INTERNATIONAL CONFERENCE ON WEB RESEARCH | Year:2018 | دوره:4 |Papers Count:60

IN THE MANAGEMENT OF LARGE ORGANIZATIONS AND COMPLEX SYSTEMS, PRESENCE OF A STRUCTURE IN REGARD WITH USEFUL PATTERN RECOGNITION CAN REDUCE MARGIN OF ERROR FOR DECISION-MAKING. IN SOME GROUNDS, IT PROVIDES THE CONTEXT TO PREDICT EFFECTIVELY WHICH MAY LEAD THE EFFICIENCY OF THE ORGANIZATION TO INCREASE. MOREOVER, IT OFFERS MORE IDEAL APPLICATION BY WHICH IDENTIFYING BOTTLENECK OR LOSS AND DAMAGE AREAS CAN BE PROVIDED. BY CREATING A SEMI-AUTOMATIC STRATEGY, PLANNING A FRAMEWORK FOR SEMANTIC INFERENCE BASED ON FUZZY COGNITIVE MAP WITHIN PATTERN CLASSIFICATION (PROBLEMS) ISSUES IS NECESSITATED ACCORDING TO WHICH BEHAVIORS IN DIFFERENT PARTS OF ORGANIZATIONS COULD BE ASSESSED AND SUPERVISED BY OVERCOMING THE COMPLEXITY OF DYNAMIC ENVIRONMENTS. THE OBTAINED PATTERN MUST BE ACTUAL SO AS THE DECISIONS MADE TO PREVENT OR SOLVE PROBLEMS ACT WITH BETTER MORE PRACTICAL RESULTS. THE MANAGEMENT CAN OBSERVE THE EXTRACTED BEHAVIORAL PATTERNS UTILIZING THE STRUCTURE VIA DATA-BY IN THE SECTOR IN ORGANIZATION REVIEW AS WELL AS STRATEGIC CHANGES, BASED ON WHICH AN ISSUE MAY BE DECIDED. COMPARING THE RECOMMENDED ISSUE WITH THE SAMPLES IN THE OBTAINED PATTERNS CAN ANTICIPATE ITS PROFITABILITY AND ACCEPT OR DECLINE THE OPTION.

THIS RESEARCH HAS SOLVED THE CHALLENGE OF EXECUTING CYBER MANOEUVRES BY MODELLING AND SIMULATING CYBER BATTLEFIELD. IN THIS MODEL BY GATHER DETAIL DATA OF CYBERSPACE ELEMENTS, INCLUDING KNOWLEDGE REPOSITORY OF VULNERABILITY, TANGIBLE AND INTANGIBLE ELEMENTS OF CYBERSPACE AND THE RELATIONSHIPS BETWEEN THEM, CAN PROVIDE AND EXECUTE CYBER MANOEUVRES, PENETRATION TESTING, CYBER-ATTACKS INJECTION, ATTACK TRACKING, VISUALIZATION, CYBER-ATTACKS IMPACT ASSESSMENT AND RISK ASSESSMENT. THE PURPOSE IS PRESENTING CYBER ENVIRONMENT DEFENCE TOOLS BASED ON SITUATION AWARENESS MODELS, AS IT LEADS TO TRUE AND TIMELY DECISION MAKING AGAINST CYBER-ATTACKS. THIS RESEARCH PROVIDES A MODEL AND TOOL FOR IDENTIFY THE RISKS IN THE NETWORK AND HELPING TO PRIORITIZE ACTIONS TO ELIMINATE THREATS.

WEB DOCUMENTS AND WEB PAGES ARE EXPANDING RAPIDLY. WEB SEARCH ENGINES AND WEB SERVICES USE DIFFERENT METHODS TO FIND WEB PAGES AND DOCUMENTS IN THE MASSIVE AMOUNT OF DOCUMENTS. HOWEVER, ORGANIZING AND ANALYZING A LARGE AMOUNT OF DATA IS CHALLENGING. THE PROBLEM WITH WEB PAGE RETRIEVAL IS THAT THE INFORMATION ON THE GLOBAL WEB IS IN DIFFERENT FORMATS AND FROM DIFFERENT SOURCES. THE ACCURACY OF DATA SELECTION IS ESSENTIAL AND THEIR COMPLIANCE WITH USER REQUESTS IS A CHALLENGE IN EXPLORING THE WEB. IN ORDER TO PROVIDE AN OPTIMAL SOLUTION FOR EXPLORING WEB DOCUMENTS AND ORGANIZING AND PROVIDING QUICK AND ACCURATE ACCESS TO STRUCTURED AND SEMI-STRUCTURED WEB DOCUMENTS AND WEB PAGES, A NEW APPROACH IS PROPOSED. THE PROPOSED METHOD IS BASED ON THE CLUSTERING AND WEB DOCUMENT FUZZATION AND THE SEMANTIC AND STRUCTURE OF WEB PAGES. IN THE PROPOSED METHOD FOR THE REDUCTION OF DIMENSION OR FEATURES, THE MAPPING OF ATTRIBUTES TO SEMANTIC DOMAINS IS PROPOSED. THE RESULTS OF THE IMPLEMENTATION OF THE PROPOSED METHOD IN PYTHON AND MATLAB SOFTWARE SHOW THAT THE PROPOSED METHOD IN CATEGORIZING AND ORGANIZING WEB DOCUMENTS IS APPROPRIATE FOR THE QUALITY OF CLUSTERS AND THEIR DENSITY, AND IN THE TERMS OF THE DAVIES BOULDIN AND SILHOUETTE INDEX, THEY HAVE SUITABLE VALUES.

IN RECENT YEARS, SOCIAL NETWORKS HAVE BECOME POPULAR AMONG INTERNET USERS, AND VARIOUS STUDIES HAVE BEEN PERFORMED ON ANALYSIS OF SUCH NETWORKS. ONE OF THE IMPORTANT ISSUES IN ANALYZING SOCIAL NETWORKS IS INFORMATION DIFFUSION ANALYSIS. IN THIS CONTEXT, USERS' BEHAVIOR IS ASSUMED TO BE INFLUENCED BY OTHER SOCIAL NETWORK USERS. SEVERAL MODELS HAVE BEEN DESIGNED TO SIMULATE AND ANALYZE HOW INFORMATION IS DISSEMINATED IN SOCIAL NETWORKS. IN THIS PAPER, WE STUDY THE PROBLEM OF LEARNING THE DIFFUSION PROBABILITIES FOR THE INDEPENDENT CASCADE MODEL. WE FIRST OUTLINE THE IMPORTANCE OF THE SUBJECT, AND THEN WE PROPOSE A METHOD TO ESTIMATE DIFFUSION PROBABILITIES. IN THIS METHOD, WE ASSIGN A WEIGHT TO EACH INDIVIDUAL DIFFUSION SAMPLE OF EACH LINK IN THE NETWORK BASED ON ITS PARAMETERS. WE PROPOSE TWO WEIGHTING SCHEMES TO CONSIDER THE DIFFERENT EFFECTS OF DIFFUSION SAMPLES. THEN, WE EVALUATE OUR METHOD FOR LEARNING DIFFUSION PROBABILITIES WITH THE HELP OF SEVERAL DATASETS AND PRESENT THE RESULTS. ALSO, THE METHOD PRESENTED IN THIS PAPER IS COMPARED WITH OTHER METHODS IN TERMS OF MEAN ABSOLUTE ERROR AND TRAINING TIME.

WITH THE RAPID DEVELOPMENT OF THE WORLD WIDE WEB AND INCREASING THE VOLUME OF INFORMATION, WEB RESEARCH HAS BECOME AN IMPORTANT RESEARCH AREA. WEB MINING RESEARCH IS MAINLY CATEGORIZED INTO TWO TYPES OF WEB CONTENT MINING AND WEB USAGE MINING. AN IMPORTANT TOPIC IN WEB USAGE MINING IS THE CLUSTERING OF USERS IN OTHER WORDS, GROUPING THESE USERS INTO CLUSTERS BASED ON THEIR COMMON FEATURES. IN THIS PAPER, USING K-MEANS, KOHONEN, AND TWO-STEP METHODS, WE CLUSTERED THE USERS INTO GROUPS WITH SIMILAR CHARACTERISTICS AND USED THE PRINCIPAL COMPONENT ANALYSIS METHOD TO ENHANCE CLUSTERING QUALITY AND USE THE SILHOUETTE CRITERION TO ASSESS CLUSTERING QUALITY. AMONG THESE THREE METHODS, K-MEANS WITH TWO CLUSTERS HAD THE HIGHEST QUALITY AND THE DATA SET WAS CLUSTERED AND ANALYZED USING THIS METHOD. BY ANALYZING THE CLUSTERS, CAN GET A BETTER UNDERSTANDING OF THE USERS AND PROVIDE CUSTOM AND MORE CONVENIENT SERVICES FOR THEM.

DEVICES SUCH AS ROUTERS, SWITCHES OR FIREWALLS ARE THE MOST VITAL CONNECTIONS IN COMMUNICATION NETWORK AMONG PHYSICAL MACHINES IN A CLOUD COMPUTING ENVIRONMENT. IN THE ABSENCE OF SECURITY ON THE NETWORK, INTRUDERS ARE ALLOWED TO ACCESS THE EQUIPMENT AND CONFIGURE IT IN THE WAY THEY WANT TO. HENCE, A METHOD SUGGESTED TO DEAL WITH DENIAL-OF-SERVICE (DOS) ATTACKS IN THE CLOUD COMPUTING PLATFORM IS ONE OF THE ESSENTIAL AND MOST IMPORTANT SECURITY ISSUES IN THIS AREA. THIS STUDY TENDS TO PROVIDE A SMART METHOD BASED ON RANDOM FOREST ALGORITHM FOCUSING ON GENETIC ALGORITHMS FOR DETECTING DOS ATTACKS. THROUGH DIFFERENT NETWORK STREAMS, NETWORK STREAMS WHICH TRIGGER DOS AND DDOS ATTACKS ARE VERY IMPORTANT. THE MAIN IDEA OF THIS STUDY IS TO USE RANDOM FOREST ALGORITHM TO IDENTIFY DOS ATTACKS, WHICH IS THE MAIN REASON FOR OPTIMIZING THIS ALGORITHM USING GENETIC ALGORITHMS. IN THIS METHOD, AN OPTIMAL SUBSET OF THE SET OF FEATURES IS EXTRACTED USING GENETIC ALGORITHMS, AND THIS OPTIMAL SUBSET IS USED FOR RANDOM FOREST LEARNING. RESULTS OF THE EXPERIMENTS CARRIED OUT AND COMPARISON OF THE SUGGESTED METHOD WITH OTHER METHODS INDICATE PROPER ACCURACY AND OPERATION OF THE SUGGESTED METHOD.

WITH THE RAPID GROWTH OF THE WEB AND ITS USERS AROUND THE WORLD, THE AVAILABILITY AND USEFULNESS OF USERS’ COMMENTS HAVE INCREASED IN RECENT YEARS. SENTIMENT ANALYSIS TECHNIQUES ARE USED TO EXTRACT VALUABLE KNOWLEDGE FROM THIS INCREASING VOLUME OF TEXTUAL INFORMATION. THESE TECHNIQUES USUALLY DECOMPOSE EVERY COMMENT TO ITS SENTENCES, DETECT THEIR SENTIMENTS, AND AGGREGATE THESE SENTIMENTS TO CALCULATE THE OVERALL SENTIMENT BEING CONVEYED IN THE COMMENT. IN THIS STUDY, A NEW SENTENCE-LEVEL AGGREGATION MECHANISM BASED ON UNINORM OPERATORS IS PROPOSED FOR AGGREGATING SENTENCE-LEVEL SENTIMENT INTO AN OVERALL DOCUMENT-LEVEL OPINION. IN ORDER TO SHOW THE UTILITY OF THE PROPOSED METHOD, IT IS APPLIED TO POLARITY DETECTION AND SCORE PREDICTION PROBLEMS ON FOUR LARGE PERSIAN REVIEW DATASETS. IMPLEMENTATION RESULTS SHOW THAT THE PROPOSED METHOD, IN COMPARISON WITH DEMPSTER-SHAFER AGGREGATION METHOD, ACHIEVES A HIGHER PERFORMANCE IN POLARITY DETECTION WHILE THE DEMPSTER-SHAFER METHOD SLIGHTLY OUTPERFORMS THE PROPOSED METHOD IN SCORE PREDICTION TASK.

THIS ARTICLE AIMS TO ANALYSE THE MISINTERPRETATIONS OF AN EX-MUSLIMS’ POSTINGS ON FACEBOOK ABOUT ISLAM RELATED ISSUES IN MALAYSIA. THERE ARE FOUR SELECTED ISSUES: ISLAM’S ATTITUDE TOWARDS HOMOSEXUALS, PUNISHMENTS FOR APOSTATES, POLYGAMY, AND MUSLIM WOMEN’S HIJAB. FACEBOOK POSTINGS IN 2017 OF AN EX-MUSLIM, NAMED MARY, HAVE BEEN ANALYSED TO IDENTIFY THE MISINTERPRETATIONS WITH REGARDS TO THE SELECTED ISSUES. THE FINDING REVEALS THAT HOMOSEXUALITY IS CONTRARY WITH THE NATURE OF HUMAN AND ANIMAL BEINGS. IN THE ISSUE OF PUNISHMENT FOR APOSTATES, DEATH PENALTY IS STILL UNCLEAR AMONG LEGAL PRACTITIONERS IN MALAYSIA. ON THE OTHER HAND, IN POLYGAMY ISSUE, SHARIA LAW IN MALAYSIA HAS ALLOCATION TO PROTECT ABUSED WOMEN. MEANWHILE, IN THE CASE OF MUSLIM WOMEN’S HIJAB, THERE ARE SIGNIFICANT DIFFERENCES BETWEEN COMMON PRACTICE AND LAW. THE COMMON PRACTICE CANNOT BE MADE AS AN ARGUMENT FOR LAW.

