Technological Assessment of Radio Frequency Identification Technology for Indoor Localization

Indoor localization is needed for guiding people who are not familiar with a facility. This need is more critical when guidance is needed to locate people or objects that need immediate attention. For example, an inexperienced facility worker might need to locate a building component (e.g., leaking pipe) for repair to prevent any damage to a facility or its residents. In such situations, an approach that can help the user to reach his/her destination point (i.e., a component of interest or a specific location in a facility) based on his/her current location is desired. To provide such guidance, the location of a person needs to be determined at a given point in time. This process is known as localization. The objective of this research study is to determine the technological viability of using radio frequency identification (RFID) to support localization. To assess the capability of RFID for localization, the writers conducted multiple field tests under real operating conditions within a facility at Carnegie Mellon University. Hypothesis tests and K-nearest neighborhood algorithm were used to determine the technological feasibility of RFID to support localization. The results showed that it is possible to identify the location of a user using this approach; however, some improvements in accuracy are needed.     

Novel Approach for the Synthesis of Chlorophosphazene Cycles with a Defined Size via Controlled Cyclization of Linear Oligodichlorophosphazenes [Cl(PCl2=N)n–PCl3]+[PCl6]−

Despite a significant number of investigations in the field of phosphazene chemistry, the formation mechanism of this class of cyclic compounds is still poorly studied. At the same time, a thorough understanding of this process is necessary, both for the direct production of phosphazene rings of a given size and for the controlled cyclization reaction when it is secondary and undesirable. We synthesized a series of short linear phosphazene oligomers with the general formula Cl[PCl2=N]n–PCl₃⁺PCl₆^– and studied their tendency to form cyclic structures under the influence of elevated temperatures or in the presence of nitrogen-containing agents, such as hexamethyldisilazane (HMDS) or ammonium chloride. It was established that linear oligophosphazenes are inert when heated in the absence of the mentioned cyclization agents, and the formation of cyclic products occurs only when these agents are involved in the process. The ability to obtain the desired size phosphazene cycle from corresponding linear chains is shown for the first time. Known obstacles, such as side interaction with the PCl₆^– counterion and a tendency of longer chains to undergo crosslinking elongation instead of cyclization are still relevant, and ways to overcome them are being discussed.     

Enhancement of hybrid sol–gel coating and industrial application on polished porcelain stoneware tiles and investigation of the performance

The aim of this study was to improve stain resistance and cleanability of polished porcelain tiles by sealing the micro-pores on the tile surface with hybrid sol–gel solution. For this purpose, solutions of a hybrid system based on sol–gel technology were prepared. The obtained solution were applied to polished unglazed tiles and subsequently spread with soft tissue thereon. To achieve complete sealing, both organic and inorganic particles of different sizes were mixed with obtained sol–gel hybrid systems. Coated surfaces were investigated by means of a scanning electron microscope. The stain resistance and the cleanability of the tile surface were tested according to ISO-10545-2014 standard. It has been shown that prepared sealing material permanently prevents formation of stains such as olive oil, green staining paste, iodine solution on the surface of polished porcelain tiles. The remains of stains on the surface can easily be removed from it with a cleaning agent.     

Bulk diffusion of iron in copper

The temperature dependence of bulk diffusion coefficient of iron in copper has been determined by electron microprobe analysis (EMA) in the temperature range from 923 to 1273 K to be $D_{Fe} = 0.03 \times 10^{ - 4} \exp \left( { - \frac{{187 kJ/mol}} {{RT}}} \right)$ m²/s. The results obtained differ from the parameters of bulk diffusion determined by the tracer method: the activation energy is less by 30 kJ/mol and the preexponential factor is less by approximately a factor of 50. The deviations of the solutions from the ideality does not explain the discrepancies obtained.     

An intelligent diagnosis system for diabetes on Linear Discriminant Analysis and Adaptive Network Based Fuzzy Inference System: LDA-ANFIS

In this study, an intelligent diagnosis system for diabetes on Linear Discriminant Analysis (LDA) and Adaptive Network Based Fuzzy Inference System (ANFIS): LDA-ANFIS is presented. The structure of this LDA-ANFIS intelligent system for diagnosis of diabetes is composed by two phases: The Linear Discriminant Analysis (LDA) phase and classificiation by using ANFIS classifier phase. In first phase, Linear Discriminant Analysis (LDA) is used to separate features variables between healthy and patient (diabetes) data. In second phase, the healthy and patient (diabetes) features obtained in first phase are given to inputs of ANFIS classifier. The correct diagnosis performance of the LDA-ANFIS intelligent system is calculated by using sensitivity and specificity analysis, classification accuracy and confusion matrix respectively. The classification accuracy of this LDA-ANFIS intelligent system was obtained about 84.61%.     

A Mask Based on a Si Epitaxial Layer for the Self-Catalytic Nanowire Growth on GaAs(111)B and GaAs(100) Substrates

Technical Physics Letters - GaAs nanowires (NWs) were generated on the surface of GaAs(111)B and GaAs(100) substrates from molecular fluxes by the self-catalytic growth method. A mask for NW growth...     

Automatic hepatitis diagnosis system based on Linear Discriminant Analysis and Adaptive Network based on Fuzzy Inference System

In this paper, an automatic diagnosis system based on Linear Discriminant Analysis (LDA) and Adaptive Network based on Fuzzy Inference System (ANFIS) for hepatitis diseases is introduced. This automatic diagnosis system deals with the combination of feature extraction and classification. This automatic hepatitis diagnosis system has two stages, which feature extraction – reduction and classification stages. In the feature extraction – reduction stage, the hepatitis features were obtained from UCI Repository of Machine Learning Databases. Then, the number of these features was reduced to 8 from 19 by using Linear Discriminant Analysis (LDA). In the classification stage, these reduced features are given to inputs ANFIS classifier. The correct diagnosis performance of the LDA-ANFIS automatic diagnosis system for hepatitis disease is estimated by using classification accuracy, sensitivity and specificity analysis, respectively. The classification accuracy of this LDA-ANFIS automatic diagnosis system for the diagnosis of hepatitis disease was obtained in about 94.16%.