Non-linear Oberbeck-electroconvection in a poorly conducting fluid through a vertical channel in the presence of an electric field

Non-linear Oberbeck-electroconvection (OBEC) in a poorly electrically conducting fluid through a vertical channel, when the walls are held at different temperatures with temperature difference perpendicular to gravity, is studied using the modified Navier stokes equation in the presence of both induced and an applied electric field. Both analytical and numerical solutions for the non-linear coupled equations governing the motion are obtained and found that analytical solutions agree well with numerical solutions for values of the buoyancy parameter N<1. It is shown that OBEC can be controlled by maintaining the temperature difference either in the same direction or opposing the potential difference with a suitable value of electric number W. The effect of W on velocity, temperature, rate of heat transfer, skin friction and mass flow rate are computed and the results are depicted graphically. We found that analytical results agree well with numerical results for small values of N. We also found that an increase in W accelerates the flow and hence increases linearly the skin friction and mass flow rate.     

Actinides selective extractants coated magnetite nanoparticles for analytical applications

N,N,N′,N′-tetraoctyl diglycolamide (TODGA) and bis(2-ethylhexy)phosphoric acid (HDEHP) were coated on Fe₃O₄ nanoparticles under different chemical conditions. The TODGA-coated magnetite nanoparticles (Fe₃O₄@TODGA) captured representative actinides Am(III) and Pu(IV) at 3–4 M HNO₃ with high efficiency. However, the HNO₃ induced pre-organization of TODGA, before coating on the magnetite nanoparticles, was found to be important for the sorption of Am(III) and Pu(IV) ions. The Fe₃O₄@HDEHP particles exhibited selectivity toward Pu(IV), and Am(III) did not sorb from 3 to 4 M HNO₃. The quantification of Pu(IV) preconcentrated on coated particles was carried out by removing the extractant coating in dioxane based scintillator, followed by liquid scintillation counting.

     

Variation in Mesomorphic Characteristics with Certain Alterations in Molecular Structure: Homologous Series iso-Propyl p-(p'-n-Alkoxy CinnamoyIoxy) Benzoates and iso-Propyl p-(p'-n-AIkoxy Benzoyloxy) Benzoates

Mesomorphic characteristics of homologous series n-propyl p-(p'-n-alkoxy cinnamoyloxy)benzoates (I)¹ are quite in keeping with the general molecular structure and molecular forces accruing therefrom. Continuing the work further, the right hand terminal group of the series (I) has been replaced by a branched group with iso disposition of the alkylchain but having the same number of carbon atoms. Thus the new homologous series iso-propyl p-(p'-n-alkoxy cinnamoyloxy)benzoates (II) with all other molecular geometry the same, gets mesomorphic characteristics changed considerably. The first few members become non-mesogenic, nematic orientation is altogether eliminates and the smectic mesophase range is reduced to about one third of that of the series (I). Another new homologous series (III) with all the molecular geometry of the series (II). but with a shorter central bridge —COO— than —CH=CH—COO—receives a further jolt in its exhibition of mesomorphic characteristics. The first seven members and the last member of the series (III) become non-mesomorphic; however, some middle members exhibit monotropic smectic mesophase. The effect of the branching of the terminal substituent and shortening of the central bridge are thus quite evident and arouse good interest. The smectic texture as determined by optical microscopy and by the study of mixtures² is of fan shaped focal conic smectic A variety.     

Conformational order of n-alkyl modified silica gels as evaluated by Fourier transform infrared spectroscopy

The conformational behaviour of non-deuterated and selectively deuterated alkyl modified silica gels in the dry state is examined by variable temperature FT IR spectroscopy. In the present study, three systems are considered, which are distinguished by the length of the tethered alkyl chains (C9Hl9-, C18H37-, C22H45-). The desired information is obtained by the analysis of various conformational-sensitive IR bands, including CH2 wagging, CD2 stretching and CD2 rocking bands. The analysis of the CH2 wagging bands provides the relative amounts (i.e., integral numbers over the whole chain) of the kink/gauche-trans-gauche, double-gauche and end-gauche conformers in the tethered alkyl chains. From the analysis of the CD2 stretching and CD2 rocking bands information about the conformational order at a specific deuterated methylene segment is available. Here, the CD2 rocking band data are used to determine the amount of gauche conformers at the deuterated carbon positions C-4 and C-6, and C-12. It is found that the conformational order critically depends on the actual alkyl chain length, chain position and sample temperature. Particular emphasis is given to the impact of the external pressure during sample preparation on the alkyl chain conformations, about which so far no information is available. It is observed that the samples prepared as KBr pellets, which experienced a pressure of about 10 kbar, are characterised by a lower amount of gauche conformers. This substantial increase of conformational order is attributed to better alkyl chain packing along with a gain of intermolecular chain interactions.     

