CONFERENCE ON RECENT RESEARCH IN SCIENCE AND TECHNOLOGY | Year:2020 | دوره:19 |Papers Count:11

ONLINE P2P LENDING PLATFORM, IN WHICH A GROUP OF USERS ACTS AS LENDERS TO PROVIDE RESOURCES, AND ANOTHER GROUP AS A BORROWER OF THESE RESOURCES TO SET UP AND DEVELOP BUSINESS WORK, CAR BUYING, MARRIAGE, HOME IMPROVEMENT, ETC. VALIDATION OF PEOPLE IN THIS SYSTEM IS DESIGNED BASED ON THEBLOCKCHAIN TECHNOLOGY (THE CHAIN OF BLOCKS).

IN THIS PAPER, A NOVEL METHOD FOR PRINTED FARSI DOCUMENTS RETRIEVAL IS PROPOSED. HERE, USED OF A HIERARCHICAL STRUCTURE OF RBF NEURAL NETWORK. THE FEATURE VECTOR IS PROFILES IN FOUR STANDARD DIRECTIONS. SUB LETTERS ARE DIVIDED INTO FOUR CATEGORIES, FIRST, MIDDLE, END AND SINGLE ACCORDING TO THE POSITION OF THE SUB-LETTERS IN SUB WORDS. ONE RBF NN IS TRAINED FOR ANY CATEGORY. THE OUTPUT OF THE NEURAL NETWORK IS PROPORTIONAL TO THE NUMBER OF SUB-LETTERS OF EACH CATEGORY, AS WELL AS THE NUMBER OF MERGING SUB-LETTERS WITH HIGH INTERFERENCE. IN THE NEXT STEP, A NEURAL NETWORK IS TRAINED FOR EACH SUBGROUP THAT HAS BEEN MERGED. TO EVALUATE THE SYSTEM, 50 DOCUMENTS HAVE BEEN SCANNED AND AFTER THE PREPROCESSING STAGES, THE LINES AND WORDS HAVE BEEN EXTRACTED. THEN THE BODY OF THE WORDS IS EXTRACTED AND ARE SEPARATED TO SUB-LETTERS. PERCENT OF CORRECT SUB-LETTER RECOGNITION IS 99%.

TODAY, PHYSICIANS MOSTLY DIAGNOSE DIABETES BY RELYING ON THEIR EXPERIENCES AND KNOWLEDGE AND COMPLICATED AND TIME-CONSUMING EXPERIMENTS. NONETHELESS, HUMAN ERRORS ARE INEVITABLE. A HYBRID METHOD IS PRESENTED IN THE CURRENT STUDY TO DIAGNOSE DIABETES BECAUSE ONE OF THE MAIN PROBLEMS REGARDING THIS DISEASE IS LACK OF TIMELY AND CORRECT DIAGNOSIS. THE PRESENT STUDY AIMS AT PRESENTING A MECHANISM TO IMPROVE THE ACCURACY OF DIABETES DIAGNOSIS. THIS MECHANISM IS CONDUCTED BASED ON THE PID DATASET ANALYSIS USING DATA MINING SYSTEMS. ACCORDING TO STUDIES, IT IS PROVED THAT HYBRID LEARNING SYSTEMS ARE MORE ACCURATE AND OUTPERFORM SIMPLE SYSTEMS. THEREFORE, A HYBRID DATA MINING SYSTEM BASED ON DEMPSTER-SHAFER WAS PRESENTED IN THIS STUDY TO DIAGNOSE DIABETES, IN WHICH PROPERTY SELECTION IS DONE BASED ON PEARSON’ S CORRELATION AND USING THE GENETIC ALGORITHM. COMMON CLASSIFICATION METHODS SUCH AS THE NEURAL NETWORK, DECISION TREE AND SUPPORT VECTOR MACHINE WERE USED AS BASIC LEARNING SYSTEMS AND DEMPSTER-SHAFER THEORY WAS USED TO COMBINE THE CLASSIFICATIONS. ACCORDING TO THE EXPERIMENTS, THE PROPOSED METHOD OUTPERFORMED THE BASIC SYSTEMS AND DIAGNOSED DIABETIC PATIENTS AT A HIGHER ACCURACY. THE DATASET ACCURACY REACHED 89. 58% FROM 87. 24%.

