Adaptive joint detection of cochannel signals for TDMA handsets

In mobile communication systems, downlink (forward link) system capacity is limited by the ability of mobile receivers to recover the desired signal in the presence of cochannel interference (CCI). Joint detection of the desired and cochannel signals is a useful approach to improving receiver performance, thus increasing system capacity. In this paper, we show that a practical single-antenna joint-detection receiver can provide significant gains in system capacity for the time-division multiple-access (TDMA) standard Telecommunications Industry Association/Electronic Industry Association/Interim Standard-136 (TIA/EIA/IS-136 or IS-136). For a sectorized system, joint detection provides a capacity gain of 47% in a typical urban environment. When used in conjunction with transmit beamforming, the synergy between the two approaches leads to a capacity gain of over 200%. In determining these gains, practical aspects of the IS-136 system are considered, namely, unsynchronized networks, limited receiver complexity, and adaptability. A semiblind acquisition process, which uses the training sequence of the desired user only, is employed, because the desired and interfering base stations are not synchronized. The receiver complexity is controlled by processing only one sample per symbol period, even though it is shown that multiple samples per symbol period should ideally be used. Finally, because receiver performance may be limited by its own intersymbol interference instead of CCI, an adaptive joint-detection process is used which selects between joint demodulation and single-user equalization for each slot.     

ED2+ macrophages increase selectively myoblast proliferation in muscle cultures

We have previously shown by coculturing myoblasts and macrophages that myotube formation is strongly increased in vitro by the presence of an acid stable, heat-labile, soluble growth factor(s) secreted by macrophages. In this paper we obtained macrophages from peritoneal washing which also contained limited amounts of other cells such as lymphocytes and mesothelial cells. We here demonstrate that an ED2-positive (ED2+) macrophage subpopulation is responsible for myoblast enhanced proliferation. ED2+ macrophages were separated by a magnetic-activated cell sorter (MACS) using a monoclonal antibody against ED2, a membrane antigen peculiar to macrophages. Both ED2+ macrophages and their conditioned medium increased myotube formation when added to primary muscle cultures. Furthermore we demonstrate that muscle growth induced by macrophages is mainly the consequence of an increased myoblast proliferation by showing the presence of an increased number of MyoD-positive (MyoD+) myonuclei.     

OCDMA and OSTBC based VLC transceiver design using NI cDAQ

Visible light communication (VLC) is a novel technology especially for short-range data communication. IEEE has standardized VLC for 5G systems as a means to short-range wireless communication. In this paper, a complete state-of-the-art VLC software-defined radio is designed using NI cDAQ components tools developed in LabVIEW/MATLAB. The main objectives in designing a VLC transceiver are the suitable envelope for driving LEDs (transmitters) and a high data rate. The current work makes use of optical code division multiple access mainly to achieve the said objectives. It is shown through comparison with existing system that the proposed system is computationally less expensive and provides improved data rate. Finally, simulation programs are also developed and the proposed system is compared with the existing system in terms of bit error rate.     

Are RNGs Achilles’ Heel of RFID Security and Privacy Protocols?

Security and privacy concerns have been growing with the increased utilisation of RFID technology in our daily lives. To mitigate these issues, numerous privacy-friendly authentication protocols have been published in the last decade. Random number generators (RNGs) are necessarily used in RFID tags to provide security and privacy. However, low-end RNGs can be the weakest point in a protocol scheme and using them might undesirably cause severe security and privacy problems. On the other hand, having a secure RNG with large entropy might be a trade-off between security and cost for low-cost RFID tags. Furthermore, RNGs used in low-cost RFID tags might not work properly in time. Therefore, we claim that the vulnerability of using an RNG deeply influences the security and privacy level of the RFID system. To the best of our knowledge, this concern has not been considered in the RFID literature. Motivated by this need, in this study, we first revisit Vaudenay’s privacy model which combines the early models and presents a new mature privacy model with different adversary classes. Then, we extend the model by introducing RANDOMEYE privacy, which allows analyzing the security of RNGs in RFID protocols. We further apply our extended model to two existing RFID schemes.     

Role of Ni<Superscript>2+</Superscript> Ions in Magnetite Nano-particles Synthesized by Co-precipitation Method

In the present work, nickel-doped iron oxide (Ni_xFe_3?x O ₄) nanoparticles with different concentration of nickel (x = 0, 0.05, 0.1, and 0.15) have been prepared by co-precipitation method. These prepared nanoparticles have been characterized by using x-ray diffractometer, thermo gravimetric analysis and differential scanning calorimetry, Fourier transform infrared spectroscopy, scanning electron microscopy, vibrating sample magnetometer, and UV-Visible spectroscopy to study their structural, thermal, morphological, magnetic, and optical properties, respectively. The x-ray diffraction confirms the formation of single-phase inverse spinel cubic structure of NiFe₃ O ₄ nanoparticles. Crystallite size has been estimated by the full width at half maximum of the most intense x-ray diffraction peak where vibrational and stretching modes of metal-oxygen bonds in 872 cm are shown in Fourier transform infrared spectra which confirms the formation of nanoparticles. The thermal analysis revealed that the transition temperature and stability increases with increasing Ni concentration. The surface morphology indicated that the particles are spherical in shape with some agglomeration. The magnetic measurement revealed that the coercivity and anisotropy increases with nickel doping in magnetite nanoparticles. The optical analysis revealed that direct and indirect both types of band gap increases when the particle size decreases because the absorption spectra shift toward smaller wavelength. The blue shift confirms the formation of nanoparticles.     