DUE ITS CAPABILITIES, NOWADAYS, REMARKABLE AMOUNTS OF DATA ARE STORED IN THE XML FORMAT. IN FACT, XML IS KNOWN AS A WIDELY-ACCEPTED STANDARD FOR DATA STORING, MANAGEMENT AND EXCHANGE. IN THIS REGARD, PROCESSING TASKS OVER SUCH DATA, SPECIFICALLY, SEARCH AND RETRIEVAL, HAVE GAINED AN INCREASING ATTENTION AND IMPORTANCE. THEREFORE, MANY RESEARCH STUDIES HAVE BEEN CONDUCTED AROUND THE TOPICS. SINCE MOST OF THE USERS-WHO SEARCH OVER XML DATA- HAVE NO KNOWLEDGE OF UNDERLYING STRUCTURE OF TARGET DATA, PROVIDING THEM WITH SOME TYPE OF INSTRUCTIONS AND GUIDANCE WILL RESULT IN INCREASING THE QUALITY AND EFFICIENCY OF THE SEARCH (RETRIEVAL) PROCESS. FURTHER, REGARDING THE REVISITED POSITION (ROLE) OF HUMANS IN THE COMPUTING PROCESSES –ESPECIALLY WITHIN THE PAST DECADE- IT RECENTLY BECAME A MAINSTREAM TO LEVERAGE HUMANS' ABILITY IN ORDER TO IMPROVE SEARCH, RETRIEVAL AND DATA MANIPULATING-RELATED PROCESSES. FOLLOWING THIS TREND, SOME STUDIES HAVE BEEN CONDUCTED IN THE CONTEXT OF XML. SINCE, THESE WORKS PERFORMED IN DIFFERENT DIRECTIONS, LACK OF A COMPREHENSIVE STUDY FOR ORGANIZING THE LITERATURE AND PROVIDING A REFERENCE POINT AS WELL AS ROAD MAP FOR THE FUTURE STUDIES IN THE FIELD IS OBVIOUS. TO FILL THIS IMPORTANT GAP, THIS PAPER AIMED TO PROVIDE A BROAD VIEW OF THE FIELD TO INVESTIGATE DIFFERENT ASPECTS OF THE TOPIC IN THE FORM PRESENTING AN OVERVIEW.

THIS PAPER EXAMINES THE POSTINGS ON FACEBOOK TIMELINE WHICH BELONGS TO A FEMALE MUSLIM APOSTATE. THE MAIN AIM IS TO EXPLORE HER VIEWS TOWARDS THE RELIGION IN ORDER TO UNDERSTAND THE REASONS BEHIND HER APOSTASY. THE FACEBOOK TIMELINE WAS OBSERVED FOR TWO YEARS (JANUARY 2016 TO DECEMBER 2017). MORE THAN 4, 000 POSTINGS WERE MADE IN THE PERIOD OF DATA COLLECTION. THE THEMATIC ANALYSIS OF THE POSTINGS REVEALS THAT ISLAM IS PERCEIVED AS DISCRIMINATIVE, COERCIVE, AND IMAGINARY. THESE NEGATIVE VIEWS OF ISLAM MAY BE ONE OF THE CONTRIBUTING FACTORS TO HER APOSTASY AND THE SHARING OF THE VIEWS ON THE TIMELINE CAN BE SEEN AS AN ATTEMPT TO PROMOTE HER IDEOLOGY. IN ENGAGING READERS WITH THE POSTINGS, THE APOSTATE MAINLY USED IMAGERY, RHETORICAL QUESTIONS, CONSTRUCTED DIALOGUES AND LOADED WORDS. THIS PAPER IS NOVEL IN THE SENSE THAT IT PUTS FORTH THE VIEWS OF AN APOSTATE WHICH IS VERY SCARCE IN THE CURRENT LITERATURE. IT IS ALSO METHODOLOGICALLY INNOVATIVE AS IT USES SOCIAL MEDIA POSTINGS AS A TOOL TO EXPLORE THE APOSTATE’S VIEWS OF RELIGION. THIS PAPER CONCLUDES THAT THE FACEBOOK TIMELINE HAS BEEN STRATEGICALLY USED BY THE APOSTATE TO PROMOTE HER IDEOLOGIES AND BELIEFS.

EFFECTIVE MEASUREMENTS AND ACCURATE ANALYSIS OF THE QUALITY OF NEWS SITES ARE THE NECESSARY STEPS TO IMPROVE THE SITES PERFORMANCE AND REPORTING METHODS. THE PURPOSE OF THIS RESEARCH IS TO PROPOSE AN INTELLIGENT QUALITY ASSESSMENT METHOD FOR NEWS SITES. THE PRESENT STUDY CONSISTS OF TWO PARTS. IN THE FIRST PART DELPHI TECHNIQUEAS A QUALITATIVE METHOD IS USED TO IDENTIFY THE INDICATORS FOR ASSESSING THE QUALITY OF NEWS SITES IN THIS REGARD, 5 DIMENSIONS AND 69 INDICATORS AS WELL AS SEVERAL SUB-CRITERIA FROM FIVE PERSPECTIVES OF DESIGN AND GRAPHIC DESIGN, CONTENT, TECHNICAL SYSTEM, SERVICES, AND EXECUTIVE MANAGEMENT OF NEWS SITES WERE IDENTIFIED,. SUBSEQUENTLY, BY THE QUALITY OF 61 NEWS SITES, WAS CALCULATED AND THE QUALITY SCORE OF EACH SITE WAS OBTAINED USING A QUESTIONNAIRE. IN THE SECOND PART, A NEURAL NETWORK MODEL WAS DESIGNED, WITH 9 INPUTS AND AND ONE OUTPUT. THE RESULTS AND THE VALUES OF MEAN SQUARED ERROR INDICATE THE VALIDITY OF THE PROPOSED MODEL.

THESE DAYS, TWITTER SOCIAL NETWORK IS ONE OF THE MAIN PLATFORMS FOR GETTING NEWS, AMONG PEOPLE OVER THE WORLD. THIS IS BECAUSE OF THE HIGH VOLUME OF DATA GENERATED BY THIS SOCIAL MEDIA, WHICH MAKES TWITTER UP TO DATE WITH NEWS AND INFORMATION. NEVERTHELESS, THE EXISTENCE OF INVALID INFORMATION OVER THE SOCIAL NETWORK MAKES THE USERS UNHAPPY AND ALSO ARISES SOME PROBLEMS IN THE REAL WORLD, PARTICULARLY IN THE CRISIS. TO OVERCOME THESE PROBLEMS AND OTHER POSSIBLE ISSUES, AUTOMATIC DETECTION OF RUMOR ON TWITTER MUST BE TAKEN INTO ACCOUNT. DESPITE SUCH ISSUES, IN THIS PAPER, RUMOR DETECTION IN TWITTER IS STUDIED. IN THIS PAPER, THE RUMOR IS VALIDATED BY CONSIDERING THE USER'S FEEDBACK, AS THE SOURCE DATA FOR RUMOR STUDY. IN OUR PROPOSED METHOD, PATTERN RECOGNITION AND ITS ANALYSIS OF THE USER CONVERSATIONAL TREE IN TWITTER IS STUDIED. THESE RECOGNIZED PATTERNS FEED INTO AS FEATURES FOR TRAINING A CLASSIFIER FOR RUMOR DETECTION. THE MODEL FOR TRAINING A CLASSIFIER IS AN EXTREME LEARNING MACHINE AND ITS EXTENSION. THE DATASET FOR EXPERIMENTS OF OUR METHOD IS THE STANDARD DATASET OF SEMEVAL-2017 TASK 8. EXPERIMENTS OF OUR PROPOSED METHOD WITH RESPECT TO COMPETITOR METHODS IN RUMOR DETECTION SHOW THAT OUR METHOD OUTPERFORMS THE STATE OF THE ART METHODS.

NOWADAYS, TOURISM IS MORE THAN JUST AN INDUSTRY, AND LIKE A DYNAMIC GLOBAL AND SOCIAL PHENOMENON. THE CITY OF SHIRAZ HAS ATTRACTED MANY TOURISTS FOR ITS ATTRACTIONS. WITH THE CHANGES THAT HAVE BEEN MADE TO THE WAY INFORMATION ACCESS IS ONE OF THE MOST WIDELY USED TOOLS FOR APP TOURISTS; THEREFORE, APPS MUST HAVE MANY CAPABILITIES AND TAILORED TO SUIT USER NEEDS SO THAT THE USER CAN EASILY AND EASILY ACCESS THE INFORMATION THEY NEED. FIND AND DO NOT GET CONFUSED.IN THIS RESEARCH, WE DEFINE THE USER NEEDS QUESTIONNAIRE AND DEFINE DIFFERENT SCENARIOS FOR USER EXPERIENCE, AND WE HAVE DEVELOPED A SPECIFIC MODEL AND TEMPLATE. BASED ON THIS PATTERN, WE REVIEWED 15 TOURISM APPLICATIONS IN SHIRAZ. THE RESULTS OBTAINED FROM THE ANALYSIS CAN BE SAID THAT THE ONLY THING THAT IS OBSERVED IN ALL APPLICATIONS IS DETAILED DESCRIPTIVE EXPLANATIONS. BASED ON THE ASSUMPTIONS OF THE RESEARCH, IT SEEMS THAT THE EXISTING APPLICATIONS IN THE TOURISM AREA OF SHIRAZ DO NOT HAVE THE PROPER DESIGN OF THE INTERFACE; AND IN DESIGNING THE USER EXPERIENCE OF APPLICATIONS IN THIS FIELD MANY OF THE NEEDS OF USERS ARE IGNORED. ACCORDING TO THE RESULTS, BOTH HYPOTHESES ARE CONFIRMED.

ONTOLOGIES ARE ONE OF THE IMPORTANT AND EFFECTIVE PARTS OF SEMANTIC WEB WHICH CONSTITUTE THE INFRASTRUCTURE AND BACKGROUND KNOWLEDGE OF THIS REALM OF WEB SCIENCE. FINDING VALID MAPPINGS AS MUCH AS POSSIBLE BETWEEN THE CONCEPTS OR ENTITIES OF ONTOLOGIES, ESPECIALLY FOR THE LARGE ONES, IS A PROMINENT TASK TO ALIGN THOSE CONCEPTS TOGETHER AND FINALLY MERGE AND INTEGRATE THEIR ONTOLOGIES TO MAKE A GENERAL AND GLOBAL ONTOLOGY THAT IS SMALLER AND MORE FLEXIBLE IN MANY APPLICATIONS OF SEMANTIC WEB. THIS PAPER DESCRIBES A NEW LEARNING-BASED ONTOLOGY MAPPING METHOD IN WHICH INDUCTIVE LOGIC PROGRAMMING (ILP) IS USED TO LEARN ONTOLOGY MAPPING USING INFORMATION GATHERED FROM INSTANCES OF EACH ENTITY IN ORDER TO MAKE SOME CORRECT AND VALID ALIGNMENTS BETWEEN CONCEPTS OF DIFFERENT ONTOLOGIES.

WITH AN INCREASING NUMBER OF INTERNET USERS UTILIZING SMARTPHONES AND SIMILAR DEVICES, FINGERPRINT SCANNERS ARE BECOMING INCREASINGLY IMPORTANT AS A SECURITY FEATURE. FROM A BUSINESS POINT OF VIEW, A COMPANY PUT ITS REPUTATION AT RISK IF ITS BIOMETRIC SECURITY SYSTEM CAN BE SPOOFED. FROM A USER POINT OF VIEW, SINCE THE FINGERPRINT LAST FOR A LIFETIME, ONCE LEAKED THEY ARE LEAKED FOR THE REST OF USER’S LIFE. THIS SURVEY REVIEWS THE FINGERPRINT SYSTEM, CLASSIFIES DIFFERENT PARTS OF IT INCLUDING TECHNIQUES FOR EXTRACTING FEATURES AND MATCHING PROCEDURES, DIFFERENT VULNERABILITIES AND PROPOSES THREE AVENUES FOR MITIGATING THE VULNERABILITIES INCLUDING SOFTWARE (BIG DATA AND ENCRYPTION/ DECRYPTION) AND SECURE HARDWARE TECHNIQUES.

INBOUND MARKETING IS THE PROCESS OF ATTRACTING THE PROBABLE CUSTOMERS TO A BUSINESS BEFORE THEY HAVE ANY INTENTION TO BECOME CUSTOMERS. AN EFFECTIVE METHOD FOR INBOUND MARKETING IS CREATION OF A POSITIVE PSYCHOLOGICAL BUSINESS ENVIRONMENT TO ATTRACT THE CUSTOMERS. A SIGNIFICANT PORTION OF TRADITIONAL BUSINESS ENVIRONMENT IS MOVING ONLINE AND THE NEW BUSINESS ENVIRONMENT IS THE COMPANY WEBSITE. ONE OF THE MAJOR ELEMENTS IN ONLINE INBOUND MARKETING IS THE WEBSITE ADDRESS AND THE WEBSITE LOGO, WHICH ARE THE FIRST FACTORS OF BRAND PERSONALITY THAT THE VISITOR TO THE COMPANY WEBSITE ENCOUNTERS WHEN LOOKING UP THE WEBSITE IN A SEARCH ENGINE. IN THIS PAPER, A FRAMEWORK FOR INBOUND E-MARKETING USING VISUAL AND PHONETIC USER EXPERIENCE ANALYTICS IS PROPOSED. THE POPULAR WEBSITES ARE STUDIED AND THE RELATIONSHIP BETWEEN WEBSITE PAGE VIEWS AND THE ENGLISH PHONETIC CONSTRUCTION OF THE WEBSITE ADDRESS AND ITS LOGO ARE ANALYZED. FOR DEMONSTRATING THE RELATIONSHIP BETWEEN THE WEBSITE LOGO AND NAME AND ITS APPEAL TO THE CUSTOMERS, THE PROPOSED MODEL IS TRAINED BY A NEURAL NETWORK. THE PROPOSED MODEL IS CAPABLE TO PREDICT WEBSITE PAGE VIEWS BASED ON THE COMPANY LOGO AND THE WEBSITE ADDRESS. THE EXPERIMENTAL RESULTS SHOW THAT THE PROPOSED FRAMEWORK IS CAPABLE OF RECOMMENDING THE STRATEGY FOR INBOUND MARKETING FOR ONLINE BUSINESS AND SERVICES WITH HIGH ACCURACY.

