scholarly journals Location-Dependent Query Processing: Semantic Cache for Real-Time Smart City Analytics

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Rabia Hasan ◽  
Waseem Shehzad ◽  
Ejaz Ahmed ◽  
Hasan Ali Khattak ◽  
Ahmed S. AlGhamdi ◽  
...  
Keyword(s):  
Query Processing ◽  
Research Work ◽  
Processing System ◽  
Mobile User ◽  
Location Based Services ◽  
Prediction Algorithm ◽  
User Query ◽  
Novel Approach ◽  
Deep Integration ◽  
Location Dependent Query

With the advent of wireless sensor networks and their deep integration with the world have enabled users worldwide to achieve benefits from location-based services through mobile applications, the problems such as low bandwidth, high network traffic, and disconnections issues are normally extracted from mobile services. An efficient database system is required to manage mentioned problems. Our research work finds the probability of user’s next locations. A mobile user (query issuer) changes its position when performing a specific mobile search, where these queries change and repeat the search with the issuer position. Moreover, the query issuer can be static and may perform searches with varying conditions of queries. Data is exchanged with mobile devices and questions that are formulated during searching for query issuer locations. An aim of the research work is achieved through effectively processing of queries in terms of location-dependent, originated by mobile users. Significant studies have been performed in this field in the last two decades. In this paper, our novel approach comprise of usage of semantic caches with the Bayesian networks using a prediction algorithm. Our approach is unique and distinct from the traditional query processing system especially in mobile domain for the prediction of future locations of users. Consequently, a better search is analyzed using the response time of data fetch from the cache.

scholarly journals A Novel Location Prediction Algorithm of Mobile Users For Cellular Networks

2015 ◽  
pp. 58
Author(s):  
Giang Minh Duc ◽  
Le Manh ◽  
Do Hong Tuan
Keyword(s):  
Execution Time ◽  
Mobile Network ◽  
Mobile User ◽  
Location Based Services ◽  
Prediction Algorithm ◽  
Second Phase ◽  
Location Prediction ◽  
Mobility Patterns ◽  
Two Phase ◽  
Computing Systems

Predicting the location of a mobile user is one of  the  important  issues  in  mobile  computing  systems. Applications of the location prediction include adjusting the bandwidth of the mobile network, the location based services  (LSB),  smart  handover,  etc.  However,  the applications  require  the  execution  time  of  the  User Mobility  Patterns  Mining  (UMPMining)  algorithm  be instantaneous.  In  this  paper,  we  propose  a  new algorithm named Find_UMP for mining next location of a  mobile  user.  Our  algorithm  includes  two  phase  as follows.  In  the  first  phase  (Find_UMP_1),  we  make  to reduce the complexity of the UMPMining algorithm. In the second phase (Find_UMP_2), we perform to reduce the  number  of  transactions  of  the  paths  database. Results  of  our  experiments  show  that  our  proposed algorithm  outperforms  the  UMPMining  algorithm  in terms of the execution time.

Green synthesis, characterization of silver sulfide nanoparticles and antibacterial activity evaluation

2019 ◽  
Author(s):  
Chem Int
Keyword(s):  
Antibacterial Activity ◽  
Large Scale ◽  
Research Work ◽  
Silver Sulfide ◽  
Morphological Properties ◽  
Effective Diameter ◽  
Novel Approach ◽  
Transmission Electron ◽  
Green Route ◽  
Silver Sulfide Nanoparticles

This research work presents a facile and green route for synthesis silver sulfide (Ag2SNPs) nanoparticles from silver nitrate (AgNO3) and sodium sulfide nonahydrate (Na2S.9H2O) in the presence of rosemary leaves aqueous extract at ambient temperature (27 oC). Structural and morphological properties of Ag2SNPs nanoparticles were analyzed by X-ray diffraction (XRD) and transmission electron microscopy (TEM). The surface Plasmon resonance for Ag2SNPs was obtained around 355 nm. Ag2SNPs was spherical in shape with an effective diameter size of 14 nm. Our novel approach represents a promising and effective method to large scale synthesis of eco-friendly antibacterial activity silver sulfide nanoparticles.

scholarly journals Extracting Stops from Spatio-Temporal Trajectories within Dynamic Contextual Features

2021 ◽  
Vol 13 (2) ◽  
pp. 690
Author(s):  
Tao Wu ◽  
Huiqing Shen ◽  
Jianxin Qin ◽  
Longgang Xiang
Keyword(s):  
Moving Objects ◽  
Major Effect ◽  
Location Based Services ◽  
Trajectory Data ◽  
The Road ◽  
Contextual Features ◽  
Novel Approach ◽  
Gps Trajectories ◽  
Time Distance ◽  
Spatio Temporal

