A New RSSI-based Centroid Localization Algorithm by Use of Virtual Reference Tags

A good design of node location is critical for efficient and effective wireless communications. This paper presents an improved algorithm, in order to solve the low localization accuracy caused by traditional centroid algorithm. The improved algorithm combined with VIRE system and traditional centroid algorithm. The VIRE algorithm is introduced and the signal propagation model is utilized to construct virtual reference tags in the location area. Simulation shows that this further developed algorithm has further improved the accuracy of positioning up to 35.12% compared to the traditional centroid algorithm. It is concluded that this algorithm can further improve the locating accuracy in comparison with the original centroid algorithm

The level of Marzano higher-order thinking skills among polytechnic students

This study aims to identify polytechnic students' level of Marzano Higher-Order Thinking Skills (HOTS) based on two dimensions, 'Extension and Refinement of Knowledge' and 'Meaningful Use of Knowledge,' and to analyze the difference in the students' level of Marzano HOTS based on these two dimensions depending on the students' demographic factors. This study design was a survey using quantitative methods. A total of 313 students were randomly selected as the survey sample. A questionnaire in the form of closed-ended questions was used as the research instrument. Data were analyzed using frequency percentage and MANOVA test. The findings showed no significant differences in the eight HOTS in the dimension of 'Extension and Refinement of Knowledge' with the gender and socio-economic status (SES) factors. However, there were significant differences in the eight HOTS with the academic achievement factor. Meanwhile, based on the dimension of 'Meaningful Use of Knowledge,' the findings showed no significant differences in the five HOTS in this dimension with the gender and academic achievement factors. The paper includes implications of the Higher-Order Thinking Skills (HOTS) for students to improve their academic performance. In future research, the authors can further identify university students' HOTS levels in the technical area

IGAA: An Efficient Optimization Technique for RFID Network Topology Design in Internet of Things

[[abstract]]Most RFID applications in the Internet of Things (IoTs) use multiple readers to read the IDs of multiple tags and form the RFID network. In such a network, unguarded reader deployment may generate over-crowded readers, cause interferences and, as a result, increases the deployment cost while degrading tag detection. Seeing that desirable reader deployment is crucial for RFID system performance, this paper introduces an optimization-based IGAA approach which outperforms existing RFID topology designs by turning up more favorable reader deployment and system performance. The new approach employs an advanced multi-objective fitness function and improved genetic annealing algorithms (GAA) to pursue a better RFID topology design. By involving an improved gene-stirring operation to help preserve good genes and locate optimal solutions for reader deployment, it is simple in operation but effective in practice. Experimental evaluation shows that when compared with related approaches, IGAA can yield better solution quality with less search time.[[notice]]補正完畢[[incitationindex]]EI[[booktype]]紙本[[booktype]]電子

Robust modeling and planning of radio-frequency identification network in logistics under uncertainties

To realize higher coverage rate, lower reading interference, and cost efficiency of radio-frequency identification networkin logistics under uncertainties, a novel robust radio-frequency identification network planning model is built and arobust particle swarm optimization is proposed. In radio-frequency identification network planning model, coverage isestablished by referring the probabilistic sensing model of sensor with uncertain sensing range; reading interference iscalculated by concentric map–based Monte Carlo method; cost efficiency is described with the quantity of readers. Inrobust particle swarm optimization, a sampling method, the sampling size of which varies with iterations, is put forwardto improve the robustness of robust particle swarm optimization within limited sampling size. In particular, the exploita-tion speed in the prophase of robust particle swarm optimization is quickened by smaller expected sampling size; theexploitation precision in the anaphase of robust particle swarm optimization is ensured by larger expected sampling size.Simulation results show that, compared with the other three methods, the planning solution obtained by this work ismore conducive to enhance the coverage rate and reduce interference and cost.info:eu-repo/semantics/publishedVersio

Enchancing RFID data quality and reliability using approximate filtering techniques