CROWDSOURCING REFERS TO A WAY OF DIVIDING A COMPLEX TASK INTO A NUMBER OF TINY AND IDENTICAL SUB-TASKS AND DISTRIBUTING SUB-TASKS BETWEEN CROWDS OF UNKNOWN PEOPLE WITH DIFFERENT SKILLS AND EXPERIENCES. IN RECENT YEARS, WITH THE ADVENT OF THE INTERNET, THIS METHOD OF ACCOMPLISHING COMPLEX TASKS ATTAINS LOTS OF ATTRACTION. WEBAZMA, IS A LABORATORY RESIDES WITHIN THE IRAN TELECOMMUNICATIONS RESEARCH CENTER (ITRC), WHOSE AIM IS TO EVALUATE PERSIAN WEB-BASED SERVICES. CONSIDERING THE FACT THAT THE PRIMARY REFERENCE FOR EVALUATING A WEB-BASED SERVICE IS ITS CUSTOMERS, WEBAZMA CONCENTRATES ON HUMAN-BASED EVALUATIONS, AND THUS, SETUP A CROWDSOURCING FRAMEWORK FOR EXECUTING SUCH EVALUATIONS USING UNKNOWN CROWDS. THUS FAR, MANY DIFFERENT EVALUATIONS HAVE BEEN CARRIED OUT WITHIN THIS FRAMEWORK. FURTHERMORE, THE FRAMEWORK HAS BEEN DESIGNED IN SUCH A WAY THAT IT CAN RUN VARIETY OF TASKS, OTHER THAN REQUIRED BY THE LABORATORY. THESE ARE DATASET GENERATION, ESPECIALLY FOR DEEP LEARNING PURPOSES, CONFIRMING DATASETS, CREATING AUDIO BOOKS, EXECUTING ONLINE SURVEYS, AND DIGITIZING OLD DOCUMENTS TO MENTION A FEW. THIS PAPER AIMS AT INTRODUCING THIS FRAMEWORK AND ITS CAPABILITIES WITH THE GOAL OF ENCOURAGING RESEARCHES, COMPANIES, AND OTHER ORGANIZATIONS TO EXPLOIT IT FOR ACCOMPLISHING THEIR COMPLEX TASKS; THOSE WHICH REQUIRE HUMAN WORKFORCES.

WE USE SEARCH ENGINES TO FIND OUR NEEDED INFORMATION THOUGH AMOUNT OF DATA. MOST OF THE TIME PEOPLE USE INTERNET TO GET INFORMATION ABOUT EVERY JOB. WEB SEARCH ENGINES OFTEN CONFUSE PEOPLE BY PRESENTING DIFFERENT RESULTS FOR SAME QUERIES. SEARCH ENGINES CREATE PROFILES FOR USERS TO SOLVE THIS PROBLEM. ACCORDING TO EACH USER'S PROFILE, SEARCH ENGINES REPRESENT RESULTS. OFTEN, USERS’ PRIVACY ARE IN ENDANGER BY USING THESE TOOLS. IN WEB SEARCH ENGINES RESULTS, WE NEED TO HAVE QUALITY AND PRIVACY PROTECTING BOTH TOGETHER. IN THIS ARTICLE WE PRESENT PROBLEMS THAT THREATEN THE USERS’ PRIVACY. WE ALSO REVIEWE HOW TO PREVENT WEB SEARCH ENGINES FROM VIOLATING THE USERS’ PRIVACY.

DUE TO THE GROWING GROWTH OF WEB APPLICATIONS AND THE TENDENCY TO USE THEM IN MOST CATEGORIES, ESPECIALLY THE MOST IMPORTANT INDUSTRIES, FINANCIAL, COMMERCIAL AND INFORMATIONAL AREAS, THE CHALLENGE OF SECURITY IS HIGHLIGHTED IN GREAT DETAIL. BY PRACTICING SECURITY THINKING AT DIFFERENT STAGES OF DESIGNING AND PRODUCING WEB-BASED SOFTWARE, THIS CAN BE SOMEWHAT ACHIEVED, BUT CERTAINLY NOT ENOUGH. WEB APPLICATIONS FIREWALLS ARE PROFESSIONAL TOOLS THAT CAN PROTECT SOFTWARES IN THIS AREA AGAINST VARIOUS SECURITY CHALLENGES AND PREVENT DATA BEING STOLEN OR SERVICES INACCESSIBLE.IN THIS PAPER, DESCRIBING THE SECURITY CHALLENGES AHEAD IN THE FIELD OF WEB APPLICATIONS, THE FIREWALLS WILL BE INTRODUCED IN 2017 AND COMPARED BRIEFLY.

ICT INCREASINGLY IS DEVELOPING AND ITS CONTEXTS SUCH AS INTERNET, SMARTPHONES, AND EVOLUTION IN COMMUNICATIONS MANIFOLD MAKE TO STRENGTHEN SOCIAL NETWORKS IN WORLDWIDE. TODAY SOCIAL NETWORKS ARE A POPULAR MEDIA FOR NETWORKING USERS. THESE PROVIDE AN EXPANDED RANGE OF SERVICE AND FUNCTIONS TO USERS AND ARE DIFFERENT AT THE TYPE OF SERVICE PROVIDING; THESE TYPES ARE CLASSIFIED INTO PUBLIC AND PROFESSIONAL NETWORKS. AT THE FORMER TYPE, THE USERS PURSUE VARIOUS GOALS AND MOTIVATIONS VIA THESE NETWORKS; AGAINST, PROFESSIONAL SOCIAL NETWORKS BE FORMED AROUND THE SPECIFIC SUBJECT AND HAVE MORE LIMITED USERS.ACCORDINGLY, THE PURPOSE OF THIS ARTICLE IS TO ANALYZE SOME OF THE SOCIAL NETWORK'S PUBLIC CHARACTERISTIC AND PARTICULARLY ANALYZE LINKED-IN PROFESSIONAL SOCIAL NETWORK FROM THE POINT IN VIEW OF TECHNICAL AND SOCIAL DIMENSIONS SUCH AS THE NUMBER OF USERS, THE VARIETY OF SERVICE, THE INCOME MODEL AND STRATEGIES OF USER ATTRACTION. THIS RESEARCH HAS BEEN DONE BY STUDYING AND REVIEWING ARTICLES AND LIBRARY DOCUMENTS, AND IN PARTICULAR THE WEBSITE OF LINKED-IN; RESULTS SHOW THAT HOW LINKED-IN CURRENTLY IS A MOST SUCCESSFUL PROFESSIONAL SOCIAL NETWORK AND HOW IT CAN ATTRACT MORE THAN 500 MILLION USERS BETWEEN OTHER PROFESSIONAL SOCIAL NETWORKS. IN ADDITION, IT IS THE FIRST PROFESSIONAL SOCIAL NETWORKS THAT EARN HIGH INCOME FROM PROVIDING BUSINESS AND HIRING SERVICE IN THE WORLD. AT THE END OF THIS RESEARCH, ONE OF THE MOST IMPORTANT REASONS FOR THE FAILURE OF THIS NETWORK IN IRAN THAT RECOGNIZE IS THE LACK OF SUPPORT FOR THE PERSIAN LANGUAGE BY THIS NETWORK; SO THIS CAN USE AS A GUIDE TO START SOCIAL NETWORK-BASED BUSINESSES IN IRAN. ANOTHER REASON MAY BE SANCTIONS AGAINST IRAN, THEREFORE, IRANIAN USER CANNOT USE ITS BUSINESS SERVICE EFFECTIVELY.

TODAY, THE WORLD WIDE WEB IS CONSIDERED AS THE LARGEST SOURCE OF DATA WITH THE HELP OF WEB SEARCH ENGINES, AS ONE OF THE MOST USEFUL TOOLS FOR EXTRACTING INFORMATION. DUE TO THE WEB GROWTH, PROVIDING INFORMATION RELATED TO USER QUERIES BY SEARCH ENGINES IS VERY DIFFICULT. ALSO, THE EFFECTIVENESS OF THE INFORMATION RETRIEVAL SYSTEMS IS LARGELY DEPENDENT ON TERM-WEIGHTING. THEREFORE, SEARCH ENGINES USE DIFFERENT WEB MINING TECHNIQUES TO RANK SEARCH RESULTS. FOR THIS PURPOSE, VARIOUS RANKING ALGORITHMS ARE PRESENTED.IN THIS RESEARCH, THE WEIGHTING ALGORITHM TF_IDF IS USED TO RANK THE DOCUMENTS. BY INTRODUCING THE ENTROPY PARAMETER RELATED TO THE NUMBER OF USER QUERY WORDS IN THE TEXT OF THE DOCUMENTS, THE ACCURACY OF THE RANKING OF THE DOCUMENTS IN THE INFORMATION RETRIEVAL IS EVALUATED. THE REMARKABLE POINTS OBTAINED FROM THE SURVEYS ON STANDARD QUESTIONS PROVIDE A NEW APPROACH TO INCREASING THE EFFICIENCY OF TEXT SEARCH SYSTEMS, WHICH THE RESPONSES FROM SUBSEQUENT EXPERIMENTS DEMONSTRATE ITS VALIDATION. THE PROPOSED APPROACH IN THIS PAPER USES THE STANDARD WEB COLLECTIONS AND THE RESULTS SHOW THAT IT CAN SIGNIFICANTLY INCREASE THE ACCURACY OF RETRIEVAL IN TERMS OF THE VOLUME OF TEST DATA COLLECTION.

NOWADAYS, THE DISCOVERY OF IMPORTANT NODES IS AMONG THE MAIN CONCERNS OF SOCIAL NETWORKS ANALYSIS. DISCOVERING IMPORTANT NODES HAS BEEN DONE FOR WIDE RANGE OF PURPOSES; FROM DISCOVERING LEADERS IN TERRORISTIC NETWORKS TO DISCOVERING INFLUENTIAL PEOPLE IN ADVERTISEMENT NETWORKS. SO FAR DIFFERENT CRITERIA HAVE BEEN INTRODUCED FOR DISCOVERY OF IMPORTANT NODES. DUE TO THE DIVERSITY OF GRAPH STRUCTURES FROM ON SIDE, AND GENERALITY OF PREVIOUS METHODS IN OTHER SIDE THE ACCURACY OF PREVIOUS METHODS IN DISCOVERING THE IMPORTANT NODES IS VERY LIMITED. IN THIS PAPER, A SYSTEM CALLED DINGA FOR DISCOVERING OF IMPORTANT NODES IN SOCIAL NETWORKS WITH AN UNKNOWN STRUCTURE HAS BEEN PROPOSED. OUR PROPOSED SYSTEM DISCOVERS THE IMPORTANT NODES IN SOCIAL NETWORKS BY EMPLOYING A WEIGHTED COMBINATION OF EIGHT INFORMATIVE CRITERIA OF IMPORTANT NODES USING GENETIC ALGORITHM. THE EFFICIENCY OF THE PROPOSED SOLUTION HAS BEEN INVESTIGATED THROUGH SIMULATION ON THE ENRON E-MAIL NETWORK. OUR PROPOSED METHOD OUTPERFORMS THE PREVIOUS METHODS, IN ADDITION TO RANDOM WEIGHT LEARNER, 21% WITH RESPECT TO ACCURACY.

THE WORKFLOW SCHEDULING PROBLEM IS ONE OF THE MOST IMPORTANT CHALLENGES IN CLOUD COMPUTING, WHICH SHOULD BE CONSIDERED BY CLOUD DATA PROVIDERS IN DATA CENTERS. SINCE GOALS OTHER THAN MAKESPAN SHOULD BE CONSIDERED IN THE REAL-WORLD SCHEDULING AND THESE GOALS ARE CONTRADICTOR IN MOST CASES, THE WORKFLOW SCHEDULING PROBLEM IS A NP-HARD PROBLEM. CONSIDERING THE COMPLEXITIES OF THE SCHEDULING PROBLEM, MULTI-OBJECTIVE METAHEURISTIC ALGORITHMS ARE A GOOD OPTION FOR SOLVING SUCH PROBLEMS. THESE ALGORITHMS HELP SERVICE PROVIDERS FIND A SET OF OPTIMAL TRADEOFFS OF SOLUTIONS. AN IMPORTANT CRITERION IN FINDING THIS TRADEOFF IS DIVERSITY IN THE CHOICE OF SOLUTIONS. BY ADDING THIS CRITERION TO THE MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS, ONE CAN ACHIEVE A SET OF OPTIMAL SOLUTIONS. GIVEN THE IMPORTANCE OF THIS CRITERION, WE EXTENDED THE BLACK HOLE HEURISTIC ALGORITHM AND THEN PRESENTED A NEW MULTI-OBJECTIVE ALGORITHM BASED ON THE DIVERSITY CRITERIA FOR WORKFLOW SCHEDULING IN THE CLOUD ENVIRONMENT. THE PURPOSE OF THE PROPOSED ALGORITHM IS TO SEARCH FOR THE PROBLEM SPACE AND FIND THE NON-DOMINATED PARETO FRONT TO OPTIMIZE THE RESOURCE EFFICIENCY, MAKESPAN AND COST FACTORS IN THE CLOUD ENVIRONMENT. IN ORDER TO ACHIEVE THIS GOAL, WE NOT ONLY INCREASED THE DIVERSITY OF SOLUTIONS, BUT ALSO MODIFIED THE LAYOUT TYPE OF INITIAL SOLUTIONS BASED ON THE PRIORITY OF REQUESTS IN THE WORKFLOW, AND CREATED A MORE APPROPRIATE INITIAL GENERATION TO ENHANCE THE PURPOSEFULNESS OF OUR SEARCH. THE RESULTS OBTAINED FROM THE WORKFLOWSIM SHOW THAT THE PROPOSED METHOD IMPROVES THE BALANCED AND UNBALANCED WORKFLOW BETTER THAN DO THE KNOWN ALGORITHMS OF SPEA2 AND NSGA2 AND PBHO.

