Comparative study of synthesis, characterization and electric properties of polypyrrole and polythiophene composites with tellurium oxide

The study involves the synthesis of polypyrrole (PPY) and polythiophene (PTP) composites of TeO₂ via in situ oxidative polymerization procedure. These composites were characterized by FTIR, XRD and SEM, which proves the successful chemical synthesis of PPY, PTP and their composites. FTIR absorption peaks confirms the insertion of TeO₂ in the backbone of PPY and PTP and also justifies the strong interaction of TeO₂ with PTP than PPY, which is responsible for a significant increase in the conductivity value in case of PTP composite than PPY composite, which ensures its better capability in future electronics. Thermal analysis shows no change in thermal stability unlike composites of PPY and PTP with other metal oxides, hence rules out the application of these composites for higher temperature purposes, however, the PTP composite material has shown the stability up to 200 °C which ensures its use in low temperature applications. The compactness, ordered morphology, better conjugation or chain length and orientation of TeO₂ with PTP backbone are responsible for more conductivity of PTP composite than PPY.     

Increased capacitation of buffalo sperm by heparin as confirmed by electron microscopy and in vitro fertilization

Capacitation of buffalo sperm was evaluated by induced acrosome reaction (AR) upon the exposure of 10 mM Ca2+. Culture of sperm for 8 hr in BO medium supplemented with 10 micrograms/ml heparin significantly (P < 0.01) increased the percentage of AR and confirmed by transmission electron microscopy. Vesiculization of outer acrosomal membrane and plasma membrane was observed significantly higher (P < 0.01) following 8 hr of sperm culture with heparin. Culture of sperm with heparin also increased rate of fertilization of in vitro matured oocytes and their subsequent development up to morula/blastocyst stage (P < 0.01). The study demonstrates that capacitation of buffalo sperm by heparin required at least 8 hr exposure of sperm to heparin for maximum acrosome reaction.     

OPTIMIZING THE ROTATION AND TRANSLATION OF FINGERPRINT IMAGES USING GENETIC ALGORITHM

In the minutiae-based fingerprint authentication system, the minutiae in the query image are required to be matched with the minutiae of the reference image that is stored in the database. Ideally, the minutiae extracted from the different impressions of the same fingerprint must match with each other, but practically, because of displacement, rotation, and other linear/ nonlinear distortions, minutiae extracted from different impressions of the same fingerprint do not match with each other. In order to maximize the number of matching minutiae, the alignment of the two fingerprints is required. Correctly aligning the fingerprints requires the translation and rotation to be recovered exactly. In this article, a new genetic-algorithm (GA)-based relative alignment algorithm for the alignment of reference and query fingerprint images is proposed. With the proposed algorithm there is no need to find the reference core or delta point because reliable detection of these reference points is a difficult task. In the proposed algorithm, all the three parameters x, y (translation), and θ (rotational) have been optimized separately. In order to improve the processing time, two acceleration steps have also been implemented. The experiments conducted on the FVC2002/Db1_a database reveal that a high accuracy has been achieved with the proposed method.     

Topology Control Algorithms for Wireless Sensor Networks: A Review

Wireless Personal Communications - Wireless sensor networks (WSN) are widely used in various domains such as military, health applications, environmental applications, structural monitoring,...     

Obtaining Crisp Priorities for Triangular and Trapezoidal Fuzzy Judgments

This paper proposes anoptimal fuzzy-based model for obtaining crisp priorities for Fuzzy-AHP comparison matrices. Crisp judgments cannot be given for real-life situations, as most of these include some level of fuzziness and complexity. In these situations, judgments are represented by the set of fuzzy numbers. Most of the fuzzy optimization models derive crisp priorities for judgments represented with Triangular Fuzzy Numbers (TFNs) only. They do not work for other types of Triangular Shaped Fuzzy Numbers (TSFNs) and Trapezoidal Fuzzy Numbers (TrFNs). To overcome this problem, a sum of squared error (SSE) based optimization model is proposed. Unlike some other methods, the proposed model derives crisp weights from all of the above-mentioned fuzzy judgments. A fuzzy number is simulated using the Monte Carlo method. A threshold-based constraint is also applied to minimize the deviation from the initial judgments. Genetic Algorithm (GA) is used to solve the optimization model. We have also conducted casestudiesto show the proposed approach’s advantages over the existingmethods. Results show that the proposed model outperforms other models to minimize SSE and deviation from initial judgments. Thus, the proposed model can be applied in various real time scenarios as it can reduce the SSE value upto 29% compared to the existing studies.     

