 (B5) mixed with 3, 6, 9, 12 and 15% of hydrous ethanol. It determined emissions of CO2 (ppm), NOx (ppm), and opacity (k value) of gases. A standard procedure was applied considering eight operating modes (M1, M2, M3, M4, M5, M6, M7, and M8) by breaking with an electric dynamometer in a laboratory. The experimental design was completely randomized, with 60 replicates and a 6 x 8 factorial design. Greater opacity and gas emissions were observed when the engine operated with 3% ethanol, while lower emissions occurred with 12 and 15%. With these fuels, the reduction of opacity, CO2, and NOx, in relation to diesel oil, was 24.49 and 26.53%, 4.96 and 5.15%, and 6.59 and 9.70%, respectively. In conclusion, the addition of 12 and 15% ethanol in diesel oil significantly reduces engine emissions.

Feature extraction method of pipeline signal based on parameter optimized vocational mode decomposition and exponential entropy

2021 ◽  
pp. 014233122110294
Author(s):  
Yina Zhou ◽  
Yong Zhang ◽  
Jingyi Lu ◽  
Fan Yang ◽  
Hongli Dong ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Working Conditions ◽  
Acoustic Signals ◽  
Normal Operation ◽  
Local Characteristic ◽  
Support Vector ◽  
K Value ◽  
Feature Vectors ◽  
Mode Decomposition ◽  
Exponential Entropy

Pipeline leakage is the main reason that affects normal operation of the pipeline. In this paper, a feature recognition method for pipeline acoustic signals based on vocational mode decomposition (VMD) and exponential entropy (EE) is investigated, which could extract the characteristics of pipeline signals and further accurately identify the pipeline acoustic signals under different working conditions. First, the VMD is used to decompose the collected acoustic signals into a number of mode components, during which process the optimal mode number (i.e., K-value) is determined by combining local characteristic scale decomposition (LCD) and correlation analysis methods. Then, the characteristic content of each mode component is analyzed with the help of the determined correlation coefficient (CC) threshold. If the correlation coefficient of a mode component is greater than the threshold, then the mode component is selected as the feature component. Subsequently, the EE values of the selected feature components are calculated to form the feature vectors corresponding to different kinds of pipeline signals. Finally, the feature vectors are input into support vector machine (SVM) to classify and recognize the different pipeline states. The experimental results demonstrate that the proposed method can identify the pipeline signals under different working conditions, and the recognition accuracy is up to [Formula: see text]. By analyzing and comparing with methods of EE-SVM, original data-SVM, VMD-singular spectrum entropy (SSE) and VMD-information entropy (IE), it is further verified that the proposed method is feasible and superior to the methods.

scholarly journals Deciphering the Disaggregation Mechanism of Amyloid Beta Aggregate by 4-(2-Hydroxyethyl)-1-Piperazinepropanesulfonic Acid Using Electrochemical Impedance Spectroscopy

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 788
Author(s):  
Hien T. Ngoc Le ◽  
Sungbo Cho
Keyword(s):  
Electrochemical Impedance Spectroscopy ◽  
Impedance Spectroscopy ◽  
Electrochemical Impedance ◽  
Specific Binding ◽  
Amyloid Β ◽  
Electrochemical Measurement ◽  
Charge Transfer Resistance ◽  
Chemical Agent ◽  
Transfer Resistance ◽  
K Value

Aggregation of amyloid-β (aβ) peptides into toxic oligomers, fibrils, and plaques is central in the molecular pathogenesis of Alzheimer’s disease (AD) and is the primary focus of AD diagnostics. Disaggregation or elimination of toxic aβ aggregates in patients is important for delaying the progression of neurodegenerative disorders in AD. Recently, 4-(2-hydroxyethyl)-1-piperazinepropanesulfonic acid (EPPS) was introduced as a chemical agent that binds with toxic aβ aggregates and transforms them into monomers to reduce the negative effects of aβ aggregates in the brain. However, the mechanism of aβ disaggregation by EPPS has not yet been completely clarified. In this study, an electrochemical impedimetric immunosensor for aβ diagnostics was developed by immobilizing a specific anti-amyloid-β (aβ) antibody onto a self-assembled monolayer functionalized with a new interdigitated chain-shaped electrode (anti-aβ/SAM/ICE). To investigate the ability of EPPS in recognizing AD by extricating aβ aggregation, commercially available aβ aggregates (aβagg) were used. Electrochemical impedance spectroscopy was used to probe the changes in charge transfer resistance (Rct) of the immunosensor after the specific binding of biosensor with aβagg. The subsequent incubation of the aβagg complex with a specific concentration of EPPS at different time intervals divulged AD progression. The decline in the Rct of the immunosensor started at 10 min of EPPS incubation and continued to decrease gradually from 20 min, indicating that the accumulation of aβagg on the surface of the anti-aβ/SAM/ICE sensor has been extricated. Here, the kinetic disaggregation rate k value of aβagg was found to be 0.038. This innovative study using electrochemical measurement to investigate the mechanism of aβagg disaggregation by EPPS could provide a new perspective in monitoring the disaggregation periods of aβagg from oligomeric to monomeric form, and then support for the prediction and handling AD symptoms at different stages after treatment by a drug, EPPS.

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