Performance evaluation of hybrid FFA-ANFIS and GA-ANFIS models to predict particle size distribution of a muck-pile after blasting

Accurately predicting the particle size distribution of a muck-pile after blasting is always an important subject for mining industry. Adaptive neuro-fuzzy inference system (ANFIS) has emerged as a synergic intelligent system. The main contribution of this paper is to optimize the premise and consequent parameters of ANFIS by firefly algorithm (FFA) and genetic algorithm (GA). To the best of our knowledge, no research has been published that assesses FFA and GA with ANFIS for fragmentation prediction and no research has tested the efficiency of these models to predict the fragmentation in different time scales as of yet. To show the effectiveness of the proposed ANFIS-FFA and ANFIS-GA models, their modelling accuracy has been compared with ANFIS, support vector regression (SVR) and artificial neural network (ANN). Intelligence predictions of fragmentation by ANFIS-FFA, ANFIS-GA, ANFIS, SVR and ANN are compared with observed values of fragmentation available in 88 blasting event of two quarry mines, Iran. According to the results, both ANFIS-FFA and ANFIS-GA prediction models performed satisfactorily; however, the lowest root mean square error (RMSE) and the highest correlation of determination (R²) values were obtained from ANFIS-GA model. The values of R² and RMSE obtained from ANFIS-GA, ANFIS-FFA, ANFIS, SVR and ANN models were equal to (0.989, 0.974), (0.981, 1.249), (0.956, 1.591), (0.924, 2.016) and (0.948, 2.554), respectively. Consequently, the proposed ANFIS-GA model has the potential to be used for predicting aims on other fields.

     

Synthesis and characterization of poly[(R,S)‐3‐hydroxybutyrate] telechelics and their use in the synthesis of poly(methyl methacrylate)‐b‐ poly(3‐hydroxybutyrate) block copolymers

Poly[(R,S)‐3‐hydroxybutyrate] oligomers containing dihyroxyl (PHB‐diol), dicarboxylic acid (PHB‐diacid) and hydroxyl‐carboxylic acid (a‐PHB) end functionalities were obtained by the anionic polymerization of β‐butyrolacton (β‐BL). Ring opening anionic polymerization of β‐BL was initiated by a complex of 18‐Crown‐6 with γ‐hydroxybutyric acid sodium salts (for PHB‐diol and a‐PHB) or succinic acid disodium salt (for PHB‐diacid). Dihydroxyl functionalization was formed by the termination of polymerization with bromo‐ethanol or bromo‐decanol while the others were done by protonation. Hydroxyl and/or carboxylic acid functionalized PHB oligomers with ceric salts were used to initiate the polymerization of methylmethacrylate (MMA). PHB‐b‐PMMA block copolymers obtained by this way were purified by fractional precipitation and characterized using ¹H‐NMR and ¹³C‐NMR, gel permeation chromatography (GPC), and thermal analysis (DSC and TGA) techniques. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 85: 965–973, 2002     

A Fuzzy Bayesian Classifier with Learned Mahalanobis Distance

Recent developments show that naive Bayesian classifier (NBC) performs significantly better in applications, although it is based on the assumption that all attributes are independent of each other. However, in the NBC each variable has a finite number of values, which means that in large data sets NBC may not be so effective in classifications. For example, variables may take continuous values. To overcome this issue, many researchers used fuzzy naive Bayesian classification for partitioning the continuous values. On the other hand, the choice of the distance function is an important subject that should be taken into consideration in fuzzy partitioning or clustering. In this study, a new fuzzy Bayes classifier is proposed for numerical attributes without the independency assumption. To get high accuracy in classification, membership functions are constructed by using the fuzzy C‐means clustering (FCM). The main objective of using FCM is to obtain membership functions directly from the data set instead of consulting to an expert. The proposed method is demonstrated on the basis of two well‐known data sets from the literature, which consist of numerical attributes only. The results show that the proposed the fuzzy Bayes classification is at least comparable to other methods.     

Computational Models in Architecture: Understanding Multi-Dimensionality and Mapping

The aim of this paper is to discuss computational thinking and parametric design and thus “what model is” in the realm of mathematics in architecture. Here we investigate how multi-dimensionality and reference systems should be contemplated, along with what mapping is and how it is related with algorithms in computational design. Set theory and functional relations are re-visited and similarity/similitude concepts and the importance of nondimensional parameters relating different reference systems (interpreted as domain and range relations) are pointed out. In this context, computational design approaches based on modern biomimetic studies in architecture which are beyond metaphors or analogies are considered as the prominent cases of the present inquiry.