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The purpose of this paper is to develop a novel totally passive, wireless temperature sensor tag based on ultra high-frequency (UHF) radio frequency identification (RFID) technology. The temperature-sensing functionality is enabled by using distilled water embedded in the tag antenna substrate. The novel sensor tag is designed to provide wireless temperature readings comparable to a commercial thermocouple thermometer even in environments with high levels of interference, such as reflections. The structure of the novel sensor tag is aimed to increase its usability by minimizing user-created errors and to simplify the measurement procedure.

The sensor tag is based on a dual port sensing concept in which two ports are used to obtain sensor readings. By utilizing two ports instead of one, the effects of environmental interference, tag-reader antenna orientation and distance can be effectively minimized. Two alternative methods of acquiring the sensor reading from the operating characteristics of the two ports are presented and discussed.

Temperature measurements in practical scenarios show that by utilizing the dual port sensing concept, the developed tag produces temperature readings wirelessly which are comparable to readings from a commercial thermocouple thermometer.

The concept of dual port sensing was shown and two alternative methods on extracting sensor readings from the differences in the port operating characteristics were introduced and discussed. In this paper, the dual port sensing concept is utilized in creating a temperature sensor tag; however, the same concept can be utilized in a variety of passive wireless sensors based on UHF RFID technology. This enables a new approach in designing accurate, easy to use and easily integrable passive sensors. The dual port sensing concept is in its early stages of development; its accuracy could be improved by developing more advanced data post-processing techniques.

The accuracy of a passive dual port UHF RFID-enabled temperature sensor tag is proven to be sufficient in many applications. This indicates that other sensor types utilizing the dual port sensing concept can reach high levels of accuracy as well. Furthermore, the passive RFID-enabled sensors based on the dual port sensing concept are superior in usability versus sensor tags equipped only with a single port. Therefore, dual port sensing concept in passive UHF RFID-enabled sensor tags could make such sensors more attractive commercially and lead to truly widespread ubiquitous sensing and computing.

This paper presents a novel passive, wireless temperature sensor tag for UHF RFID systems. The sensor tag utilizes a new structure which allows tight integration of two ports and two tag antennas. The accuracy of the developed tag is confirmed throughout measurements and it is found comparable to the accuracy of commercial thermometers in practical measurement scenarios. Moreover, the paper presents a dual port sensing concept and two readout methods based on the concept which are aimed to increase the accuracy and usability of all kinds of UHF RFID-enabled sensor tags.

The purpose of this paper is to develop a new genetic optimization strategy which provides computationally more efficient and accurate solutions, and to provide practically applicable optimization method in radar cross‐section (RCS) minimization problems.

The problem of RCS minimization for three‐dimensional air vehicle is considered. New computationally efficient optimization tool; neural networks (NNs) coupled multi‐frequency vibrational genetic algorithm (NN‐coupled VGA^m) is based on genetic algorithm (GA) search strategy together with NNs. The results include RCS minimization problem of an air vehicle under structural and aero dynamical‐related geometry constraints.

For the demonstration problem considered, remarkable reduction in the computational time has been accomplished.

The results reported in this paper suggest an efficient GA optimization methodology for engineering problems.

Owing to reduction in computational time, the new method provides a shorter design cycle for engineering problems.

The purpose of this paper is to investigate the numerical aspects of the electromagnetic scattering of a plane wave by a set of buried cylinders.

The cylindrical wave approach is employed. The analytical model is implemented in a Fortran code. The numerical aspects of the technique are presented, with particular emphasis on the numerical evaluation of the integrals involved in the procedure.

The tool obtained allows a fast computation of the electromagnetic field scattered by an arbitrary disposition of circular cylinders below an interface. Comparisons with the finite element method are proposed, showing the very good agreement between the results obtained with the two different approaches.

The advantages of the proposed technique in terms of computational weight are explained. The method can be useful in a wide class of application, e.g. in the ground penetrating radar applications, microscopy, biomedical applications, etc.

The purposes of this paper are to numerically analyse the distribution of the electromagnetic field in the electromagnetic device wherein a high-speed unit exists and to develop a strong tool to analyse the evolution of an electromagnetic field tangled with moving parts.

The precise integration time domain (PITD) method and parameter weighted averaging approximation scheme.

It is shown that that the electromagnetic field in the device is significantly affected by the velocity of the moving unit and the parameters of the base material. The computation resources of the proposed method are saved and the efficiency is enhanced.

The parameter approximation (PA)-PITD method can be an effective and efficient time domain method to analyse the evolution of the electromagnetic field in electromagnetic devices with moving parts and similar problems.

The purpose of this paper is to design and measure an H‐plane substrate integrated waveguide (SIW) 72 GHz backfired horn antenna chip. The SIW horn was fabricated on a standard 0.5‐μm GaAs process with substrate thickness of 100 μm.