THE AIM OF THIS RESEARCH IS TO DETERMINE THE RESIDUAL STRESSES DUE TO T WELDING AND COMPARING IT WITH THE ONE-PASS CONDITION. THE RESIDUAL STRESSES HAVE GREAT IMPORTANCE IN COMPARING TOPICS. BECAUSE THE WELDING SPEED AFFECTS THESE STRESSES, IN THIS PAPER, THE SIMULATION PROCESS OF WELDING ON THE STRUCTURAL STEEL IN VARIOUS ADVANCING SPEEDS HAS BEEN INVESTIGATED USING THE THERMAL MODEL IN ANSYS WORKBENCH SOFTWARE. THIS PROCESS IS SIMULATED FOR THE WELDING PROCESS OF THE CIRCULAR CROSS-SECTION OF A PIPE. THEN, THE NUMBER OF STRESSES AND HEAT GENERATED ON THE WORKPIECE DUE TO HEAT TREATMENT WAS EXTRACTED AND THE RESULTS WERE PRESENTED IN THE FORMAT OF TABLES AND FIGURES. THE RESULTS SHOWED THAT THE RESIDUAL STRESSES DECREASED AS THE WELDING SPEED INCREASED.

THE STRUCTURE OF THE BRAIN TISSUES COULD BE WELL STUDIED BY THE BRAIN MAGNETIC RESONANCE IMAGES (MRI). ONE OF THE AAPPLICATION OF MAGNETIC RESONANCE IMAGES OF THE BRAIN IS THE DIAGNOSIS OF BRAIN TUMORS BY SEGMENTATION AND CLUSTERING TECHNIQUES. ACCURATE DIAGNOSIS OF BRAIN TUMORS IS CONSIDERED TO BE ONE OF THE MAIN CHALLENGES IN SEGMENTATION TECHNIQUES. DUE TO POOR SENSITIVITY TO NOISE FUZZY CLUSTERING ALGORITHM IS ONE OF THE IMPORTANT METHODS SEGMENTATION OF BRAIN TUMORS. THE PRECISE SELECTION CLUSTER CENTERS IN FUZZY CLUSTERING ALGORITHM BY INITIALIZED THE MEMBERSHIP MATRIX KNOWN AS THE MAIN RESEARCH CHALLENGES BECAUSE THE ACCURACY OF THIS ALGORITHM IN IMAGES SEGMENTATION DEPENDS ON THE OPTIMAL MEMBERSHIP MATRIX. IN THIS STUDY, FOR MORE OPTIMAL SELECTION OF MEMBERSHIP MATRIX IN THE FUZZY CLUSTERING ALGORITHM, WATER WAVES OPTIMIZATION (WWO) ALGORITHM IS USED. OUR IMPLEMENTATION RESULTS ON A SET OF MAGNETIC RESONANCE IMAGES OF THE BRAIN IN THE BRATS DATA SET SHOWS THAT THE AVERAGE SET F MEASURES SUCH AS JACCARD INDEX, SIMILARITY INDEX, ACCURACY, SENSITIVITY AND SPECIFICITY IN THE PROPOSED METHOD ARE %25. 39, 235229, 2%5299, %25. 39 AND 2952. 9. THE SIMILARITY OF OUR PROPOSED IS BETTER THAN APPROACH TO SEGMENTATION PROCEDURES SUCH FCM, KFCM AND GFCM BECAUSE MEMBERSHIP MATRIX IS CALCULATED BY THE WATER WAVES OPTIMIZATION ALGORITHM AND THUS CLUSTER CENTERS ARE SELECTED MORE ACCURATE IN PROPOSED METHOD.

ENTERPRISES TODAY ARE DRIVEN BY DATA, OR, TO BE MORE PRECISE, INFORMATION THAT IS GLEANED FROM DATA. IT REDUCES UNCERTAINTY, AND IT TURNS DECISION-MAKING FROM AN ART TO A SCIENCE. RAW DATA IS INCONSISTENT, INCOMPLETE, OUTDATED, UNFORMATTED, AND RIDDLED WITH ERRORS. THIS IS WHERE YOU NEED DATA INTEGRATION TO UNIFY AND MASSAGE THE DATA, DATA WAREHOUSING TO STORE AND STAGE IT, AND BI TO PRESENT IT TO DECISION-MAKERS IN AN UNDERSTANDABLE WAY. IT CAN BE A LONG AND COMPLICATED PROCESS. FIRMS MUST INVEST HEAVILY IN BUILDING A NEXTGENERATION CUSTOMER DATA MANAGEMENT CAPABILITY TO GROW REVENUE AND PROFITS IN THE AGE OF THE CUSTOMER. THEREFORE, IN THIS ARTICLE, WE FOCUS ON THE IMPORTANCE OF THE DATA ANALYSIS SCIENCE AND THE ROLE OF BUSINESS INTELLIGENCE IN ORGANIZATIONAL PROCESSES.