IN RECENT YEARS, VEHICLES HAVE MADE A LOT OF PROGRESS, BUT NOT ALL OF THEIR COMPUTATIONAL CAPACITIES HAVE YET BEEN USED. VEHICULAR CLOUD COMPUTING (VCC) IS A CONCEPT THAT USES THIS COMPUTATIONAL CAPABILITY USING THE CONCEPT OF CLOUD. THE COST AND APPLICATIONS OF ANY TECHNOLOGIES HAVE ALWAYS BEEN OF GREAT IMPORTANCE IN ITS USAGE. GIVEN THE NOVICE CONCEPT, AS FAR AS THE AUTHORS KNOW, THERE IS NO MODEL THAT CAN CALCULATE THE COST AND RESPONSE TIME OF THE VCC. THE TOPIC DISCUSSED IN THIS PAPER IS TO PRESENT A MODEL FOR VCC WITH THE APPROACH OF COST AND RESPONSE TIME REDUCTION USING ONBOARD COMPUTATIONAL CAPACITIES. THIS MODEL CAN HELP TO ESTIMATE THE COST OF IMPLEMENTATION AND VARIOUS SCENARIOS OF VCC. IN THE MODEL, COST CALCULATIONS ARE BASED ON THE LOCATION OF THE COMPUTATIONAL WORK, THE HARDWARE SPECIFICATIONS OF THE COMPUTING RESOURCES, AND THE RESOURCE PRIORITY. THE SIMULATION OF THE PROPOSED MODEL HAS BEEN DONE IN CLOUD ANALYST SOFTWARE FOR DIFFERENT PERIODS, AND THE RESULTS WERE COMPARED WITH ANOTHER REFERENCE. THE RESULTS INDICATE THAT THE PROPOSED MODEL CAN SHOW A VIEW OF THE PROPOSED SYSTEM WITH ITS PROS AND CONS.

DUE TO THE MAJOR ROLE OF RESEARCH IN SUSTAINABLE DEVELOPMENT OF COUNTRIES ALL AROUND THE WORLD, MAPPING THE SCIENTIFIC PRODUCTION MUST BE DESIGNED ACCORDING TO INDEXED IN DATABASES. THE PURPOSE OF THE PRESENT STUDY IS TO ANALYZE IRANIAN LITERATURE ON THE FIELD OF SOCIAL NETWORKS IN COMPARISON WITH THE SAME STUDIES AT CROSS THE WORLD LEVEL. THIS IS A RESEARCH IS A DESCRIPTIVE STUDY. A TOTAL OF 123, 609 DOCUMENTS INDEXED PERTAINED TO THIS TOPIC WERE PROCESSED FROM 1970 TO THE END OF 2017 INDEXED IN SCOPUS DATABASE. EXCEL SOFTWARE WAS USED TO ANALYZE THE DATA. DIFFERENT STUDY TYPES, CHARACTERIZED BY YEARS, CITY/COUNTRY OF ORIGIN, JOURNALS AND MORE PRODUCTIVE AUTHORS, THE RATIO COOPERATION BETWEEN THEM BY COUNTRY AND INSTITUTIONS, CITES AND H INDEX. DATA WAS COLLECTED AND ANALYZED IN MICROSOFT EXCEL SOFTWARE. FINDING SHOWED THAT UNITED STATES WAS THE HIGHEST PRODUCER (%29.74), FOLLOWED BY CHINA (%11.85) AND IRAN RANKED 31TH AMONG THE COUNTRIES OF THE WORLD. ALTHOUGH, RATIO OF SCIENTIFIC PRODUCTION IN BIBLIOGRAPHICAL DATABASES, PARTICULARLY REGIONAL, IS STILL RELATIVELY IMPRESSIVE THEN IT IS NECESSARY TO PROMOTE MORE RESEARCH ON IT.

IN THIS DECADE WITH INCREASING TECHNOLOGY DEVELOPMENT AND WIDE USAGE OF MOBILE DEVICES, USING APPLICATIONS IN TEACHING PATIENTS SPECIALLY THE ONES WITH PARTICULAR RESTRICTIONS SUCH AS SPINAL CORD INJURY (SCI) PATIENTS WHO ARE NOT ABLE TO MOVE THAT EASILY, COULD BE BENEFICIAL. ON THE OTHER HAND, DUE TO THEIR VARIOUS BODY CAPABILITIES, THE TEACHING MATERIAL COULD NOT BE THE SAME FOR ALL THE PATIENTS. THUS PERSONALIZING SUPPORT SYSTEMS SEEMS TO HAVE A SIGNIFICANT ROLE ON INCREASING USER SATISFACTION, IMPROVING TREATMENT TREND AND INCREASING THE PATIENT'S ABILITY TO DO DAILY ACTIVITIES. TAKING THE ABOVE POINT INTO ACCOUNT, IN THIS PAPER WE ARE GOING TO DESCRIBE THE PERSONALIZATION PROCESS OF "SPINAL CORD INJURY MOBILITY AND TRANSFER SUPPORT APPLICATION" WHICH IS BASED ON CASE-BASED REASONING (CBR). THE SUPPORT APPLICATION WILL PROVIDE PERSONALIZED EDUCATIONAL CONTENTS SUCH AS VIDEOS TEACHING MOBILITY AND TRANSFER, TEXT AND AUDIO GUIDES, ACCORDING TO THE PATIENTS' CHARACTERISTICS. IN ORDER TO OPTIMIZE THE PERSONALIZATION PROCESS, PERFORMANCE OF THE SUPPORT SYSTEM WAS EVALUATED IN TWO SITUATIONS, CHANGING THE NUMBER OF CLUSTERS AND CHANGING THE SIMILARITY THRESHOLD. AT THE END, THE RESULTS CONCLUDED THAT CBR CAN BE USED AS AN EFFECTIVE METHOD IN PERSONALIZING MEDICAL SUPPORT SYSTEMS.

LINK PREDICTION ON SOCIAL NETWORKS IS ONE OF THE ISSUES THAT HAS ATTRACTED MANY RESEARCHERS IN RECENT YEARS. IN THIS PROBLEM, MISSING AND FUTURE LINKS ARE PREDICTED BY USING EXISTING LINKS IN THE. ONE OF THE NEWEST APPROACHES TO THIS PROBLEM IS THE USE OF DEEP LEARNING TO EXTRACT THE VECTOR OF THE FEATURES OF EACH NODE AND THEN FIND MISSING AND FUTURE LINKS. THIS PAPER PRESENTS A METHOD FOR LEARNING THE VECTOR REPRESENTATION OF NETWORK NODES BASED ON THE INFORMATION OF THE NODES ADJACENT TO EACH NODE IN THE SOCIAL NETWORK AND THE VARIOUS LINKS PRESENT ON THE NETWORK. THE RESULTS SHOW THAT THE PROPOSED METHOD PROVIDES GOOD RESULTS FOR LINK PREDICTION IN COMPARISON WITH OTHER METHODS.

ONE OF THE KEY ISSUES IN THE WEB IS THE CONNECTION BETWEEN SOFTWARE SYSTEMS WITHOUT PROGRAMMING LANGUAGE OR OPERATING SYSTEM DEPENDENCIES. WEB SEARCH IS A WEB DEVELOPMENT SOLUTION WITH THE APPROACH. ONE OF THE KEY CHALLENGES IN WEB SERVICE DISCOVERY IS THE INCREASING AVAILABILITY OF WEB SERVICES. IN THIS CONTEXT, MANY STUDIES HAVE BEEN CARRIED OUT BASED ON THE USE OF SERVICE QUALITY PARAMETERS. BUT THE USE OF USERS TO ATTRACT MORE SATISFACTION HAS LESSENED THE DISCOVERY OF WEB SERVICES, WHILE MANY RESEARCHES HAVE BEEN DONE IN VARIOUS AREAS, SUCH AS MULTIMEDIA SYSTEMS. ENTERING A USER'S OPINION IN THE AREA OF SERVICE QUALITY CREATES THE CONCEPT OF QUALITY OF EXPERIENCE. DUE TO THE LARGE NUMBER OF WEB BROWSERS IN DIFFERENT DOMAINS, IT'S A SERIOUS CHALLENGE TO DISCOVER AND SELECT A WEB SERVICE THAT IS CLOSE TO THE USER'S PERSPECTIVE. THIS ARTICLE TRIES TO INCREASE THE USER'S SATISFACTION FROM THE RESULTS OF THE DISCOVERY AND SELECTION OF WEB SERVICES BY OFFERING A SUGGESTED METHOD FOR CHOOSING THE APPROPRIATE QUALITY OF EXPERIENCE. IN THE END, THE RESULTS SHOW THAT USER SATISFACTION HAS BEEN INCREASED AFTER APPLYING THE QUALITY PARAMETERS OF EXPERIENCE IN THE CHOICE OF THE WEB SERVICE.

TODAYS, THE INTERNET CONVEYS NEGATIVE EFFECTS, IN ADDITION TO ITS POSITIVE IMPACTS. PARENTS’ INADEQUATE KNOWLEDGE ABOUT THE INTERNET CAN HARM FAMILY AND SOCIAL LIFE. FAMILY PLAYS A CENTRAL ROLE IN SOCIETY AND HUMAN LIFE THEREFORE PARENTS SHOULD PROTECT THEIR CHILDREN FROM RISKS AND HARMS OF THE INTERNET, IN ADDITION TO THE RISKS AND HARMS IN THE REAL WORLD. THE PRESENT STUDY IS CONDUCTED TO INVESTIGATE THE CORRELATION BETWEEN EDUCATIONAL LEVEL OF PARENTS AND THE PARENTAL SUPERVISION OF THEIR CHILDREN’S PRIVATE INTERNET SETTINGS AND ALSO THE CORRELATION BETWEEN SUPERVISION OF PARENTS AND REJECTION BY CHILDREN. THIS STUDY ASKED 152 IRANIAN STUDENTS AGED 15 TO 17 YEARS AND ONE OF THEIR PARENTS TO FILL OUT QUESTIONNAIRES REGARDING THEIR INTERNET USAGE AND PARENTAL SUPERVISIONS. RESULTS SHOW THAT PARENTS WITH HIGHER EDUCATIONAL STATUS CHECKS CHILDREN’S INTERNET SETTINGS MORE. RESULTS ALSO SHOW THAT THE MORE PARENTS CHECK THEIR CHILDREN’S INTERNET SETTING THE MORE CHILDREN IGNORE PARENTAL SUPERVISION.

INTERNET OF THINGS, COGNITIVE SYSTEMS, AND BLOCK CHAIN TECHNOLOGY ARE THREE FIELDS WHICH HAVE CREATED NUMEROUS REVOLUTIONS IN SOFTWARE DEVELOPMENT. IT SEEMS THAT A COMBINATION AMONG THESE FIELDS MAY RESULTS IN EMERGING A HIGH POTENTIAL AND INTERESTING FIELD. THEREFORE, IN THIS PAPER, WE PROPOSE A FRAMEWORK FOR INTERNET OF THINGS BASED ON COGNITIVE SYSTEMS AND BLOCKCHAIN TECHNOLOGY. TO THE BEST OF OUR KNOWLEDGE, THERE IS NO FRAMEWORK FOR INTERNET OF THINGS BASED ON COGNITIVE SYSTEMS AND BLOCKCHAIN. IN ORDER TO STUDY THE APPLICABILITY OF THE PROPOSED FRAMEWORK, A RECOMMENDER SYSTEM BASED ON THE PROPOSED FRAMEWORK IS SUGGESTED. SINCE THE PROPOSED FRAMEWORK IS NOVEL, THE SUGGESTED RECOMMENDER SYSTEM IS NOVEL. THE SUGGESTED RECOMMENDER SYSTEM IS COMPARED WITH THE EXISTING RECOMMENDER SYSTEMS. THE RESULTS SHOW THAT THE SUGGESTED RECOMMENDER SYSTEM HAS SEVERAL BENEFITS WHICH ARE NOT AVAILABLE IN THE EXISTING RECOMMENDER SYSTEMS.