Radio Frequency Identification (RFID) is an emerging auto-identification technology that uses radio waves to identify and track physical objects without the line of sight. While delivering significant improvements in various aspects, such as, stock management and inventory accuracy, there are serious data management issues that affect RFID data quality in preparing reliable solutions. The raw read rate in real world RFID deployments is often in the 60-70% range and naturally unreliable because of redundant and false readings. The redundant readings result in unnecessary storage and affect the efficiency of data processing. Furthermore, false readings that focused on false positive readings generated by cloned tag could be mistakenly considered as valid and affects the final results and decisions. Therefore, two approaches to enhance the RFID data quality and reliability were proposed. A redundant reading filtering approach based on modified Bloom Filter is presented as the existing Bloom Filter based approaches are quite intricate. Meanwhile, even though tag cloning has been identified as one of the serious RFID security issue, it only received little attention in the literature. Therefore we developed a lightweight anti-cloning approach based on modified Count- Min sketch vector and tag reading frequency from e-pedigree in observing identical Electronic Product Code (EPC) of the low cost tag in local site and distributed region in supply chain. Experimental results showed, that the first proposed approach, Duplicate Filtering Hash (DFH) achieved the lowest false positive rate of 0.06% and the highest true positive rate of 89.94% as compared to other baseline approaches. DFH is 71.1% faster than d-Left Time Bloom Filter (DLTBF) while reducing amount of hashing and achieved 100% true negative rate. The second proposed approach, Managing Counterfeit Hash (MCH) performs fastest and 25.7% faster than baseline protocol (BASE) and achieved 99% detection accuracy while DeClone 64% and BASE 77%. Thus, this study successfully proposed approaches that can enhance the RFID data quality and reliability

A Review on Missing Tags Detection Approaches in RFID System

Radio Frequency Identification (RFID) system can provides automatic detection on very large number of tagged objects within short time. With this advantage, it is been using in many areas especially in the supply chain management, manufacturing and many others. It has the ability to track individual object all away from the manufacturing factory until it reach the retailer store. However, due to its nature that depends on radio signal to do the detection, reading on tagged objects can be missing due to the signal lost. The signal lost can be caused by weak signal, interference and unknown source. Missing tag detection in RFID system is truly significant problem, because it makes system reporting becoming useless, due to the misleading information generated from the inaccurate readings. The missing detection also can invoke fake alarm on theft, or object left undetected and unattended for some period. This paper provides review regarding this issue and compares some of the proposed approaches including Window Sub-range Transition Detection (WSTD), Efficient Missing-Tag Detection Protocol (EMD) and Multi-hashing based Missing Tag Identification (MMTI) protocol. Based on the reviews it will give insight on the current challenges and open up for a new solution in solving the problem of missing tag detection

A low-cost collaborative location scheme with GNSS and RFID for the Internet of Things

The emergence and development of the Internet of Things (IoT) has attracted growing attention to low-cost location systems when facing the dramatically increased number of public infrastructure assets in smart cities. Various radio frequency identification (RFID)-based locating systems have been developed. However, most of them are impractical for infrastructure asset inspection and management on a large scale due to their high cost, inefficient deployment, and complex environments such as emergencies or high-rise buildings. In this paper, we proposed a novel locating system by combing the Global Navigation Satellite System (GNSS) with RFID, in which a target tag was located with one RFID reader and one GNSS receiver with sufficient accuracy for infrastructure asset management. To overcome the cost challenge, one mobile RFID reader-mounted GNSS receiver is used to simulate multiple location known reference tags. A vast number of reference tags are necessary for current RFID-based locating systems, which means higher cost. To achieve fine-grained location accuracy, we utilize a distance-based power law weight algorithm to estimate the exact coordinates. Our experiment demonstrates the effectiveness and advantages of the proposed scheme with sufficient accuracy, low cost and easy deployment on a large scale. The proposed scheme has potential applications for location-based services in smart cities