LACTIC ACID BACTERIA, OF WHICH HALF OF THE FINAL PRODUCTS OF GLUCOSE FERMENTATION ARE LACTIC ACID, ARE NAMED LACTOBACILLUS. THESE BACTERIA ARE THE MAIN COMPONENTS OF THE MICROBIAL FLORA OF FERMENTED DAIRY PRODUCTS. IN THIS STUDY, THE ENZYMATIC ACTIVITY OF PROBIOTIC BACTERIA BACILLUS SUBTILIS AND LACTOBACILLUS CAESI WAS STUDIED. BACILLUS SUBTILIS BACTERIA WERE CULTURED ON BROTH NUTRIENT CULTURE MEDIA, MRS BROTH, MRS BROTH + GLUCOSE, MRS BROTH + LACTOSE, LACTOSE BROTH AND TSB. THE RESULTS OF THIS STUDY INDICATE THAT BACILLUS SUBTILIS BACTERIA IS HIGHLY CAPABLE OF PRODUCING α-AMYLASE ENZYME. THE SPECIFIC CULTURE MEDIUM OF BACILLUS SUBTILIIS IS TRYPTIC BRACHYCEA AND TRYBETHIC AGAR. HOWEVER, THIS BACTERIUM HAS GROWN WELL IN MOST OF THE CULTURE MEDIA STUDIED. THE CULTURE MEDIUM IS SPECIFIC FOR LACTOBACILLUS CASEI MRS, AND THE BEST GROWTH OF THIS BACTERIUM WAS OBSERVED IN THE MRS MEDIUM CONTAINING LACTOSE GLUCOSE. BY APPLYING STRESS CONDITIONS, THE SECRETION OF THE ENZYMES OF THIS BACTERIUM INCREASED IN THE MEDIUM. LACTOBACILLUS CASEI DID NOT SHOW ANY GROWTH ON THE MCCANKY AGAR CULTURE MEDIA.

TODAY, ALL OVER THE WORLD, DUE TO MAJOR PROBLEMS SUCH AS ENVIRONMENTAL POLLUTION DUE TO THE UNTAPPED USE OF FOSSIL FUELS, AS WELL AS THE ENDING OF NONRENEWABLE ENERGY SOURCES, THE NEED TO USE SCIENCE AND TECHNOLOGY AND SUSTAINABLE ENERGY IN VARIOUS FIELDS PARTICULARLY IN THE BUILDING INDUSTRY, WHICH HAS TAKEN A LARGE SHARE OF ENERGY CONSUMPTION. THEREFORE, IN THIS RESEARCH, WITH THE AIM OF STUDYING THE INTELLIGIBILITY OF THE BUILDING, FIRSTLY, IT WILL EXPLAIN THE MATERIALS AND STRUCTURES OF THE SMART, AND THEN EXAMINE HOW MUCH AN INTELLIGENT BUILDING CAN BE EFFECTIVE IN SAVING ENERGY. THE RESULT OF THE RESEARCH SUGGESTS THAT THE USE OF INTELLIGENT MATERIALS AND, IN FACT, INTELLIGENT BUILDING CAN HELP TO INCREASE THE COMFORT OF USERS AND REDUCE ENERGY CONSUMPTION IN RESIDENTIAL AND OFFICE BUILDINGS.

IN THIS PAPER WE SUGGEST USING A WIRELESS SENSOR NETWORK AND USING FUZZY LOGIC A SYSTEM FOR INTELLIGENT DETECTION OF MOUNTAIN LANDSLIDES. THIS SYSTEM IS IN HIGH-RISK ROUTES WHICH THE CONSTANT MONITORING OF THESE AREAS IN THE EVENT OF A FALL OF IT AND IT DECLARES THIS DANGER AT A PROPER DISTANCE FROM THE FALL. IN THIS PAPER USING ELECTROMAGNETIC SENSORS WE CAN EASILY MAKE HIS DIAGNOSIS AND SAVE MANY PEOPLE FROM COLLISION WITH THE LOSS. THE IDEA THAT CAN BE EASILY IMPLEMENTED CAN SAVE MANY PEOPLE'S LIVE IN PARTICULAR CIRCUMSTANCES.