RSS Fingerprints Based Distributed Semi-Supervised Locally Linear Embedding (DSSLLE) Location Estimation System for Indoor WLAN

An important requirement for many novel location based services, is to determine the locations of people, equipment, animals, etc. The accuracy and response time of estimation are critical issues in location estimation system. Most of the location estimation system suffers with the problem of scalability and unavailability of all the access points at all the location for large site. In this paper, we have proposed a distributed semi-supervised location estimation method, which divide the location estimation system into subsystems. Our method partition the input signal space and output location space into clusters on the basis of visibility of access points at various locations of the site area. Each cluster of input signal space together with output location subspace is used to learn the association between Received Signal Strength fingerprint and their respective location in a subsystem. Previous methods for location estimation in indoor wireless networks require a large amount of labeled data for learning the radio map. However, labeled instances are often difficult, expensive, or time consuming to obtain, as they require great efforts, meanwhile unlabeled data may be relatively easy to collect. So, the use of semi-supervised learning is more feasible. On each subsystem at first, we use Locally Linear Embedding to reduce the dimensions of data, and then we use semi-supervised learning algorithm to learn the radio map. The algorithm performs nonlinear mapping between the received signal strengths from nearby access points and the user’s location. It is shown that the proposed Distributed Semi-Supervised Locally Linear Embedding scheme has the advantage of robustness, scalability, useful in large site application and is easy in training and implementation. We have compared our results with Distributed Subtract on Negative Add on Positive (DSNAP) and benchmark method RADAR. Experimental results show that our method provide better results in terms of accuracy and response time in comparison to centralized systems, in which a single system is used for large site as well as with DSNAP and benchmark method RADAR.     

Effect of undulating bottom on wave interaction with a floating flexible plate coupled with a flexible porous barrier

Meccanica - In the present study, under the assumption of small amplitude water wave theory and structural response, effect of bed undulation on the wave interaction with a combination of flexible...     

Performance Analysis of Received Signal Strength Fingerprinting Based Distributed Location Estimation System for Indoor WLAN

Location Estimation has become important for many applications of indoor wireless networks. Received Signal Strength (RSS) fingerprinting methods have been widely used for location estimation. Most of the location estimation system suffers with the problem of scalability and unavailability of all the access points at all the location for large site. The accuracy and response time of estimation are critical issues in location estimation system for large sites. In this paper, we have proposed a distributed location estimation method, which divide the location estimation system into subsystems. Our method partitions the input signal space and output location space into clusters on the basis of visibility of access points at various locations of the site area. Each cluster of input signal space together with output location subspace is used to learn the association between RSS fingerprint and their respective location in a subsystem. We have performed experimentation on two RSS dataset, which are gathered on different testbeds, and compared our results with benchmark RADAR method. Experimental results show that our method provide better results in terms of accuracy and response time in comparison to centralized systems, in which a single system is used for large site.     

Markov Chain Based Roaming Schemes for Honeypots

The paper proposes a reactive roaming scheme for honeypots. The main aim of a honeypot is to capture the activities of the attacker. If the attacker detects honeypot on a system, its value drops. So, the concept of roaming honeypots is being proposed, to prevent the attacker from detecting the honeypot, which in turn increases the efficiency of honeypot and allows collecting rich data about activities of active attackers. The honeypot is shifted to another system which is most probable to be attacked within the network. The concept of Markov chain analysis is being used to detect the most probable system to be attacked based on the current status of the network. Further, using IP shuffling and services on/off concepts, honeypots roam on the network to the most probable system to be attacked using the threat score. Snort is used to capture data about the number of attacks on each of the nodes of the network and the data collected is then used as an input for Markov chain analysis to identify the most probable system where honeypot can be roamed/moved. The roaming scheme has been implemented for both high interaction honeypots and low interaction honeypots. The high interaction implementation helps in capturing in depth information on a shorter range of IP addresses, whereas the low interaction implementation is efficient in capturing information on a large range of IP addresses. The main advantage of this approach is that it predicts the frequency of attacks on the nodes of a particular network and takes a reactive step by starting the honeypot services on that particular node/system on the network.     

A bibliographical review of the high pressure studies of ferroelectric phase transitions

A brief review of the various high pressure studies on the phase transitions in ferroelectric crystals carried out over the past two decades is presented. The theoretical framework in which high pressure studies have to be viewed is given. The pressure data of ferroelectric crystals are organized in the form of tables. High pressure spectroscopic and structural studies are included. The review contains a bibliography of over two hundred references.