IN REGARDS TO INCREASING THE RESEARCH INTEREST IN WEB RESEARCH STUDIES AND THE APPLICATIONS OF WEB RESEARCH IN VARIOUS FIELDS, IT NEEDS TO DEFINE AND INVESTIGATE THE RELATED CONCEPTS TO THE WEB. THIS STUDY DISCUSSES AND DEFINES THE DIFFERENT TYPES OF WEB AND RELATED CONCEPTS. IN THIS STUDY DIFFERENT TYPES OF THE WEB FROM WEB 1.0 TO WEB 5.0 AND THEIR TOOLS WILL DEFINE, THEN COMPARE WEB 2.0 AS THE INTERACTIVE WEB, SOCIAL MEDIA AND VIRTUAL SOCIAL NETWORKS, THEIR SIMILARITIES, AND DIFFERENCES. FINDINGS SHOW THAT ALTHOUGH WEB 2.0, SOCIAL MEDIA AND VIRTUAL SOCIAL NETWORKS HAVE SIMILARITIES IN DEFINITION AND APPLICATION, THEY ARE DIFFERENT CONCEPTS WHICH CANNOT USE THEM INSTEAD.

THIS STUDY AIMED TO DESIGN A METADATA APPLICATION PROFILE TO ORGANIZE CONTENT OBJECTS OF SHAHID BEHESHTI UNIVERSITY OF MEDICAL SCIENCES’ LIBRARIES. A SYSTEMATIC-ANALYTICAL APPROACH WAS USED IN THIS RESEARCH. THE STUDY POPULATION INCLUDED CONTENT OBJECTS IN THE 23 LIBRARIES (CENTRAL, HOSPITAL AND COLLEGE LIBRARIES) OF SHAHID BEHESHTI UNIVERSITY OF MEDICAL SCIENCES. FOR COLLECTING DATA RELATED TO THE NATIVE FEATURES AND NEEDS OF GENERATING METADATA RECORDS IN THESE LIBRARIES, A QUESTIONNAIRE DESIGNED BY THE RESEARCHER. THE QUESTIONNAIRE WAS COMPLETED BY THE LIBRARIANS OF THE ORGANIZATION, AND STRUCTURED OBSERVATION BY THE RESEARCHER OF THE METADATA DATABASES OF LIBRARIES IN THE RESEARCH COMMUNITY.THE NATIVE NEEDS OF LIBRARIES AND INTENDS OF THEM IN THE FIELD OF INFORMATION ORGANIZATION WAS EXTRACTED VIA A CHECKLIST (CREATED BASED ON THE METADATA STANDARDS) AND TAKING INTO ACCOUNT THE CONTEXT OF LIBRARIES IN SHAHID BEHESHTI UNIVERSITY OF MEDICAL SCIENCES, AN APPLICATION PROFILE WAS DESIGNED TO ORGANIZE THEIR CONTENT OBJECTS. THE APPLICATION PROFILE CONTAINS 63 ELEMENTS INCLUDING 22MANDATORY ELEMENTS AND 41 OPTIONAL ELEMENTS FOR DESCRIBING DIFFERENT KINDS OF CONTENT OBJECTS. AMONG THESE 63 ELEMENTS, 53 ELEMENTS HAVE BEEN SELECTED FROM THE UNIMARC FORMAT AS THE BASIC STANDARD, 8 ELEMENTS HAVE BEEN EXTRACTED FROM THE DUBLIN CORE METADATA INITIATIVE (DCMI), AND2 ELEMENTS HAVE BEEN DETERMINED FROM THE METADATA OBJECT DESCRIPTION SCHEMA (MODS). FINALLY, THE STRUCTURE AND SEMANTICS OF THE METADATA APPLICATION PROFILE DESIGNED BASED ON THE CONTEXT OF THE LIBRARIES TO BE STUDIED.

NOWADAYS, THE SOCIAL NETWORKS BACAME ONE OF THE CRUCIAL COMMUNICATING TOOLS IN SOCIAL AND GLOBE AND THEY HAVE A HIGH REPUTATION BETWEEN PEOPLE. AS STUDY THE MOTIVATION OF THE USERS IN USING THE SOCIAL NETWORKS IS IMPORTANT; THIS STUDY AIMS TO INVESTIGATE THIS MOTIVATION. THIS IS A REVIEW-DESCRIPTIVE STUDY REVIEWING THE PREVIOUS STUDIES ON THE REASON AND MOTIVATION OF IRANIAN USERS APPLYING FOR THE SOCIAL NETWORKS. TO DO SO, DATA AND INFORMATION OF THIS STUDY WERE GATHERED BY SEARCHING A KEYWORD IN BOTH PERSIAN DATA BASE (SID, NOORMAGS, ENSANI) AND GOOGLE SCHOLAR. THE RESULTS OF NINETEEN ARTICLES WERE CHECKED. THE RESULTS INDICATE THAT IRANIAN USERS USE THE SOCIAL NETWORK WITH DIFFERENT INCENTIVES WHICH COMMUNICATING WITH FRIENDS, FIND THE NEW FRIENDS, FUN AND HOBBY, SHARING THE DATA, LEARNING THE NEW CAPABILITIES, EDUCATION AND BEING UPDATE BY NEWS ARE AMONG THE MOST IMPORTANT ONE.

ACCORDING TO THE INCREASING USAGE OF CLOUD COMPUTING AND NECESSITY OF OPTIMIZE USAGE OF RESOURCES, AND CONSIDERING TO USERS WHO PAY FOR SERVICES BY THEM USAGE (PAY-AS-YOU-GO), THERE SHOULD BE A QUICKER WAY FOR USERS TO DECREASE THE USER'S WAITING TIME AND TASK'S MAKES PANE. THE MAIN PURPOSE OF THIS PAPER IS TO PROVIDE AN OPTIMAL ALGORITHM USING THE ADVANTAGES OF TWO TRADITIONAL ALGORITHMS: MIN-MIN AND MAX-MIN. OTHER POINT THAT FOLLOW IN TOMMP ALGORITHM IS THE PRIORITY OF THE TASKS. THERE ARE A LOT OF SCHEDULING ALGORITHMS IN THE WORLD TODAY, BUT IN MOST ALGORITHMS THE PRIORITY GIVEN TO THE TASK HAS BEEN NEGLECTED AND OVERLOOKED. IN THIS ALGORITHM, PRIORITY IS FIRSTLY SELECTED FOR TASKS BASED ON A PRIORITIZATION ALGORITHM, AND THEN USING THE MEDIAN NUMBER TO DECIDE WHICH ONE OF THE MIN-MIN OR MAX-MIN ALGORITHMS IS TO BE USED. IT SHOULD BE NOTED THAT ACCORDING TO THE TOMMP ALGORITHMS, ITS MAKES PANE IS LOWER THAN COMPARISONS OF THE COMPARED ALGORITHMS AND IT’S SHOWN TO BE BETTER THAN THE COMPARABLE ALGORITHMS.

TODAY THERE IS A HUGE AMOUNT OF INFORMATION FROM A LOT OF VARIOUS RESOURCES SUCH AS WORLD WIDE WEB, NEWS ARTICLES, E-BOOKS AND EMAILS. ON THE ONE HAND, HUMAN BEINGS FACE A SHORTAGE OF TIME, AND ON THE OTHER HAND, DUE TO THE SOCIAL AND OCCUPATIONAL NEEDS, THEY NEED TO OBTAIN THE MOST IMPORTANT INFORMATION FROM VARIOUS RESOURCES. AUTOMATIC TEXT SUMMARIZATION ENABLES US TO ACCESS THE MOST IMPORTANT CONTENT IN THE SHORTEST POSSIBLE TIME. IN THIS PAPER A QUERY-ORIENTED TEXT SUMMARIZATION TECHNIQUE IS PROPOSED BY EXTRACTING THE MOST INFORMATIVE SENTENCES. TO THIS END, A NUMBER OF FEATURES ARE EXTRACTED FROM THE SENTENCES, EACH OF WHICH EVALUATES THE IMPORTANCE OF THE SENTENCES FROM AN ASPECT. IN THIS PAPER 11 OF THE BEST FEATURES ARE EXTRACTED FROM EACH OF THE SENTENCES. THIS PAPER HAS SHOWN THAT USE OF MORE SUITABLE FEATURES LEADS TO IMPROVED SUMMARIES GENERATED. IN ORDER TO EVALUATE THE AUTOMATIC GENERATED SUMMARIES, THE ROUGE CRITERION HAS BEEN USED.

IN RECENT YEARS, VARIOUS METHODS HAVE BEEN PRESENTED FOR ALLOCATING RESOURCES IN THE CLOUD. ONE OF THESE METHODS IS THE ALLOCATION OF MARKET-BASED RESOURCES, IN WHICH DIFFERENT MARKET MODELS USED TO EXCHANGE GOODS AND SERVICES ARE USED TO ALLOCATE RESOURCES. IN THIS THESIS, THE ISSUE OF SELECTING A SUITABLE MODEL FOR ALLOCATION OF SUPPLIERS' RESOURCES IS BASED ON ONE OF THE MARKET MODELS UNDER THE TITLE OF THE CONTINUOUS DOUBLE AUCTION MODEL WHEN PROVIDERS WITH SOURCE SHORTAGES ARE FACED AND A MODEL BASED ON THE BEST BIDIRECTIONAL AUCTION MODEL CONTINUOUSLY IN THE CLOUD TO CREATE A FEDERAL ENVIRONMENT IN ORDER TO OPTIMIZE THE SUPPLY OF RESOURCES TO ONE ANOTHER. THE RESULTS OF THE EXPERIMENT SHOW THAT THE PROPOSED MODEL FOR IMPLEMENTING FEDERAL CLOUDS BASED ON THE MOST SUITABLE CONTINUOUS DOUBLE AUCTION MODEL IN THIS THESIS IN TERMS OF SUCCESSFUL ALLOCATIONS, RESOURCE EFFICIENCY AND PROVIDER INCOME WILL BE MORE OPTIMAL THAN OTHER SELECTED MODELS OF THIS THESIS FOR PROVIDERS IN THE SINGLE CLOUD.

INTERNET OF THINGS IS THE CONCEPT OF CONNECTING EVERY DEVICE TO THE INTERNET. RFID SYSTEMS ARE USED IN IOT DUE TO THEIR BRILLIANT ADVANTAGES. HENCE, IOT FACES MANY CHALLENGES SUCH AS LIMITED ADDRESS SPACE IN RFID SYSTEMS. LOTS OF PROPOSED METHODS ARE USING DIFFERENT ALGORITHMS BASED ON ELECTRONIC PRODUCT CODE AND RFID READER TO GENERATE NEW IPV6 ADDRESSING MECHANISMS. EPC IS USED IN RFID SYSTEMS TO IDENTIFY THE PRODUCTS. DIFFERENT ADDRESSING METHODS ARE ANALYZED IN THIS STUDY. ALSO, WE PROPOSE A NEW EPC BASED IPV6 ADDRESSING MECHANISM WITH THE HELP OF READER NETID TO PROVIDE A UNIQUE AND HIERARCHICAL ADDRESS FOR RFID. THE MAIN ADVANTAGES OF OUR PROPOSED METHOD IS THAT, OUR MECHANISM IS VERY SIMPLE AND EASY TO IMPLEMENT.

RECENTLY BIG DATA ATTRACT THE RESEARCHE'S INTEREST AS A HIGH VOLUME, GENERATED VARIOUS SOURCES AND HIGH RATES GENERATED DATA. PRIVACY IS ONE OF THE MAIN ISSUES IN BIG DATA. ANONYMIZATIN IS KNOWN AS A SUITABLE SOLUTION FOR THIS PROBLEM. IN THIS PAPER THE POPULAR ANONYMIZATION TECHNIQUES ARE DESCRIBES. THESE TECHNIQUES ARE DIFFERENTS IN COMPUTATIONAL COMPLEXITY, PROCESSING TIME, AND RE-IDENTIFICATION RISK. SO IT IS EXPECTED THAT USING THIS TECHNIQUES IN BIG DATA HAVING SOME CHALLENGES. IN THIS REVIEW THESE CHALLENGES ARE ALSO DESCRIBED AND SOME OF THE MAIN RESEARCH DIRECTION FOR FUTURE WORK IS MENTIONED.

THE INTERNET HAS PROVIDED AN APPROPRIATE ENVIRONMENT FOR DIRECT COMMUNICATIONS BETWEEN CONSUMERS AND PRODUCERS IN DIFFERENT PROFESSIONS. HOWEVER, THE ADVERTISEMENT POTENTIAL OF THE INTERNET HAS NOT RECEIVED THE ATTENTION IT DESERVES AND, UNLIKE WHAT IS EXPECTED, INTERNET ADVERTISEMENTS HAVE NOT BEEN ABLE TO MEET THE NEEDS OF USERS AND ADVERTISERS, WHICH CAN BE DUE TO A LACK OF KNOWLEDGE ABOUT AUDIENCES. IN THE PRESENT RESEARCH, INTERESTS OF THE AUDIENCES AND THE PERSUASIVE FACTORS INFLUENCING THEM HAVE BEEN STUDIED IN TWO DIFFERENT AGE GROUPS SO THAT BY UNDERSTANDING THEIR INTERESTS AND PREFERENCES ADVERTISEMENTS CAN BE PRODUCED THAT MAKE AUDIENCES FEEL THAT THE ADVERTISEMENTS ARE IN LINE WITH THEIR NEEDS AND INTERESTS AND THE NEEDS OF THE SENDERS AND RECIPIENTS OF MESSAGES ARE MET AS WELL. THIS STUDY WAS CONDUCTED THROUGH A QUESTIONNAIRE DISTRIBUTED AMONG 116 INTERNET USERS AGED 15-25 AND 35-45. THE RESULTS OF THIS STUDY SHOW THAT VISUAL, TEXTUAL AND COMMUNICATIVE STIMULANTS HAVE AN EFFECT ON THE ATTITUDES AND REACTIONS OF INTERNET USERS AND THESE STIMULANTS ARE DIFFERENT IN THE AGE GROUPS 15-25 AND 35-45; THEREFORE, FOR EACH GROUP A DIFFERENT WAY OF ADVERTISEMENT AND PERSUASION SHOULD BE UTILIZED SO THAT INTERNET ADVERTISEMENTS BECOME MORE EFFICIENT.

