’Does country-of-origin matter in the era of globalisation? Evidence from cross sectional data in Uzbekistan

To examine the consistency over time of customer attitude towards country-of-origin in a transitional economy. A single cross-sectional study in Uzbekistan was carried out, with n=527, consisting of 374 street and 153 online surveys, replicating a study carried out 20 years earlier. Whilst consumers still perceive products from advanced countries to have higher quality, quality perception in relation to country-of-origin information is dynamic, and transitional countries can improve the perception of consumers towards their national brands. This study was carried out in Tashkent, the capital of Uzbekistan, the most populous of the Central Asian republics. Researchers may wish to extend it by examining COO effects in other transitional economies, and additionally to examine the effect of country-of-brand origin. Customer perceptions and attitudes take a long time to evolve. This cross-sectional study showed that the COO perception of China has improved significantly and the perception towards the products produced locally in Uzbekistan has also slightly improved across all categories. Strong brands can contribute to the image of the country. Transition countries need to take appropriate marketing actions to cultivate positive perception through innovation and branding. Prior research has been extended by adding new product categories such as mobile phones, computers, washing machines and air conditioners. This research shows that government officials and exporters in developing countries should prioritise strengthening their country’s image to help domestic marketers export and attract foreign investors. We provide insights for marketers to understand the impact of product country-of-origin on customer purchase intention and its antecedents in transitional economies such as Uzbekistan

Antenna with artificial magnetic conductor for wireless application

— This paper discussed the recent works on Artificial Magnetic Conductor (AMC) with the antenna. Two different application for antenna with AMC have been discussed. The first application is the antenna with AMC that has been used for RFID system to detect the metal object. Without incorporating AMC with antenna the system cannot be detected. When the AMC is attached with the RFID Tag antenna the system is back to normal where longer distance is achieved. The second application is used for flexible AMC using textile material for signal transmission enhancement. Using two antennas for on body application the system has been tested using AMC and without AMC. It shows that the transmission is better when there is an AMC attach to the body compared without AMC. Index Terms — Artificial Magnetic Conductor, high impedance surface, metamaterial, reflection phase

Money Laundering Detection Framework to Link the Disparate and Evolving Schemes

Money launderers hide traces of their transactions with the involvement of entities that participate in sophisticated schemes. Money laundering detection requires unraveling concealed connections among multiple but seemingly unrelated human money laundering networks, ties among actors of those schemes, and amounts of funds transferred among those entities. The link among small networks, either financial or social, is the primary factor that facilitates money laundering. Hence, the analysis of relations among money laundering networks is required to present the full structure of complex schemes. We propose a framework that uses sequence matching, case-based analysis, social network analysis, and complex event processing to detect money laundering. Our framework captures an ongoing single scheme as an event, and associations among such ongoing sequence of events to capture complex relationships among evolving money laundering schemes. The framework can detect associated multiple money laundering networks even in the absence of some evidence. We validated the accuracy of detecting evolving money laundering schemes using a multi-phases test methodology. Our test used data generated from real-life cases, and extrapolated to generate more data from real-life schemes generator that we implemented

Money Laundering Detection Framework to Link the Disparate and Evolving Schemes

Money launderers hide traces of their transactions with the involvement of entities that participate in sophisticated schemes. Money laundering detection requires unraveling concealed connections among multiple but seemingly unrelated human money laundering networks, ties among actors of those schemes, and amounts of funds transferred among those entities. The link among small networks, either financial or social, is the primary factor that facilitates money laundering. Hence, the analysis of relations among money laundering networks is required to present the full structure of complex schemes. We propose a framework that uses sequence matching, case-based analysis, social network analysis, and complex event processing to detect money laundering. Our framework captures an ongoing single scheme as an event, and associations among such ongoing sequence of events to capture complex relationships among evolving money laundering schemes. The framework can detect associated multiple money laundering networks even in the absence of some evidence. We validated the accuracy of detecting evolving money laundering schemes using a multi-phases test methodology. Our test used data generated from real-life cases, and extrapolated to generate more data from real-life schemes generator that we implemented. Keywords: Anti Money Laundering, Social Network Analysis, Complex Event Processin

A 28 GHz 0.18-μm CMOS cascade power amplifier with reverse body bias technique

A 28 GHz power amplifier (PA) using CMOS 0.18 μm Silterra process technology is reported. The cascade configuration has been adopted to obtain high Power Added Efficiency (PAE). To achieve low power consumption, the input stage adopts reverse body bias technique. The simulation results show that the proposed PA consumes 32.03mW and power gain (S21) of 9.51 dB is achieved at 28 GHz. The PA achieves saturated power (Psat) of 11.10 dBm and maximum PAE of 16.55% with output 1-dB compression point (OP1dB) 8.44 dBm. These results demonstrate the proposed power amplifier architecture is suitable for 5G applications

Updating radical ring-opening polymerisation of cyclic ketene acetals from synthesis to degradation

Radical ring-opening polymerisation (RROP) of cyclic ketene acetals (CKAs) has gained momentum as it yields polyesters as biodegradable polymers from a radical polymerisation. In order to advance the polymerisation, some of its major limitations were addressed in the research presented, focussing on the four mainly used CKAs in modern research on RROP. Monomer synthesis has been updated towards a cobalt/TMSCl-based system that was performed reliably on several monomers at room temperature. Calculations using the density functional theory (DFT) revealed that the ring-opening step is energetically hampered in comparison to a ring-retaining reaction, which explained the challenges faced to promote the ring-opening reaction. Higher molecular weights up to four times the values reached by thermally initiated polymerisation were obtained by exploiting UV light and ultrasound as alternative methods to facilitate the polymerisation. The reaction procedure also influenced thermal properties of the polymers, which in turn affected the enzymatic degradation of nanoparticles based on those polymers. Altogether, the present study offers a holistic update to enhance the RROP of CKAs

Central limit theorems for arrays of decimated linear processes

Linear processes are defined as a discrete-time convolution between a kernel and an infinite sequence of i.i.d. random variables. We modify this convolution by introducing decimation, that is, by stretching time accordingly. We then establish central limit theorems for arrays of squares of such decimated processes. These theorems are used to obtain the asymptotic behavior of estimators of the spectral density at specific frequencies. Another application, treated elsewhere, concerns the estimation of the long-memory parameter in time series, using wavelets.The authors would like to thank the referee for his/her suggestions. Murad S. Taqqu would like to thank Telecom Paris Tech for their hospitality. This research was partially supported by the NSF Grants DMS-0505747 and DMS-0706786 at Boston University. (DMS-0505747 - NSF; DMS-0706786 - NSF)First author draf