Perbandingan Performansi Model pada Algoritma K-NN terhadap Klasifikasi Berita Fakta Hoaks Tentang Covid-19

During Covid-19 pandemic, there was various hoax news about Covid-19. There are truth-clarification platforms for hoax news about Covid-19 such as Jala Hoax and Saber Hoax which categorize into misinformation and disinformation. Classification of supervised learning methods is applied to carry out learning from fact labels. Dataset is taken from Jala Hoax and Saber Hoax as many as 559 data which are made into Class 1 (Misleading Content, Satire/Parody, False Connection), Class 2 (False Context, Imposter Content), Class 3 (Fabricated and Manipulated Content). K-Nearest Neighbor (K-NN) is used to classify categories of misinformation and disinformation. Dissimilarity measure Jaccard Distance is compared with Euclidean, Manhattan, and Minkowski and uses k-value variance in the K-NN to determine the performance comparison results for each test. Results of Jaccard Distance at the value of k = 4 get a higher value than other model with an accuracy 0.696, precision 0.710, recall 0.572, and F1-Score. Maximum results tend to be on label of the most data class in Class 1 (Misleading Content, Satire or Parody, False Connection) with a total of 58 correct data from 61 test data.

A Review Paper on Cryptography and Network Security

With the explosively growing internet that has been merging with our lives for the past few decades, data and network security has been of utmost importance as society moves towards the age of digital information. As the number of users connected to the web increases, the threat faced by the network because of attackers also increases. Cryptography, the science of information security derived from the inherent needs of humans to converse and share information or communicate selectively at times, has the primary function of sending correct data over the network without any undesirable modifications. In cryptography, the original message is masked or encrypted by the sender and has to be decoded or decrypted by the receiver using a predefined set of algorithms decided before the commencement of the data transmission. Thereby, successfully avoiding redundant people from accessing or understanding the message as it is converted to content unreadable by the human eye.

The Influence of Filters on EEG-ERP Testing: Analysis of Motor Cortex in Healthy Subjects

The raw EEG signal is always contaminated with many different artifacts, such as muscle movements (electromyographic artifacts), eye blinking (electrooculographic artifacts) or power line disturbances. All artifacts must be removed for correct data interpretation. However, various noise reduction methods significantly influence the final shape of the EEG signal and thus its characteristic values, latency and amplitude. There are several types of filters to eliminate noise early in the processing of EEG data. However, there is no gold standard for their use. This article aims to verify and compare the influence of four various filters (FIR, IIR, FFT, NOTCH) on the latency and amplitude of the EEG signal. By presenting a comparison of selected filters, the authors intend to raise awareness among researchers as regards the effects of known filters on latency and amplitude in a selected area—the sensorimotor area.

Best Practices for Technical Reproducibility Assessment of Multiplex Immunofluorescence

Multiplex immunofluorescence (mIF) tyramide signal amplification is a new and useful tool for the study of cancer that combines the staining of multiple markers in a single slide. Several technical requirements are important to performing high-quality staining and analysis and to obtaining high internal and external reproducibility of the results. This review manuscript aimed to describe the mIF panel workflow and discuss the challenges and solutions for ensuring that mIF panels have the highest reproducibility possible. Although this platform has shown high flexibility in cancer studies, it presents several challenges in pre-analytic, analytic, and post-analytic evaluation, as well as with external comparisons. Adequate antibody selection, antibody optimization and validation, panel design, staining optimization and validation, analysis strategies, and correct data generation are important for reproducibility and to minimize or identify possible issues during the mIF staining process that sometimes are not completely under our control, such as the tissue fixation process, storage, and cutting procedures.

Improved Outsourced Provable Data Possession for Secure Cloud Storage

With the advent of data outsourcing, how to efficiently verify the integrity of data stored at an untrusted cloud service provider (CSP) has become a significant problem in cloud storage. In 2019, Guo et al. proposed an outsourced dynamic provable data possession scheme with batch update for secure cloud storage. Although their scheme is very novel, we find that their proposal is not secure in this paper. The malicious cloud server has ability to forge the authentication labels, and thus it can forge or delete the user’s data but still provide a correct data possession proof. Based on the original protocol, we proposed an improved one for the auditing scheme, and our new protocol is effective yet resistant to attacks.

