Energy efficiency in cognitive radio assisted D2D communication networks

Telecommunication Systems - The next generation networks intend to have features like device to device (D2D) connectivity, energy efficiency and spectral efficiency. This paper presents problem...     

Learning AP in wireless powered communication networks

In a wireless powered communication network (WPCN), sensor nodes harvest energy to transmit information. By a harvest‐then‐transmit (HT) protocol, nodes can be classified into either energy receiving (ER) or data transmitting (DT) nodes depending on the current level of the harvested energy. Since nodes may join or leave a network any time and energy levels vary, the distribution of ER and DT nodes changes over time. As the number of contending DT nodes is highly dynamic, a quick learning mechanism is required for an access point (AP). We propose a learning AP that learns from experience and adapts the frame size according to the changes in the number of DT nodes. The proposed learning AP is also shown to learn well and react to the situation. We compare the performances of the proposed learning mechanism with a WPCN and conventional HT FSA schemes. The proposed RL scheme outperforms the comparative schemes in terms of success rate and delay.     

Highly Efficient and Less Time Consuming Additive Free Anisotropic Etching of Silicon Wafers for Photovoltaics

Silicon - Etching of silicon wafers has a great effect on increasing the efficiency of photovoltaic devices. Texturization can effectively reduce the front surface reflection and improve device...     

Synthesis and characterization of poly 2-N-acrylamido-2-methyl−1-propane sulfonic acid functionalized graphene oxide embedded electrolyte membrane using DOE for PEMFC

A novel proton exchange membrane consisting of 2-N-acrylamido-2-methyl−1-propane sulfonic acid modified graphene oxide nanocomposite (PAMPS-mGO), carboxylated poly(vinyl chloride) (CPVC), and poly 2-N-acrylamido-2-methyl−1-propane sulfonic acid (PAMPS) has been successfully prepared by simple and scalable polymer blending methodology. Different compositions of PEM in terms of its constituting precursors such as PAMPS-mGO, CPVC, and PAMPS were optimized by Placket Burman Design and their ion exchange capacity (IEC), oxidative stability, water uptake percentage, mechanical stability, and proton conductivity were evaluated. The amounts of significant precursors were further optimized by Central Composite Design. The membrane with excellent performance in PEMFC was obtained when appropriate proportions of CPVC (10%), PAMPS (20%), and PAMPS-mGO (20%) were blended. Among all membrane with mentioned composition exhibited IEC 1.3 mmol/g, oxidative stability 97.2%, WU 40.8%, proton conductivity 151 S/cm, water content 17.43, current density 1537 mA/cm² at 120°C, power density 566.5 mW/cm² at 120°C, Young modulus 797 MPa, tensile strength 16.8 MPa, and elongation at break % of 2.7 MPa. These results are in good comparison with PEM based on Nafion. Thus, the CPVC, PAMPS, and PAMPS-mGO-based composite PEM is a good candidate for PEMFC at elevated temperature under anhydrous conditions.     

Role of graphene and transition metal dichalcogenides as hole transport layer and counter electrode in solar cells

Photovoltaic (PV) technology got much attention in the past few decades in developing advanced and environment friendly solar cells (SCs). However, high cost, unstable nature, and low efficiency are major limitations towards commercialization of SCs. To overcome the issues, two-dimensional materials (2DMs) have been exploited due to low cost, high catalytic activity, fast charge separation, and better electrochemical performance. The review emphasis on (a) the electrochemical performance of graphene and transition metal dichalcogenides (TMDCs) as a hole transport layer (HTL) in SCs and (b) to explore low-cost and effective counter electrode (CE) based on graphene and TMDCs for dye-sensitized solar cell (DSSC). The review presents a comparative analysis of 2DMs as HTL and CE to attain highly efficient and low-cost PV devices. Multiple combinations of the material with graphene, graphene oxide (GO), reduced graphene oxide (rGO), tungsten disulfide (WS₂), molybdenum disulfide (MoS₂) as HTL, and CE material in PV cells are discussed and comparatively analyzed. Numerous strategies are briefly discussed to enhance the efficiency of SCs by utilizing graphene and TMDCs based HTL and CEs. The review focuses on the recent progress in developing low-cost and highly efficient PV devices by using 2DMs. Our study reveals that GO/PEDOT:PSS demonstrate a maximum power conversion efficiency (PCE) of 13.1% when fabricated at different revolutions. Moreover, our statistical analysis unveils that efficiency of the cell can be enhanced by optimizing the layer thickness, which provide a route to develop highly efficient and better performance SCs that can be exploited for future commercial applications.     