Planar SIW horn design method with standard GaAs circuit design rule was adopted. The input reflection coefficient and output antenna gain was simulated at the FEM‐based 3D full‐wave EM solver, Ansoft HFSS and measured at the Agilent E8361C Network Analyzer and Cascade 110 GHz probe station.

The measured input −6 dB bandwidth is about 0.9 GHz at a center frequency of 72.39 GHz. The maximum antenna power gain extracted from the path loss at 72.39 GHz is about −3.64 dBi.

Thin substrate exhibits larger capacitance and energy stores rather than radiates. Flat cutting restricts the arc lens design and results in the radiation plane mismatches to the air. Simple taper transition design makes the input bandwidth much narrower. The problems can be further improved by selecting thicker substrate and the multi‐section input CPW GSG pads to microstrip transition.

Unlike the traditional anechoic chamber, the antenna measurement station is exposed to the open space and chip antenna was supported by the FR4 substrate and the metal probing station plate. A fully characterization of the antenna open space environment before the measurement is needed.

An H‐plane SIW 72 GHz horn antenna was designed and studied. The antenna was using the GaAs 0.5‐μm MMICs process design rule includes the SIW designed cylindrical metal bars all being restricted in standard rectangular shape. Compare to traditional bulky waveguide horn antenna, the antenna chip size is only 1.8×1.7 mm². The on‐wafer measurement is conducted to measure the input return loss and the maximum antenna power gain of the on‐chip antenna. The designed on‐chip SIW horn antenna is useful for the integrated design of the E band GaAs MMICs single‐chip RF transceiver.

The purpose of the paper is to identify the multiple types of data that can be collected and analyzed by practitioners across the cold chain, the ICT infrastructure required to enable data capture and how to utilize the data for decision making in cold chain logistics.

Content analysis based literature review of 38 selected research articles, published between 2000 and 2016, was used to create an overview of data capture, technologies used for collection and sharing of data, and decision making that can be supported by the data, across the cold chain and for different types of perishable food products.

There is a need to understand how continuous monitoring of conditions such as temperature, humidity, and vibration can be translated to support real-time assessment of quality, determination of actual remaining shelf life of products and use of those for decision making in cold chains. Firms across the cold chain need to adopt appropriate technologies suited to the specific contexts to capture data across the cold chain. Analysis of such data over longer periods can also unearth patterns of product deterioration under different transportation conditions, which can lead to redesigning the transportation network to minimize quality loss or to take precautions to avoid the adverse transportation conditions.

The findings need to be validated through further empirical research and modeling. There are opportunities to identify all relevant parameters to capture product condition as well as transaction data across the cold chain processes for fish, meat and dairy products. Such data can then be used for supply chain (SC) planning and pricing products in the retail stores based on product conditions and traceability information. Addressing some of the above research gaps will call for multi-disciplinary research involving food science and engineering, information technologies, computer science and logistics and SC management scholars.

The findings of this research can be beneficial for multiple players involved in the cold chain like food processing companies, logistics service providers, ports and wholesalers and retailers to understand how data can be effectively used for better decision making in cold chain and to invest in the specific technologies, which will suit the purpose. To ensure adoption of data analytics across the cold chain, it is also important to identify the player in the cold chain, which will drive and coordinate the effort.

This paper is one of the earliest to recognize the need for a comprehensive assessment for adoption and application of data analytics in cold chain management and provides directions for future research.

Considering the vector Helmholtz equation in three dimensions, this paper aims to present a novel approach for coupling the finite element method and a boundary integral formulation. It is demonstrated that the method is well-suited for many realistic three-dimensional problems in high-frequency engineering.

The formulation is based on partial solutions fulfilling the global boundary conditions and the iterative interaction between them. In comparison to other coupling formulation, this approach avoids the typical singularity in the integral kernels. The approach applies ideas from domain decomposition techniques and is implemented for a parallel calculation.

Using confirming elements for the trace space and default techniques to realize the infinite domain, no additional loss in accuracy is introduced compared to a monolithic finite element method approach. Furthermore, the degree of coupling between the finite element method and the integral formulation is reduced. The accuracy and convergence rate are demonstrated on a three-dimensional antenna model.

This approach introduces additional degrees of freedom compared to the classical coupling approach. The benefit is a noticeable reduction in the number of iterations when the arising linear equation systems are solved separately.

This paper focuses on multiple heterogeneous objects surrounded by a homogeneous medium. Hence, the method is suited for a wide range of applications.

The novelty of the paper is the proposed formulation for the coupling of both methods.