WE LIVE IN A WORLD SURROUNDED BY NUMEROUS SOCIAL MEDIA PLATFORMS, APPLICATIONS AND WEBSITES WHICH PRODUCE VARIOUS TEXTS, IMAGES AND VIDEOS (POSTS) DAILY. PEOPLE SHARE THEIR MOMENTS WITH THEIR FRIENDS AND FAMILIES VIA THESE TOOLS TO KEEP IN TOUCH. THIS EXTENSIVENESS OF SOCIAL MEDIA HAS LED TO AN EXPANSION OF INFORMATION IN VARIOUS FORMS. IT IS DIFFICULT TO IMAGINE SOMEONE TOTALLY UNFAMILIAR WITH THESE CONCEPTS AND NOT HAVING POSTED ANY CONTENT ON A PLATFORM. ALL USERS, RANGING FROM INDIVIDUALS TO LARGE COMPANIES, WANT TO GET THE MOST OF THEIR AUDIENCES’ ATTENTION. NEVERTHELESS, THE PROBLEM IS THAT NOT ALL THESE POSTS ARE ADMIRED AND NOTICED BY THEIR AUDIENCE. THEREFORE, IT WOULD BE IMPORTANT TO KNOW WHAT CHARACTERISTICS A POST SHOULD HAVE TO BECOME THE MOST POPULAR. STUDYING THIS ENORMOUS DATA WILL DEVELOP A KNOWLEDGE FROM WHICH WE CAN UNDERSTAND THE BEST WAY TO PUBLISH OUR POSTS. TO THIS END, WE GATHERED IMAGES AND VIDEOS FROM INSTAGRAM ACCOUNTS AND WE USED SOME IMAGE/VIDEO CONTEXT FEATURES TO PREDICT THE NUMBER OF LIKES A POST OBTAINS AS A MEANING OF POPULARITY THROUGH SOME REGRESSION AND CLASSIFICATION METHODS. BY THE EXPERIMENTS WITH 10-FOLD CROSS-VALIDATION, WE GET THE RESULTS OF POPULARITY SCORE PREDICTION WITH 0.002 IN RMSE AND POPULARITY CLASS PREDICTION WITH 90.77% ACCURACY. AS WE KNOW, THIS STUDY IS THE FIRST EXPLORING OF IRANIAN INSTAGRAM USERS FOR POPULARITY PREDICTION.

INTERACTIVE RECOMMENDER SYSTEMS INVOLVE USERS IN THE PROCESS OF RECOMMENDATIONS. USERS WITH DIFFERENT SKILL LEVELS HAVE VARIOUS PREFERENCES IN THEIR TYPE OF INTERACTIONS WITH INTERACTIVE RECOMMENDER SYSTEMS. ADAPTING USERS’ TYPE OF INTERACTIONS WITH RECOMMENDER SYSTEMS ACCORDING TO THEIR EXPERIENCE LEVELS SEEMS TO BE A PROMISING IMPROVEMENT TO ENHANCE RECOMMENDATION PROCESS AND USER SATISFACTION WITH INTERACTIVE RECOMMENDER SYSTEMS. IN THIS PAPER, EXPERT USERS ARE AUTOMATICALLY RECOGNIZED BASED ON THEIR INTERACTION WITH AN INTERACTIVE RECOMMENDER SYSTEM. SHOPR SOFTWARE, AN INTERACTIVE RECOMMENDER APPLICATION FOR SMARTPHONES, IS USED TO TRACK USERS’ INTERACTIONS. USERS ARE GROUPED IN TWO CATEGORIES OF EXPERT AND NOVICE USERS BASED ON THEIR INTERACTIONS WITH SHOPR SOFTWARE IN OUR USER STUDY. TASK COMPLETION TIME IS USED TO RECOGNIZE USERS’ SKILL LEVEL. THE RESULT OF THE STUDY SHOW THAT ALL USERS RECOGNIZED AS EXPERT USERS ARE INDEED EXPERT BUT SOME EXPERT USERS WHO SPENT MORE TIME IN THE RECOMMENDER SYSTEM TO IMPROVE THEIR CHOICE OF SHOPPING CANNOT BE DETECTED BY THIS ALGORITHM. THE RESULT OF THIS RESEARCH CAN BE USED TO OFFER PERSONALIZED INTERACTION FOR EXPERT USERS IN INTERACTIVE RECOMMENDER SYSTEMS.

TEXT MINING IS ONE OF THE MAIN TASKS IN WEB RESEARCH THAT AIMS AT CLASSIFICATION OR CLUSTERING AVAILABLE TEXTS IN THE WEB FOR DIFFERENT APPLICATIONS, SUCH AS NEWS ANALYSIS AND SOCIAL NETWORK ANALYSIS. SINCE A VERY LARGE AMOUNT OF TEXTUAL DATA IS AVAILABLE ON THE WEB, REDUCING THE DIMENSION OF DATA USING FEATURE EXTRACTION TECHNIQUES PLAYS AN IMPORTANT ROLE IN IMPROVING THE EFFICIENCY AND EFFECTIVENESS OF THE TEXT MINING ALGORITHMS. VARIOUS TECHNIQUES HAVE BEEN PROPOSED IN MACHINE LEARNING TASKS THAT CAN ALSO BE APPLIED IN THE TEXT MINING DOMAIN. IN THIS PAPER WE STUDY THE AVAILABLE TECHNIQUES AND COMPARE THEIR IMPACT ON IMPROVING PERSIAN TEXT CLASSIFICATION PERFORMANCE. OUR EXPERIMENTAL RESULTS ON HAMSHAHRI CORPUS SHOWS THAT USING AN APPROPRIATE FEATURE SELECTION TECHNIQUE CAN IMPROVE THE CLASSIFICATION F-MEASURE FROM 88.12% TO 93.07%.

TRUST NETWORK CAN BE USEFUL TOOL FOR IDENTIFICATION OF THE TRUSTFUL SOURCES OF INFORMATION IN A SOCIAL WEB APPLICATION. DESPITE THE USEFULNESS OF A TRUST NETWORK, IT IS USUALLY SPARSE AS USERS ARE GENERALLY RELUCTANT TO EXPRESS THE TRUST RELATIONSHIPS. THEREFORE, ONE APPROACH TO MAKE THE TRUST NETWORK DENSER IS TO IDENTIFY THE POTENTIAL TRUST RELATIONSHIPS BETWEEN USERS AND RECOMMEND THE RELIABLE AND TRUSTFUL PARTICIPANT TO USERS. THE MAIN CONTRIBUTION OF THIS RESEARCH IS THE EXAMINATION OF THE PERFORMANCE OF LOCALLY LINEAR NEURO FUZZY (LLNF) MODEL IN THE TRUST PREDICTION CONTEXT. THEREFORE, LLNF WAS COMPARED WITH TWO CLASSIFICATION TECHNIQUES INCLUDING ANFIS AND C4.5 DECISION TREE. TO CONDUCT EXPERIMENTS, DATA OF EPINIONS NETWORK WERE USED. THE RESULTS OF EXPERIMENTS DEMONSTRATE THAT LLNF ACHIEVES THE HIGHEST PERFORMANCE IN TERMS OF AREA UNDER ROC (AUC). IN ADDITION, LLNF FOLLOWS CLOSELY C4.5 DECISION TREE REGARDING F-MEASURE. LLNF CAN BE A GOOD CANDIDATE FOR TRUST RELATIONSHIPS PREDICTION.

MOODLE AS AN OPEN SOURCE LEARNING MANAGEMENT SYSTEM (LMS) IS WIDELY ACCEPTED WORLDWIDE WITHIN ACADEMIC COMMUNITIES. IT HAS VARIOUS FACILITIES, PROVIDING BY NUMEROUS PLUGINS, WHICH ARE APPLIED BY DIFFERENT ADOPTERS. THE PURPOSE OF THIS PAPER IS ENRICHING THIS SOFTWARE BY PUBLISHING IT ON THE WEB OF DATA. MODELING THE SOFTWARE USING AN ONTOLOGY WHICH IS UNDERSTANDABLE FOR MACHINE, DESCRIBING BY RDF TRIPLES SET, AND LINKING TO RELIABLE DATASETS CAN INCREASE ITS ACCESSIBILITY AND REUSABILITY. IN ADDITION, RESPONSES OF MANY QUERIES ABOUT THIS SOFTWARE CAN BE RETRIEVED THROUGH SEMANTIC SEARCH ENGINES BY NAVIGATING SEMANTIC LINKS. THE PROPOSED APPROACH IS APPLICABLE FOR PUBLISHING ANY OTHER OPEN SOURCE SOFTWARE ON THE WEB OF DATA.

WITH THE DAILY INCREASING DEVELOPMENT OF THE INTERNET OF THINGS, INTERNET OF THINGS PLATFORM AS A SERVICE, COME INTO THE WORLD ARENA WITH DIFFERENT STRUCTURES AND CHARACTERISTICS. THIS LEADS TO MAKE THE BALANCE OF THEIR ADVANTAGES AND DISADVANTAGES, SO THAT WE CAN CHOOSE THE APPROPRIATE PLATFORM TO APPLY IT FOR ADVANCEMENT OF OUR AIMS. DATA MANAGEMENT, DATA MONITORING, NO LOSS DATA, SPEED, LOW LATENCY AND OTHER CRITERIA PLAY VERY IMPORTANT ROLE TO SELECT A GOOD PLATFORM. THEREFORE, IN THIS RESEARCH, WHILE INVESTIGATING THE QUANTITATIVE AND QUALITATIVE CRITERIA OF DIFFERENT PLATFORMS, WE HAVE TRIED TO FIND A FRAMEWORK FOR EVALUATING THEM. IN ORDER TO ACHIEVE THIS GOAL, SOME PLATFORMS SUCH AS THING SPEAK, XIVELY AND AWS IOT HAVE BEEN INTRODUCED AND ACCORDING TO BE MENTIONED CRITERIA; WE HAVE IMPLEMENTED AND TESTED DIFFERENT SCENARIOS IN THE EQUAL ENVIRONMENT AND CONDITIONS, AND EVALUATED HOW THE PLATFORMS BEHAVE ACCORDING TO THE EXISTING CRITERIA.

THE DRAMATIC INCREASE OF INTERNET USAGE FOR THE PURCHASING AND ORDERING GOODS OR SERVICES IN IRAN PROVIDES NEW CHALLENGES FOR RESEARCHERS AND MANAGERS TO UNDERSTAND CONSUMER BEHAVIOR ON THESE FASTEST GROWING E-COMMERCE BUSINESSES. AS ONE OF THE FACTORS INFLUENCING CONSUMERS PURCHASE BEHAVIOR, DECISION-MAKING STYLES ARE CRUCIAL FOR UNDERSTANDING CONSUMER SHOPPING BEHAVIOR AND FOR DEVELOPING SUCCESSFUL MARKETING STRATEGIES. THE PURPOSE OF THIS RESEARCH IS TO BETTER UNDERSTAND IRANIAN ONLINE SHOPPERS BY INVESTIGATING THEIR DECISION-MAKING STYLE AND EXPLORING THE RELATIONSHIPS BETWEEN THEIR DECISION-MAKING CHARACTERISTICS AND THEIR ONLINE SHOPPING BEHAVIOR. CONSUMER STYLE INVENTORY (CSI) DEVELOPED BY SPROLES AND KENDALL (1986) WAS ADOPTED AS A THEORETICAL BACKGROUND OF THIS STUDY, IN ORDER TO UNDERSTAND CONSUMERS’ SHOPPING ORIENTATION. DESPITE EXTENSIVE RESEARCH REGARDING CONSUMER DECISION MAKING STYLES, ALMOST NO ATTENTION HAS BEEN PAID TO UNDERSTAND IRANIAN CONSUMERS AS ONLINE SHOPPERS. THIS RESEARCH INTENDS TO FILL THE IDENTIFIED GAP BY IMPLEMENTING FACTOR ANALYSIS AND CORRELATION MATRIX. THE RESULT SHOWS THAT THERE ARE DIFFERENCES IN PURCHASING BEHAVIOR BETWEEN EXPLORED STYLES OF CONSUMER. THE RESULTS ALSO DEMONSTRATED THAT SOME OF THE CHARACTERISTICS OF THE CONSUMER STYLE INVENTORY ARE RELATED TO THE ONLINE PURCHASE BEHAVIOR. THE CONCLUSION OF THIS RESEARCH PROVIDES INFORMATION FOR MANAGERS OF SHOPPING WEBSITES ABOUT CONSUMER PURCHASING DECISIONS BASED ON THE CONSUMER STYLES INVENTORY (CSI).