SOCIAL NETWORKS HAVE ALREADY GROWN DRAMATICALLY IN VARIOUS SCIENTIFIC FIELDS. THE FIELDS CONSIST OF NETWORK ANALYSIS HAVE INTERESTED MANY RESEARCHERS TO STUDYING NETWORK STRUCTURES. COMMUNITY-BASED STRUCTURE IS ONE OF THE MOST IMPORTANT CHARACTERISTICS OF COMPLEX NETWORKS AND IS A BASIC CONCEPT IN THE DISCOVERY AND UNDERSTANDING OF NETWORKS. IN THE REAL WORLD, TOPOLOGICAL INFORMATION LONELY IS OFTEN INADEQUATE TO FIND OUT THE EXACT STRUCTURE OF THE COMMUNITY. THE POTENTIAL PREVIOUS INFORMATION CAN BE DERIVED FROM THE KNOWLEDGE AVAILABLE IN THE DOMAIN OF MANY APPLICATIONS. THEREFORE, HOW TO IMPROVE THE PERFORMANCE OF COMMUNITY DETECTION BY COMBINING TOPOLOGY WITH PREVIOUS INFORMATION IS A CHALLENGING PROBLEM. IN THIS RESEARCH, AN INTEGRATED SEMI-SUPERVISED FRAMEWORK FOR INTEGRATING A NETWORK TOPOLOGY WITH ITS PREVIOUS INFORMATION IS PROVIDED FOR THE COMMUNITY DETECTION. IF PREVIOUS INFORMATION INDICATES THAT SOME OF THE NETWORK MEMBERS BELONG TO A PARTICULAR COMMUNITY, THEN ADDING THE TERM "GRAPH REGULATION" CAN IMPROVE DETECTION OPERATIONS BY REDUCING THE ASYMMETRY OF THE HIDDEN SPACE OF THESE NODES. THE EXPERIMENTS PERFORMED ON THE DATA SET BELONGING TO THE STUDIED NETWORKS SHOW THAT THE PROPOSED METHOD INCREASES THE ACCURACY OF DETECTION OF COMMUNITY, ESPECIALLY IN NETWORKS WITH UNSPECIFIED STRUCTURES.

BARIUM TITANATE IS ONE OF THE MOST IMPORTANT PIEZOELECTRIC MATERIALS USED IN MICROELECTRONIC DEVICES SUCH AS ULTRASONIC DEVICES, SENSORS, TRANSDUCERS, ETC. THIS IS DUE TO THE HIGH DIELECTRIC CONSTANT AND LOW DIELECTRIC LOSSES OF THIS MATERIAL. THESE TYPES OF MATERIALS HAVE A PEROVSKITE CRYSTAL SYSTEM. IN THIS STUDY, BARIUM TITANATE WAS SYNTHESIZED BY WET CHEMISTRY AND ITS POWDER DOPED BY HOLMIUM OXIDE AND MANGANESE OXIDE. THE EFFECTS OF THESE ADDITIVES ON THE SECONDARY PHASES FORMED, SHAPE, AND MORPHOLOGY OF PARTICLES AND DIELECTRIC PROPERTIES OF THE SAMPLES ARE DISCUSSED. THE MICROSTRUCTURE OF THE SAMPLES WAS INVESTIGATED BY FIELD EMISSION SCANNING ELECTRON MICROSCOPY (FESEM). X-RAY DIFFRACTION ANALYSIS WAS USED TO INVESTIGATE THE FORMATION OF PHASES. THE SURFACE OF THE SPECIMENS WAS GOLD-COATED TO MEASURE THEIR DIELECTRIC PROPERTIES BY PRECISION LCR METER. THE DIELECTRIC PROPERTIES DEPEND ON THE FREQUENCY AND SINTERING METHOD AND THE FREQUENCY VARIATIONS AFFECT THE DIELECTRIC CONSTANT AND DIELECTRIC LOSSES. MICROWAVE SAMPLES HAD BETTER DIELECTRIC PROPERTIES THAN MICROWAVE SAMPLES, AND THE PARTICLE SHAPES DIFFERED IN THE TWO SINTERING METHODS. THIS IS DUE TO DIFFERENCES IN THE HEATING MECHANISM.