The purpose of this paper is to present a numerical analysis of the specific absorption rate (SAR) and temperature increase in a three dimensional (3D) anatomical human eye model exposed to electromagnetic (EM) fields at 1.9, 2.4 and 5.1 GHz, in particular devices such as tablets, smart phones, etc., which are based on Wi-Fi and 4G technology.

A new 3D model of the human eye composed of nine different tissues with a high resolution of 0.5 mm is presented, including a precise definition of the cornea and lens and also distinguishing the cornea from the aqueous humor and the sclera from the retina and choroid. The EM problem is solved from the Maxwell’s equations which gives the electric field and in turn enables the calculation of the SAR in any part of the eye model. The thermal problem is solved from the bioheat (Pennes’) equation taking the SAR as an input of the power dissipated by the EM field. In both cases the finite difference time domain method is employed.

A plane-wave field located 30 cm away from the eye is considered as the source for the far-field EM exposure. The results for maximum SAR indicate that the smallest value is 0.06 W/kg in the lens for 1.9 GHz whereas the highest value encountered is 0.43 W/kg in the vitreous humor for 5.1 GHz. In the worst case, the maximum SAR in the lens is 0.28 W/kg for 5.1 GHz. In all cases, the SAR values are within the limits defined by international standards. In terms of maximum temperature, the highest value found is 0.01 C in the cornea, aqueous humor and lens for 5.1 GHz.

The work presents a thorough numerical calculation of the temperature increase in the human eye induced by devices that are based on Wi-Fi and 4G technology operating at 1.9-5.1 GHz.

This paper aims to present the development of a holistic campus facility management (CFM) performance assessment framework that incorporates a fuzzy logic approach and integrates a comprehensive set of key factors for successful management of campus facilities. The devised framework aims to cater to the needs of campus facilities management firms and departments for the purpose of gauging and assessing their performance across different management domains. Through this approach, facility management organizations can detect potential areas of enhancement and adopt preemptive steps to evade issues, foster progress and ensure success.

After a comprehensive analysis of the literature, conducting in-depth interviews with industry experts and employing the Delphi technique in two rounds, a total of 45 indicators critical to CFM success were identified and subsequently sorted into seven distinct groups. Through an online questionnaire, 402 subject-matter experts proficiently assessed the significance of the critical success indicators and their groups. A fuzzy logic framework was developed to evaluate and quantify a firm's compliance with the critical success indicators and groups of indicators. The framework was subsequently weighted using computations of the relative importance index (RII) based on the responses received from the questionnaire participants. The initial section of the framework involved a comprehensive analysis of the firm's performance vis-à-vis the indicators, while the latter part sought to evaluate the impact of the indicators groups on the overall firm's performance.

The utilization of fuzzy logic has uncovered the significant effects each effective CFM key indicator on indicators groups, as well as the distinct effects of each CFM indicators group on the overall performance of CFM. The results reveal that financial management, communications management, sustainability and environment management and workforce management are the most impactful indicators groups on the CFM performance. This suggests that it is imperative for management to allocate increased attention to these specific areas.

This study contributes to the advancement of current knowledge by revealing vital indicators of effective CFM and utilizing them to construct a thorough fuzzy logic framework that can assist in evaluating the effectiveness of CFM firms worldwide. This has the potential to provide crucial assistance to facility management organizations, facility managers and policymakers in their quest for informed decision-making.

Traditional paper-based contracts are document-intensive, insecure, susceptible to forgery and errors, detrimental to productivity improvement and require multiple intermediaries. Addressing these challenges requires computerised construction to modernise the way modern construction projects are procured with blockchain-enabled smart contracts. Smart contracts could replace paper-based contracts by improving transparency and security and automating contractual terms, processes and transacting activities. However, smart contracts are an emerging technology with limited adoption in construction projects, and the issues influencing its widespread adoption remain unclear and unexplored. Hence, this study aims at exploring and understanding the important obstacles to adoption of smart contracts in construction projects.

Using an international questionnaire survey, the study draws on experienced construction practitioners with direct involvement and knowledge in blockchain technology and smart contract initiatives and activities. Descriptive statistics and fuzzy logic techniques were used to analyse and model the quantitative survey data to establish the critical barriers to smart contracts adoption.

Organisational and external characteristics, personal characteristics and technology characteristics constitute major obstacles to the successful adoption of smart contracts. Construction practitioners’ limited knowledge of smart contracts, resistance to technology change, insufficiently digitalised construction industry and lack of or weak governmental support are critical to smart contracts adoption.

The research contributes to the body of knowledge on diffusing cutting-edge technology by advancing the understanding of practitioners’ perspectives on the primary obstacles to smart contracts adoption. Understanding the obstacles provides industry stakeholders (policymakers, leaders and practitioners) with underpinning knowledge with which to develop and implement corrective actions.