THE PURPOSE OF THIS RESEARCH IS TO ANSWER THE QUESTION OF WHAT IS THE CONSTRUCT OF MEDICINE AND DOCTORS TO TWITTER USERS, AND WHAT EFFECT THE ISSUE OF THE DEATH OF ABBAS KIAROSTAMI - AS A RESULT OF THE MEDICAL ERROR IN THE TREATMENT STAGES - HAS HAD ON THE WAY IN WHICH SOCIAL CONSTRUCTION WORKS IN THIS AREA. TEXT MINING METHOD, WHICH IS A NEW METHOD THAT APPLIES TO DEAL WITH "BIG DATA", WAS USED TO ANSWER THIS QUESTION. REGARDING THE RESEARCH TOPIC, 5 TIME INTERVALS WERE CONSIDERED FOR DATA EXTRACTION. IT WAS DETERMINED DURING THE RESEARCH THAT THE VOLUME OF MEDICINE AND DOCTOR RELATED TWEETS INCREASED BY 7 IN THE TIME BETWEEN 1394 AND 1396, WHICH IS MUCH HIGHER THAN THE TOTAL VOLUME OF PERSIAN TWEETS. IN THE FOLLOWING, IT WAS FOUND THAT THE NEGATIVE SYMPTOMS, WITH A SUBSTANTIAL INCREASE, HAVE MUCH MORE REFERRAL THAN THE INCREASING VOLUME OF TWEETS IN THE MEDICAL FIELD. IT WAS ALSO FOUND THAT THE NEGATIVE WORDS, IN THE AFTERMATH OF KIAROSTAMI'S DEATH, WERE GENERALLY LINKED TO THE TERM "MEDICAL", AND THE CONSTRUCTION OF "MEDICAL ERROR" SIGN WAS ESTABLISHED AT THIS POINT. THEREFORE, DUE TO THE DEATH OF KIAROSTAMI AS ONE OF THE MOST PROMINENT PERSONALITIES IN THE COMMUNITY, AND THE CONSTRUCTION OF THEIR CONNECTION WITH MEDICAL ERROR, MEDICINE AND DOCTORS, THEY "ENTERED THE PUBLIC OPINION OF IRANIAN SOCIETY". ALSO, AS A RESULT OF THE LINKAGE BETWEEN "ERROR", "FAILURE" AND "MISTAKE" WITH "MEDICINE, " CERTAINTY OF DOCTORS AND MEDICINE’S SANCTUARY AND RESPECT HAS COLLAPSED, AND THE CONNECTION BETWEEN WORDS WITH VALUE AND VALIDITY ON THE ONE HAND AND THE MEDICINE ON THE OTHER HAND, HAS BEEN DENEUTRALIZED.

ON THE INTERNET, SEARCH ENGINES CAN RETRIEVE IMAGES WITH OPTIMUM PRECISION AND SPEED BY SEARCHING THROUGH TEXT AND WEB PAGES. IN THE IMAGE RETRIEVAL SYSTEMS, TEXT BASED IMAGE RETRIEVAL (TBIR) APPROACH (KEYWORDS), CONTENT BASED IMAGE RETRIEVAL (CBIR) AND THE COMBINATION OF THOSE APPROACHES HAVE BEEN APPLIED. IT IS WORTH NOTING THE APPLICATION OF KEYBOARDS ARE USER-FRIENDLY AND HENCE MANY RESEARCHERS PREFER TO USE THEM IN RETRIEVAL PROBLEMS. AS EXPECTATION, SUITABLE KEYWORDS WHICH ARE MUCH MORE RELATED TO IMAGE TITLES ARE VERY IMPORTANT IN RETRIEVING IMAGES. IN THIS PAPER, BASED ON WORDNET, A MODEL IS PROPOSED TO RETRIEVE TEXT-BASED IMAGE RECOGNITION ACCURACY AND THEN THE PROPOSED APPROACH HAS BEEN USED FOR CLUSTERING (I.E. K-MEANS ALGORITHM). THE SEMANTIC WEB IS RELATED TO RELATIONS AND THE DISCOVERY OF MEANINGS AND ATTEMPTS TO DISCOVER THE PATTERNS OF THE CLASS AND THE MEANINGS OF WORDS. WORDNET HAS A VARIETY OF SEMANTIC RELATIONSHIPS WITH CONCEPTS, THEREFORE IT IS POSSIBLE TO RETRIEVE FILE INFORMATION IN THE BEST WAY. WE APPLIED THE PROPOSED MODEL ON THE UIUC DATA. THE RESULTS INDICATED THE HIGH PERFORMANCE OF THE PROPOSED MODEL IN EVALUATING THE ACCURACY OF DETECTION OF TBIR CLUSTERING (>90% OVERALL ACCURACY).

IN THIS PAPER, FIRST WE GET FAMILIAR WITH KEY TERMS ON SOFTWARE ARCHITECTURE AREA. THEN WE MENTION PRINCIPAL RULES ON MICROSERVICES ARCHITECTURE. AFTER THAT, WE SHOW GENERAL INTEREST IN MICROSERVICES ARCHITECTURE COMPARING TO THE SERVICE ORIENTED ARCHITECTURE BY FETCH THE GOOGLE TREND SERVICE STATISTICS. AFTER THAT, WE DISCUSS ABOUT MONOLITHIC ARCHITECTURE MAIN ISSUES AND COMPARING MICROSERVICES ARCHITECTURE WITH SERVICE ORIENTED ARCHITECTURE. IN THE MOST IMPORTANT SECTION OF THE ARTICLE, WE HIT TECHNICAL AND EXPERIMENTAL RESULT THAT EXTRACTED FROM 21 NOTABLE DEVELOPERS AND EXPERT IN SOFTWARE INDUSTRY IN MIGRATION CAUSES TO THE MICROSERVICE ARCHITECTURE WHICH MOST IMPORTANT ONE NAMED THE ENHANCED MAINTENANCE IN LARGE SCALE. WE WILL INTRODUCE JOLIE PROGRAMMING LANGUAGE WHICH NATIVELY SUPPORT MICROSERVICE ARCHITECTURE. MICROSERVICE FORWARD CHALLENGES WILL BE DESCRIBE AND CONTAINER TECHNOLOGY ON THE SHOULDER OF DOCKER OPEN SOURCE PLATFORM WILL BE INTRODUCE. CONTAINER IS AS A COMPETITOR FOR HYPERVISOR AND WE WILL HEAR OF THEM MORE IN FUTURE. MOST IMPORTANT DESIGN PATTERN FOR MICROSERVICES WILL BE DESCRIBE WITH SOLUTION.

WITH THE DAILY-INCREASING DEVELOPMENT OF SCIENCE, VARIOUS METHODS HAVE BEEN DESIGNED TO MORE AND BETTER RETRIEVE THE SCIENTIFIC DOCUMENTS BASED ON THE NEED AND SEARCH OF USERS. FOR SOME DOCUMENTS IN THE VARIOUS SCIENTIFIC DATABASES, NO COMPLETE INFORMATION EXISTS AND THE USERS HAVE TO OBSERVE THE INSIDE OF A DOCUMENT IN ORDER TO CATCH UP WITH ITS METADATA INCLUSION THE AUTHORS, THEIR AFFILIATIONS, THE REFERENCES CITED AND ETC. THEREFORE, PRESENCE OF A METHOD BASED ON EXTRACTING THE INFORMATION BASED ON THE AVAILABLE STRUCTURAL AND GEOMETRICAL PROPERTIES IN A DOCUMENT CAN ASSIST THE RECOVERY OF RELATED AND REQUIRED DOCUMENTS. IN ADDITION, THE AVAILABLE PITFALL IN THE RELATIONAL DATABASED IS THE LACK OF DIRECT AND INDIRECT RELATIONSHIPS BETWEEN THE AVAILABILITIES OF EACH SYSTEM FOR WHICH A GRAPH-ORIENTED DATABASE CAN ESTABLISH THE RELATIONS BETWEEN THESE AVAILABILITIES. IN THIS RESPECT, AFTER EXTRACTING METADATA USING THE GEOMETRICAL PROPERTIES OF DOCUMENT AND USING A GRAPH-ORIENTED MODEL, THE RELATIONS BETWEENVARIOUS DOCUMENTS’ AVAILABILITIES SUCH AS AUTHORS, CONFERENCES, SUBJECTS AND KEYWORDS AND ETC. ARE MODELED IN ORDER TO RETRIEVE THE INFORMATION MORE EFFECTIVELY. THE EXTRACTED DATA ARE REFINED AND STORED IN THE GRAPH MODEL AND WILL BE AVAILABLE FOR A USER VIA A WEB-BASED USER INTERFACE. TO PRODUCE THE RESULTS OF EACH SEARCH, THE RELATED DOCUMENTS WILL BE RETRIEVED BASED ON THE GRAPH RELATIONS AND BE WEIGHED ACCORDING TO THE RATE OF RELATEDNESS OF EACH DOCUMENT AND THE NUMBER OF REFERENCES. IN ORDER TO EVALUATE THE PROPOSED METHOD, PUBMED DATABASE IS USED. THE RESULTS OF EXPERIMENTS SHOW THE PROPOSED METHODS OUTPERFORMED 60% IN CONTRAST TO THE PUBMED DATABASE SEARCH ENGINE IN TERMS OF THE RETRIEVED DOCUMENTS. FURTHERMORE, BASED IN THE F-MEASURE, AND NDCG- MEASURE OF PROPOSED METHOD CONSIDERABLY OUTPERFORMED THE PUBMED DATABASE SEARCH ENGINE IN TERMS OF THE QUALITY OF RETRIEVED DOCUMENTS.

NETWORK CLUSTERING IS ONE OF THE PROBLEMS THAT HAS ATTRACTED MANY RESEARCHERS IN RECENT YEARS. IN THIS ISSUE, EACH USER IS ASSOCIATED WITH A SPECIFIC COMMUNITY BASED ON THE VARIOUS FEATURES OF THE NETWORK, INCLUDING THE STRUCTURE. IN THE RECENT YEARS, DEEP LEARNING IS WIDELY USED TO EXTRACT THE FEATURE VECTOR OF NODES THEN THE VECTORS ARE USED TO FIND THE COMMUNITY OF EACH NODE. IN THIS PAPER, A NETWORK REPRESENTATION LEARNING ALGORITHM IS PRESENTED BASED ON THE INFORMATION OF THE NEIGHBORS OF EACH NODE AND COMMUNITIES ON THE NETWORK. THE RESULTS SHOW THAT OUR NODES’ REPRESENTATION METHOD OFFERS A BETTER QUALITY CLUSTERING OF SOCIAL NETWORKING USERS THAN THE PREVIOUS NETWORK REPRESENTATION LEARNING METHODS.

LINKED DATA TECHNOLOGY AS A RESULT OF GROWTH OF SEMANTIC WEB IN THE LAST DECADE, ENABLE APPLICATIONS TO EXPLOIT DATA FROM MANY DIFFERENT RESOURCES. LINKED DATA MADE IT POSSIBLE TO SEARCH DATA SEMANTICALLY OVER THE WEB, WHEREAS COMMON SEARCH ENGINES USE TEXT MATCHING APPROACHES TO FIND DESIRED DATA AND DOCUMENTS. SO THAT, QUERYING SPATIAL AND TEMPORAL FEATURES OF VARIOUS DATA BECOMES EASIER USING LINKED DATA. AIR POLLUTION IN LARGE CITIES IS ONE OF THE MOST IMPORTANT PUBLIC HEALTH ISSUES. THIS RESEARCH TAKES ADVANTAGE OF LINKED DATA SOLUTION TO ENABLE THE MULTISOURCE DATA FUSION AND ANALYTICS. WE USE DBPEDIA TO ENRICH AIR POLLUTION INFORMATION AND SPECIFY AREAS HAVING HARMFUL LEVELS OF PARTICULATE POLLUTION FOR VULNERABLE LOCATIONS SUCH AS UNIVERSITIES USING AQI INTERPOLATION MAP AND NEAREST UNIVERSITIES TO AIR MONITORING STATIONS WITH PERILOUS LEVEL. THE RESULTS OF EXPERIMENT SHOW THAT USING THE INTRINSIC POTENTIAL OF LINKED DATA TECHNOLOGY WE CAN INTERLINK INFORMATION FROM VARIOUS RESOURCES EFFICIENTLY.

LINK PREDICTION IS AN IMPORTANT TASK IN MANY APPLICATION DOMAINS. WIDESPREAD RESEARCHES HAVE BEEN DONE TO EXTRACT INFORMATION FROM NETWORK'S ENTITIES AND RELATIONS. TEMPORAL LINK PREDICTION IS A TASK OF PREDICTING UNSEEN LINKS THAT WILL BE FORMED IN THE FUTURE BASED ON DIFFERENT SNAPSHOTS OF THE NETWORK. THIS PAPER PROPOSES A FRAMEWORK IN WHICH THE CONCERNS AND CHALLENGES OF TEMPORAL LINK PREDICTION ARE DISCUSSED. ALL MAJOR AND RECENT METHODOLOGIES IN TEMPORAL LINK PREDICTION ARE CLASSIFIED. THIS PRESENTED CLASSIFICATION IS ANALYZED BASED ON THE DISCUSSED CHALLENGES. ACCORDINGLY, THIS FRAMEWORK PROVIDES AN APPROPRIATE PLATFORM FOR COMPARING AND ANALYZING DIFFERENT APPROACHES AND CHALLENGES, THAT WILL ENCOURAGE FUTURE RESEARCH IN DEVELOPING MORE POWERFUL METHODS.