An In-Network Querying Framework for Wireless Sensor Networks

In contrast to traditional wireless sensor network (WSN) applications that perform only data collection and aggregation, the new generation of information processing applications such as pursuit-evasion games, tracking, evacuation, and disaster relief applications require in-network information storage and querying. Due to the resource limitations of WSNs, it is challenging to implement in-network querying in a distributed, lightweight, resilient, and energy-efficient manner. We address these challenges by exploiting location information and the geometry of the network and propose an in-network querying framework, namely, the Distributed Quad-Tree (DQT). DQT is distance sensitive for querying of an event: the cost of answering a query for an event is at most a constant factor (2sqrt{2} in our case) of the distance “d” to the event. DQT construction is local and does not require any communication. Moreover, due to its minimalist infrastructure and stateless nature, DQT shows graceful resilience to node failures and topology changes. Since event-based querying is inherently limited to the anticipated types of inquiries, we further extend our framework to achieve complex range-based querying. To this end, we use a multiresolution algorithm, which is optimal with respect to least square errors that models the data in a decentralized way. Our model-based scheme answers queries with approximate values accompanied by certainty levels with increased resolution at lower layers of the DQT hierarchy. Our analysis and experiments show that our framework achieves distance sensitivity and resiliency for event-based querying, as well as greatly reduces the cost of complex range querying.     

Enhanced dissolution and absorption of trimethoprim from coprecipitates with polyethylene glycols and polyvinylpyrrolidone

Coprecipitates of trimethoprim have been prepared by solvent method using polyethylene glycols 4000, 6000 and 9000, and polyvinylpyrrolidone (M.W. 40,000) as water soluble carriers. A marked increase in the dissolution rate of trimethoprim in the coprecipitates was observed compared with that of the drug alone. Coprecipitates with polyethylene glycol 6000 (1:2) showed faster release as well as bioavailability of the drug in human volunteers.     

Handling Class Imbalance in Online Transaction Fraud Detection

With the rise of internet facilities, a greater number of people have started doing online transactions at an exponential rate in recent years as the online transaction system has eliminated the need of going to the bank physically for every transaction. However, the fraud cases have also increased causing the loss of money to the consumers. Hence, an effective fraud detection system is the need of the hour which can detect fraudulent transactions automatically in real-time. Generally, the genuine transactions are large in number than the fraudulent transactions which leads to the class imbalance problem. In this research work, an online transaction fraud detection system using deep learning has been proposed which can handle class imbalance problem by applying algorithm-level methods which modify the learning of the model to focus more on the minority class i.e., fraud transactions. A novel loss function named Weighted Hard- Reduced Focal Loss (WH-RFL) has been proposed which has achieved maximum fraud detection rate i.e., True Positive Rate (TPR) at the cost of misclassification of few genuine transactions as high TPR is preferred over a high True Negative Rate (TNR) in fraud detection system and same has been demonstrated using three publicly available imbalanced transactional datasets. Also, Thresholding has been applied to optimize the decision threshold using cross-validation to detect maximum number of frauds and it has been demonstrated by the experimental results that the selection of the right thresholding method with deep learning yields better results.     

Structural and thermal analysis of in situ synthesized C–WC nanocomposites

Nanostructure of carbon encapsulated tungsten carbide (WC@C) has been prepared using reaction between metallic magnesium (Mg), acetone (C₃H₆O) and tungsten trioxide (WO₃) in an autoclave at 600 °C. The resultant powders were characterized by X-ray diffraction (XRD), differential thermal analysis/thermal gravimetric analysis and transmission electron microscopy (TEM). The XRD results showed that the optimization of the reaction time facilitates the reduction as well as carburization of the tungsten source. The apparent activation energy for decarburization of carbide phase was also evaluated from the data of thermal analysis to find the thermal stability of carbide phase. TEM image showed that the synthesized sample consisted of particles with an average size of 35 nm.