Own experience of mri T2 and ct perfusion of the brain, how to avoid «failures»

Introduction. To reduce the number of cerebral perfusion studies, the interpretation of which is not possible or can be performed with errors, we retrospectively analyzed cerebral perfusion studies for three years, analyzed the identified errors at the stage of data collection and the stage of study interpretation.Aims and objectives: to analyze and divide into groups the reasons that led to limitations or impossibility to assess perfusion during interpretation of the obtained data, to develop an algorithm of actions to reduce the number of uninterpreted studies.Materials and Methods. The study retrospectively evaluated 275 CT and MRI brain perfusion studies performed between 2017 and 2019 on 1.5 T MR and 32-slice CT scans.Results. The result of this study was a better understanding of the causes of the most common errors in perfusion studies. Analysis of the causes allowed us to identify factors that affect the performance of the study and the interpretation of the data obtained. Discussion. In order to perform a quality perfusion study, given the many factors affecting the interpretation of the data obtained, a number of conditions on the planning and execution of the study, as well as on the evaluation of the data obtained, must be followed. Conclusions. Understanding the reasons that lead to limitations or inability to evaluate MRI and CT perfusion studies, adhering to guidelines for planning and evaluating studies allows for correct data and avoids obtaining uninformative studies or studies whose interpretation is limited.

Bending Stiffness of Hybrid Wood-Metal Composite Beams: An Experimentally Validated Numerical Model

This paper presents an experimentally validated model for the computational analysis of metal-reinforced wooden composites. The model can be used in both research and in industry to effectively estimate how much a certain composite design improves the bending stiffness and strength of a hybrid metal-reinforced wooden component. A model based on computer simulations allows the prediction and analysis of the mechanical behaviour of a hybrid composite material consisting of several interconnected components made of different base materials. The model for different boundary conditions and parameters provides the correct data on stiffness, especially bending, and the associated maximum displacements. It allows for a variation of the mechanical and geometrical properties, and makes it possible to observe the initiation of irreversible change in the window-frame member. The model enables parametrical simulations to find the optimum layout of reinforcements in the window-frame member, as well as to make estimations of the maximum performance of certain designs.

THEORETICAL ANALYSIS OF MEMBRANE AIR DEHUMIDIFICATION IN AIR CONDITIONING SYSTEMS

The paper presents a simulation of the process of removing moisture from the air in air conditioning systems using construction vapor-permeable membranes. The existing classical physical and mathematical models are considered and analyzed. Based on the analysis of classical models, a schematic and corresponding theoretical mathematical model of air dehumidification with a semipermeable building membrane with certain characteristics for possibilities of use in air conditioning systems is developed and presented. The data of calculations of moisture release from air for the developed model are given. As a result of analytical researches the correct data for possible use in air conditioning systems are received. Key words: air conditioning systems, air dehumidification, semipermeable membrane, permeability, membrane air dehumidification, convective flow, diffusion flow, moisture permeability.

Classification of Diseases of The Urinary System using an Expert System

Purpose – Develop and use an Expert System (ES) to classify diseases of the urinary system. Design/methodology/approach – Computational experiments were divided into three phases, as described: Phase A: Database selection: We searched for a database that contains information on diseases of the urinary system. Phase B: Development and Implementation of the Expert System: Rules and variables were planned for the correct data manipulation, and the Expert System was created by implementing the rules and variables. Phase C: Validation of the Expert System: Expert System validated by specialists. Findings – The Expert System was validated by a general practitioner and, as such, was successful while carrying out the tests and results. In conclusion, the Expert System was generated to classify two diseases (Cystitis and Nephritis) of the urinary system. This was validated by a general practitioner who confirmed the accuracy of the information within the system developed and aimed of assisting the field of medicine for a specific organ. Originality/value – The development of the present work has made it possible to assist the specific diagnosis of two diseases of the urinary system. With the assistance of the Specialist System, professionals can be more confident when diagnosing diseases of the urinary system in patients. Keywords - Urinary System; Expert Systems; Artificial Intelligence; Support to The Diagnosis.

Corrigendum to “Molecular Simulation of the Surface Tension of 33 Multi-site Models for Real Fluids” [J. Mol. Liq. 235 (2017) 126–134]

The authors regret that at typesetting stage, additional ‘1’ digits were mistakenly introduced into the tables, leading to an incorrect reproduction of numerical data. Corrected versions of the tables are included here; the affected values, which in the published article [1] erroneously contained an additional leading digit, are highlighted in bold typeface. The text of the article, and the conclusions formulated therein, were based on the correct data and do not require any modification. The authors would like to apologize for any inconvenience caused.