WEB PERSONALIZATION REFERS TO A SET OF OPERATIONS THAT MODIFY THE WEB EXPERIENCE FOR A SINGLE OR A GROUP OF USERS BY PROVIDING DYNAMIC RECOMMENDATIONS BASED ON THEIR BEHAVIOR PATTERNS. ONE OF THE CHALLENGES OF IMPROVING THE PERFORMANCE OF WEB PERSONALIZATION ALGORITHMS IS THE SIMULTANEOUS USE OF STRUCTURAL DATA AND USER BROWSING INFORMATION. IN THIS PAPER, AFTER INTRODUCING A WEIGHING CRITERION, WE USE A NEW ALGORITHM BASED ON THE GRAPH STRUCTURE BETWEEN WEB PAGES TO OFFER PAGES TO USERS. THE PROPOSED ALGORITHM COMBINES THE LINK GRAPH STRUCTURE AND THE COLLECTION OF HEAVY ITEM SETS AND GENERATES NEW ASSOCIATION RULES BASED ON WEIGHTED ITEMS, OR THE SO-CALLED WEIGHTED ASSOCIATION RULES. IN THIS ALGORITHM, THE PAGES ARE WEIGHTED BASED ON A NEW MEASURE THAT REFLECTS THE INTEREST OF USERS AND THE SIGNIFICANCE OF THE PAGE. WEBPAGE RECOMMENDATION IS PERFORMED BASED ON HEAVY DATA. MORE SPECIFICALLY, THE TRANSACTION DATA SET IS ANALYZED USING A FREQUENT-PATTERN (FP) TREE ALGORITHM, HEAVY ITEM SETS ARE GENERATED SEPARATELY, THE PURITY AND CONNECTIVITY OF INTERACTING NEIGHBOR AND NON-NEIGHBOR ITEMS ARE PROCESSED BY THE EXTENDED VALENCY ALGORITHM, AND FINALLY, THE ASSOCIATION RULES ARE PRODUCED FOR WEBPAGE RECOMMENDATION. THE PROPOSED METHOD FOR WEBPAGE RECOMMENDATION IS CALLED THE EXTENDED HEAVY VALENCY ALGORITHM. IN THE PROPOSED METHOD, THE WEB STRUCTURE IS ANALYZED USING THE PRINCIPLES OF GRAPH THEORY AND AFTER EXAMINING THE MODES OF THE GRAPH STRUCTURE, THE WEIGHTS ARE CALCULATED BASED ON THE CONCEPTS OF CONNECTIVITY AND PURITY OF NEIGHBOR AND NON-NEIGHBOR ITEMS AT THE NODES (LINKS). THE PROPOSED WEIGHTING FORMULA ALLOWS US TO CALCULATE THE VALUE OF A LINK OR NODE WITH A RELATIVELY HIGH PRECISION. THE EXACT VALUE OF THE PROPOSED ALGORITHM FOR THE MINIMUM BACKUP VALUE IS BETWEEN 5 TO 20, 70 TO 82 PERCENT.

NOWADAYS MICROSERVICE, AS ONE OF THE MOST IMPORTANT ARCHITECTURAL APPROACHES TOWARDS CLOUD COMPUTING, HAS CAUGHT THE ATTENTION OF MANY DEVELOPERS. TO GIVE A SIMPLE DEFINITION OF MICROSERVICE, IT COULD BE SAID: EACH MICROSERVICE IS COMPLETELY INDEPENDENT, AND IMPLEMENTS A PART OF THE BUSINESS, WHICH IS COMPOSED OF SEVERAL MICROSERVICES. EACH MICROSERVICE COULD BE DEPLOYED, UPDATED, AND SCALED, WITHOUT ANY IMPACT ON OTHER MICROSERVICES, AND IT IS ALL AUTOMATED. AMONG AGILE METHODS, CONTINUOUS DELIVERY HAS PLAYED AN IMPORTANT ROLE IN DEVELOPMENT PROCESS OF MICROSERVICE-BASED SYSTEMS. CONTINUOUS DELIVERY PROVIDES FASTER DELIVERY OF CHANGES AND FASTER GETTING CUSTOMER’S FEEDBACKS. CONTINUOUS DELIVERY CONSISTS OF MANY SECTIONS, ONE OF WHICH IS SOFTWARE TEST. ONE OF THE CHALLENGES OF AUTOMATED DEPLOYING OF NEW RELEASES TO PRODUCTION ENVIRONMENT, IS SOFTWARE RELIABILITY, THAT IN CASE IT IS BREACHED, THE BENEFICIARIES WOULD SUFFER CONSIDERABLE LOSSES. REGRESSION TEST IS ONE OF THE TESTS USED FOR ENSURING RELIABILITY, WHICH COMPARES TWO SYSTEM VERSIONS BASED ON VARIOUS METRICS. THIS PAPER PROPOSES AN AUTOMATED METHOD IN RUNNING THIS TEST, WHICH PLACES REGRESSION TEST IN CONTINUOUS DELIVERY STEPS, WHICH TESTS OPERABILITY OF THE LAST DEVELOPED VERSION AS A BLACK BOX, AND PREVENTS WRITING TEST UNIT. FINALLY, MICROSERVICE DEVELOPERS COULD ENSURE THE OPERABILITY OF THE DEVELOPED MICROSERVICE DEPENDENCIES THROUGH INVESTIGATING OBTAINED COMPARISONS.

CLOUD COMPUTING PROVIDES ITS USERS THE ABILITY TO LEVERAGE COMPUTATIONAL RESOURCES BASED ON THEIR DEMAND AND ACCORDING TO THEIR REQUIREMENTS. ONE OF THE BIGGEST ADVANTAGES OF SUCH AN APPROACH IS THAT THE WASTE IN COMPUTATIONAL RESOURCES WOULD BE REDUCED TO A MINIMUM. IN ORDER TO PROVIDE A PROPER RESPONSE TO THE NEEDS OF ITS LABORATORIES, COMPUTER ENGINEERING DEPARTMENT OF IRAN UNIVERSITY OF SCIENCE AND TECHNOLOGY HAS DECIDED TO CREATE AN INFRASTRUCTURE AS A SERVICE CENTER WELL-KNOWN IN THE CLOUD COMPUTING PARADIGM. AT ITS CORE, THE CENTER USES OPENSTACK AS ONE OF THE MOST WIDELY-ACCEPTED AND COMMONLY USED OPEN SOURCE PLATFORMS FOR MANAGING INFRASTRUCTURAL RESOURCES. IN THIS PAPER, WE WILL REVIEW THE STRATEGIC DECISIONS BEING MADE BY THE MAJOR CONTRIBUTORS OF THE CENTER. TO THIS END, WE WILL FIRST DISCUSS ABOUT THE FUNDAMENTAL CONCEPTS IN CLOUD COMPUTING AND MOVE ON TO EXCHANGE VIEWS ON THE PIPELINES, CHALLENGES, AND EXPERIENCES GAINED THROUGHOUT THE PROCESS.

THE INCREASING GROWTH OF WEB HAS GIVEN PEOPLE THE ABILITY TO SIMPLY EXPRESS THEIR OPINION AND KNOW OTHERS’ OPINION. MINING VIEWPOINTS AND OPINION OR SENTIMENT ANALYSIS IS CONSIDERED AS A SUBFIELD OF TEXT MINING AND ITS MAIN GOAL IS TO FIND WRITER’S OPINION ABOUT A TOPIC. MEETING THIS GOAL IS NOT A SIMPLE TASK SINCE EMOTIONS IN A SENTENCE OR A PHRASE ARE USUALLY RECOGNIZED BY COMBINING EMOTIONS OF ITS WORDS. IN THIS PAPER, WE CONCENTRATE ON BIPOLAR TERMS WHICH ARE THOSE PHRASES CONTAINING AT LEAST ONE POSITIVE AND ONE NEGATIVE WORD. IN ORDER TO CONSIDER BIPOLAR TERMS, PHRASES WITH OPPOSING POLARITY ARE FIRST EXTRACTED FROM PERSENT DATASET THEN, BASED ON THE WORDS OF THESE PHRASES AND THEIR POLARITY IN THE SENTENCE THE FINAL SCORE IS COMPUTED. THEN, THE SCORE OF EACH SENTENCE IS CALCULATED USING CNRC LEXICON AND MAXIMUM OF ABSOLUTE VALUES, DIFFERENCE, AND AVERAGE METHODS WITH AND WITHOUT CONSIDERING BIPOLAR TERMS. THE RESULTS OF IMPLEMENTATION OF THE PROPOSED METHOD SHOW THAT EMPLOYING BIPOLAR TERMS IMPROVES THE LEXICON-BASED APPROACH FOR BOTH POLARITY DETECTION AND SCORE PREDICTION PROBLEMS.

THE PURPOSE OF THIS RESEARCH IS TO INVESTIGATE THE CREDIBILITY OF WEB-BASED INFORMATION RESOURCES IN RELATION TO THE RESEARCH CARRIED OUT AND THE VARIOUS LEVELS THAT THESE STUDIES HAVE ADDRESSED. FOR THIS PURPOSE, RESEARCHES THAT HAVE BEEN PERFORMED IN THE NAME OF MODEL, FRAMEWORK, METHOD, THEORY, ETC. HAVE BEEN INVESTIGATED. THE METHOD USED IN THIS RESEARCH IS CONTENT ANALYSIS AND THE INFORMATION GATHERING TOOL IS THE LIBRARY METHOD. THE RESULTS OF THIS RESEARCH SHOWED THAT AMONG THE RESEARCHES CARRIED OUT, 9 RESEARCHES OF PETTY AND CACIOPPA, TSENG AND FOGG, FRITCH AND CROMWELL, WATHEN AND BURKELL, FOGG, MEOLA, METZGER, RIEH AND DANIELSON AND HILLIGOSS AND RIEH CAN BE INTRODUCED AS MODELS.. THE RESULTS ALSO SHOWED THAT CREDIBILITY ASSESSMENT STUDIES OF WEB-BASED INFORMATION RESOURCES TOOK PLACE AT FOUR LEVELS OF USER, WEBSITE, SOURCE AND MESSAGE. AT EACH OF THESE LEVELS, THERE ARE SUGGESTED CRITERIA FOR EVALUATING THESE RESOURCES WHICH AT THE LEVEL OF THE USER, SUBJECT KNOWLEDGE; AT THE LEVEL OF THE WEB SITE, BEING UP TO DATE; AT THE LEVEL OF THE SOURCE, THE SOURCE'S SPECIALIZED KNOWLEDGE; AND AT THE MESSAGE LEVEL, HAVING THE DOCUMENT WERE THE MOST IMPORTANT CRITERIA FOR EACH LEVEL.

EMOTIONS AS ONE OF THE IMPORTANT ELEMENTS OF HUMAN NATURE ARE A PART OF EVERYDAY COMMUNICATIONS OF PEOPLE. WE CAN DISTINGUISH PERSON'S EMOTIONS FROM SOME OUTCOME BEHAVIORS SUCH AS SPEECH, FACIAL EXPRESSION, BODY MOVEMENTS AND GESTURES. ANOTHER OUTCOME BEHAVIOR THAT REFLECTS THE INNER STATES OF THE PERSON IS HIS/HER GRAMMAR AND WRITTEN METHOD. BECAUSE NOWADAYS, PEOPLE ARE MORE LIKELY TO USE TEXTUAL TOOLS TO MAKE CONNECTION, EMOTION EXTRACTION FROM THE TEXT HAS ATTRACTED A LOT OF ATTENTION. THIS PAPER PROVIDES A FRAMEWORK FOR THE EXTRACTION OF EMOTIONS IN THE TEXT. BY CONSIDERING THAT A TEXT MAY CONTAIN MORE THAN ONE EMOTION THAT ONLY ONE OF THEM IS TEXT DOMINANT EMOTION, OUR PROPOSED METHOD, HAS MODELED EMOTION EXTRACTION PROBLEM AS A MULTI-LABEL CLASSIFICATION PROBLEM BY REMOVING THE FIXED BOUNDARIES OF EMOTIONS, AND RECOGNIZES ALL THE EXISTING EMOTIONS IN THE SENTENCE AND ALSO DOMINANT EMOTION. THE PROPOSED METHOD EXTRACTS EMOTIONS BY USING STRUCTURAL AND SEMANTIC INFORMATION IN THE SENTENCE, LINGUISTIC INFORMATION AND MACHINE LEARNING TECHNIQUES. THE EXPERIMENTS HAVE BEEN DONE ON MULTI-LABEL DATASET CONTAINS 629 SENTENCES WITH EIGHT EMOTIONAL CATEGORIES. BASED ON THE RESULTS, OUR PROPOSED METHOD, COMPARED WITH USED MULTI-LABEL LEARNING METHODS (BR, RA K EL, ML K NN) HAVE SHOWN A BETTER PERFORMANCE.

WIRELESS MOBILE NETWORK IS SUSCEPTIBLE TO VARIOUS ATTACKS DUE TO ITS CHARACTERISTICS AND WIRELESS MODE OF COMMUNICATION. PRIVACY PRESERVING OR USER ANONYMITY IS NECESSARY TO PROTECT THE PRIVACY OF THE USER BY ENSURING THAT THE ATTACKERS ARE NOT ABLE TO RETRIEVE SENSITIVE INFORMATION OF USERS. IN THIS PAPER, A TOKEN BASED PRIVACY PRESERVING AND AUTHENTICATION TECHNIQUE FOR WIRELESS MOBILE NETWORKS IS PROPOSED. IN THIS TECHNIQUE, A TOKEN IS USED TO CARRY THE MESSAGE BETWEEN THE SENDER AND RECEIVER THROUGH DUMMY NODES SELECTED BY THE BASE STATION. THIS TOKEN IS ENCRYPTED SUCH THAT ONLY THE SENDER AND RECEIVER IS CAPABLE OF RETRIEVING THE MESSAGE BEING TRANSMITTED. THUS, IT BECOMES A HARD TASK FOR THE ATTACKER TO IDENTIFY THE USER NODE SINCE THE NODE INFORMATION IS ENCRYPTED WITHIN THE TOKEN. HENCE THIS TECHNIQUE CAN EFFICIENTLY PRESERVE THE PRIVACY OF THE USERS AND ENHANCE THE NETWORK OPERATION. BY SIMULATION RESULTS, IT IS SHOWN THAT THE PROPOSED TECHNIQUE IMPROVES THE RELIABILITY AND REDUCES THE COMMUNICATION OVERHEAD.