Mobile Location Indexing Based On Synthetic Moving Objects

Today, the number of researches based on the data they move known as mobile objects indexing came out from the traditional static one. There are some indexing approaches to handle the complicated moving positions. One of the suitable ideas is pre-ordering these objects before building index structure. In this paper, a structure, a presorted-nearest index tree algorithm is proposed that allowed maintaining, updating, and range querying mobile objects within the desired period. Besides, it gives the advantage of an index structure to easy data access and fast query along with the retrieving nearest locations from a location point in the index structure. A synthetic mobile position dataset is also proposed for performance evaluation so that it is free from location privacy and confidentiality. The detail experimental results are discussed together with the performance evaluation of KDtree-based index structure. Both approaches are similarly efficient in range searching. However, the proposed approach is especially much more save time for the nearest neighbor search within a range than KD tree-based calculation

Range Tree Based Indexing of Mobile Tracking System

With advances in location-based services, indexing the need for storing and processing continuously moving data arises in a wide variety of applications. Some traditional spatial index structures are not suitable for storing these moving positions because of their unbalance structure. Searching an unbalanced tree may require traversing an arbitrary and unpredictable number of nodes and pointers. Presorting before tree structure is one of the ways of building a balanced two dimensional tree. In this paper, we proposed Presort Range tree that is suitable for moving objects with the dynamic range query. Moreover, with extending mobile technology, tracking the changing position of devices becomes a new challenge. The current location of each user would always be known at the server side whereas it would create a problem. If the mobile movements are small and frequent, at that time unnecessary updates would be performed at the server. In this paper, we also proposed Hybrid Update Algorithm to reduce the server update cost greatly

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Efficient Performance Optimization on Yarn-Based MapReduce Hadoop Framework

Apache Hadoop exposes 180+ configurationparameters for all types of applications and clusters,10-20% of which has a great impact on performanceand efficiency of the execution. The optimalconfiguration settings for one application may not besuitable for another one leading to poor systemresources utilization and long application completiontime. Further, optimizing many parameters is a timeconsuming and a challenging job becauseconfiguration parameters and search space are huge,and users require good knowledge of Hadoopframework. The issue is that the user should adjust atleast the important parameters, e.g. the number ofmap tasks that can run in parallel for a givenapplication. This paper introduces the parameteroptimization algorithm to the key application levelparameter based on input data size and dynamicresource capabilities at any given time for a givenapplication to improve execution time and resourceutilization with nearly zero optimization overhead

Discovering the Association Rules in Data Cube from Web Server Log Files

Analyzing and exploring regularities in thebehavior of the web page reader is imprinted onthe web server log files can improve systemperformance; enhance the quality and delivery ofInternet information services to the end user.Webmining techniques can use to search for webaccess patterns, web structures, regularity anddynamics of web contents. OLAP (OnlineAnalytical Processing)-based association rulemining integrates OLAP and association rulemining that facilitates flexible mining ofinteresting knowledge in data cube because it canbe performed at multilevel or multidimensional indata cube.In this system, Web log database is usedto store web log records of log files collected fromweb server. And web log database are constructedvia a process of data cleaning, datatransformation. Data cube will be implementedfrom log files.Generating rules from data cubewill reduce counting phase of association rulesince it stores the pre-computed countvalues.Frequent patterns are generated based ondimensions of the web logs instead of page itemsets.The generated frequent patterns can later beapplied to improve web site management, decisionmaking process

Improving Hadoop MapReduce Performance Using Speculative Execution Strategy in a Heterogeneous Environment

MapReduce is currently a parallel computingframework for distributed processing of large-scaledata intensive application. The most importantperformance metric is job execution time but it canbe seriously impacted by straggler machines.Speculative execution is a common approach for thisproblem by backing up slow tasks on alternativemachines. Some schedulers with speculativeexecution have been proposed but they have someweaknesses:(i) they cannot calculate the progressrate accurately because the progress scores of thephases are set to constant values which may betotally different for heterogeneous environment, (ii)they define the stragglers by specifying a staticthreshold value which calculates the temporaldifference between an individual task and theaverage task progression. To get the betterperformance, this paper proposes an algorithmidentifying the stragglers by the more accurateprogress of each job based on its own historicalinformation and using a dynamic threshold valueadjusting the continuously varying environmentautomatically

Implementing Mobile Tracking System on Disaster Notification

With advances in location based services,tracking the changing position of devices is becominga new challenge. Mobile devices are the mosteffective and convenient communication tools whichare not restricted by time and place. In this paper,the main service task is the timely delivery of possiblydisaster information to mobile devices which are inthe imminent disaster area.The system finds whether a mobile is within adefined disaster area using its GPS coordinates. Thesystem architecture is built for sending notification tomobile devices in disaster service area. This systemalso proposes an algorithm for client side whichcombines the time and distance-based locationupdateapproaches. This proposed algorithm will aidto get last current location and reduce server updatecost

Message Scheduling Delivery on Disaster Notification System

Natural disaster cannot be prevented, but itsimpacts can be eliminated or reduced. Mobiledevices are the most effective and convenientcommunication tools which are not restricted by timeand place. In this paper, the main service task is thetimely delivery of possibly disaster information tomobile devices which are in the imminent disasterarea. The system finds whether a mobile is within adefined disaster area using its GPS coordinates. Thesystem architecture is built for sending notificationsto mobile devices in disaster area. This system alsoproposes an algorithm for server side messagescheduling based on queuing theory. This algorithmcan handle queuing of messages and delivery to thetarget devices

Extracting User’s Interests from Web Log Data for Implementing Adaptive Education System

As World Wide Web is a repository of web pagesand links, it provides not only useful information forthe Internet users but also becomes delivery platformfor searching and surfing day by day. Webpersonalization is the process of customizing a Website to the needs of each specific user or set of users,taking advantage of the knowledge required throughthe analysis of the user’s navigation behavior.Integration usage data with user profile dataenhances the personalization process. In this paper,the adaptive educational system is developed toextract user’s interests from web log data andimplemented the recommender system to suggest thenext links for studying next. The SPADE (SequentialPattern Discovery using Equivalence classes) is usedin finding semantic association rules to overcome theburden of repeated database scans while calculatingthe support of the candidates and DynamicLCS(Longest Common Subsequence) is applied inmapping with users’ current session and associationrules which are generated from the SPADE algorithm.In the proposed system, the teacher and the contentdeveloper are performed their tasks to become themost accurate information for the bestrecommendations by using domain ontology. Themain objective of this proposed system is to analyzethe student’s behavioral patterns to recommend thenew links that best match the individual user’s preferences