Identifying stops from GPS trajectories is one of the main concerns in the study of moving objects and has a major effect on a wide variety of location-based services and applications. Although the spatial and non-spatial characteristics of trajectories have been widely investigated for the identification of stops, few studies have concentrated on the impacts of the contextual features, which are also connected to the road network and nearby Points of Interest (POIs). In order to obtain more precise stop information from moving objects, this paper proposes and implements a novel approach that represents a spatio-temproal dynamics relationship between stopping behaviors and geospatial elements to detect stops. The relationship between the candidate stops based on the standard time–distance threshold approach and the surrounding environmental elements are integrated in a complex way (the mobility context cube) to extract stop features and precisely derive stops using the classifier classification. The methodology presented is designed to reduce the error rate of detection of stops in the work of trajectory data mining. It turns out that 26 features can contribute to recognizing stop behaviors from trajectory data. Additionally, experiments on a real-world trajectory dataset further demonstrate the effectiveness of the proposed approach in improving the accuracy of identifying stops from trajectories.

Trilateration approaches for seamless out-/indoor GNSS and Wi-Fi smartphone positioning

2019 ◽  
Vol 13 (1) ◽  
pp. 47-61
Author(s):  
Guenther Retscher ◽  
Jonathan Kleine ◽  
Lisa Whitemore
Keyword(s):  
Inertial Sensors ◽  
Low Cost ◽  
Ground Truth ◽  
Mobile User ◽  
Location Based Services ◽  
Raspberry Pi ◽  
Indoor Environments ◽  
Point Location ◽  
Point Determination ◽  
The Relationship

Abstract More and more sensors and receivers are found nowadays in smartphones which can enable and improve positioning for Location-based Services and other navigation applications. Apart from inertial sensors, such as accelerometers, gyroscope and magnetometer, receivers for Wireless Fidelity (Wi-Fi) and GNSS signals can be employed for positioning of a mobile user. In this study, three trilateration methods for Wi-Fi positioning are investigated whereby the influence of the derivation of the relationship between the received signal strength (RSS) and the range to an Access Points (AP) are analyzed. The first approach is a straightforward resection for point determination and the second is based on the calculation of the center of gravity in a triangle of APs while weighting the received RSS. In the third method a differential approach is employed where as in Differential GNSS (DGNSS) corrections are derived and applied to the raw RSS measurements. In this Differential Wi-Fi (DWi-Fi) method, reference stations realized by low-cost Raspberry Pi units are used to model temporal RSS variations. In the experiments in this study two different indoor environments are used, one in a laboratory and the second in the entrance of an office building. The results of the second and third approach show position deviations from the ground truth of around 2 m in dependence of the geometrical point location. Furthermore, the transition between GNSS positioning outdoors and Wi-Fi localization indoors in the entrance area of the building is studied.

A declarative query processing system for nowcasting

2016 ◽  
Vol 10 (3) ◽  
pp. 145-156 ◽  
Author(s):  
Dolan Antenucci ◽  
Michael R. Anderson ◽  
Michael Cafarella
Keyword(s):  
Query Processing ◽  
Processing System

Cloud Query Processing System for Big Data Management

2017 ◽  
pp. 263-288
Author(s):  
Bhavani Thuraisingham ◽  
Mohammad Mehedy Masud ◽  
Pallabi Parveen ◽  
Latifur Khan
Keyword(s):  
Big Data ◽  
Data Management ◽  
Query Processing ◽  
Processing System

scholarly journals Numerical Investigation of Ferrofluid Preparation during In-Vitro Culture of Cancer Therapy for Magnetic Nanoparticle Hyperthermia

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5545 ◽  
Author(s):  
Izaz Raouf ◽  
Piotr Gas ◽  
Heung Soo Kim
Keyword(s):  
Numerical Model ◽  
Cancer Therapy ◽  
Magnetic Nanoparticle ◽  
Research Work ◽  
Thermal Response ◽  
Linear Response Theory ◽  
Novel Approach ◽  
Magnetic Nanoparticle Hyperthermia

Recently, in-vitro studies of magnetic nanoparticle (MNP) hyperthermia have attracted significant attention because of the severity of this cancer therapy for in-vivo culture. Accurate temperature evaluation is one of the key challenges of MNP hyperthermia. Hence, numerical studies play a crucial role in evaluating the thermal behavior of ferrofluids. As a result, the optimum therapeutic conditions can be achieved. The presented research work aims to develop a comprehensive numerical model that directly correlates the MNP hyperthermia parameters to the thermal response of the in-vitro model using optimization through linear response theory (LRT). For that purpose, the ferrofluid solution is evaluated based on various parameters, and the temperature distribution of the system is estimated in space and time. Consequently, the optimum conditions for the ferrofluid preparation are estimated based on experimental and mathematical findings. The reliability of the presented model is evaluated via the correlation analysis between magnetic and calorimetric methods for the specific loss power (SLP) and intrinsic loss power (ILP) calculations. Besides, the presented numerical model is verified with our experimental setup. In summary, the proposed model offers a novel approach to investigate the thermal diffusion of a non-adiabatic ferrofluid sample intended for MNP hyperthermia in cancer treatment.

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