EkmEx - an extended framework for labeling an unlabeled fault dataset

Multimedia Tools and Applications - Software fault prediction (SFP) is a quality assurance process that identifies if certain modules are fault-prone (FP) or not-fault-prone (NFP). Hence, it...     

Multi Layered Rule-Based Technique for Explicit Aspect Extraction from Online Reviews

In the field of sentiment analysis, extracting aspects or opinion targets from user reviews about a product is a key task. Extracting the polarity of an opinion is much more useful if we also know the targeted Aspect or Feature. Rule based approaches, like dependency-based rules, are quite popular and effective for this purpose. However, they are heavily dependent on the authenticity of the employed parts-of-speech (POS) tagger and dependency parser. Another popular rule based approach is to use sequential rules, wherein the rules formulated by learning from the user’s behavior. However, in general, the sequential rule-based approaches have poor generalization capability. Moreover, existing approaches mostly consider an aspect as a noun or noun phrase, so these approaches are unable to extract verb aspects. In this article, we have proposed a multi-layered rule-based (ML-RB) technique using the syntactic dependency parser based rules along with some selective sequential rules in separate layers to extract noun aspects. Additionally, after rigorous analysis, we have also constructed rules for the extraction of verb aspects. These verb rules primarily based on the association between verb and opinion words. The proposed multi-layer technique compensates for the weaknesses of individual layers and yields improved results on two publicly available customer review datasets. The F1 score for both the datasets are 0.90 and 0.88, respectively, which are better than existing approaches. These improved results can be attributed to the application of sequential/syntactic rules in a layered manner as well as the capability to extract both noun and verb aspects.     

Automatic Detection of Weapons in Surveillance Cameras Using Efficient-Net

The conventional Close circuit television (CCTV) cameras-based surveillance and control systems require human resource supervision. Almost all the criminal activities take place using weapons mostly a handheld gun, revolver, pistol, swords etc. Therefore, automatic weapons detection is a vital requirement now a day. The current research is concerned about the real-time detection of weapons for the surveillance cameras with an implementation of weapon detection using Efficient–Net. Real time datasets, from local surveillance department's test sessions are used for model training and testing. Datasets consist of local environment images and videos from different type and resolution cameras that minimize the idealism. This research also contributes in the making of Efficient-Net that is experimented and results in a positive dimension. The results are also been represented in graphs and in calculations for the representation of results during training and results after training are also shown to represent our research contribution. Efficient-Net algorithm gives better results than existing algorithms. By using Efficient-Net algorithms the accuracy achieved 98.12% when epochs increase as compared to other algorithms.     

Assessment of AgNPs exposure on physiological and biochemical changes and antioxidative defence system in wheat (Triticum aestivum L) under heat stress

The present study was designed to check the role of silver nanoparticles (AgNPs) on physiological, biochemical parameters and antioxidants of wheat (Triticum aestivum L.) under heat stress. Plant extract of Moringa oleifera was used for AgNPs synthesis followed by characterization through UV–Vis spectroscopy, SEM, XRD and Zeta analyser. Heat stress was applied in range of 35–40°C for 3 hrs/ day for 3 days to wheat plants at trifoliate stage. Heat stress decreased the RWC (13.2%), MSI (16.3%), chl a (5.2%), chl b (4.1%) and TCCs (9.9%). Wheat plants treated with AgNPs showed significant increase in RWC (12.2%), MSI (26.5%), chl a (10%), chl b (16.4%), TCCs (19%), TPC (2.4%), TFC (2.5%), TASC (2.5%), SOD (1.3%), POX (1.5%), CAT (1.8%), APX (1.2%) and GPX (1.4%), under heat stress. Lower concentration of AgNPs (50 mg/l) decreased the sugar (5.8%) and proline contents (4%), while increase was observed in higher AgNPs concentrations. Overall, AgNPs treatment enhanced thermo‐tolerance in wheat plants, but the mechanism of AgNPs action needs further investigation at genome and proteome level in wheat plants under heat stress.Inspec keywords: crops, ultraviolet spectra, X‐ray diffraction, visible spectra, botany, microorganisms, scanning electron microscopy, solubility, agricultural products, nanoparticles, antibacterial activity, sugar, silver, food products, biochemistryOther keywords: heat stress, heat‐stress tolerance, wheat plants, AgNPs exposure, wheat antioxidative defence system, Triticum aestivum L, Moringa oleifera, biochemical parameters, silver nanoparticles, ultraviolet–visible spectroscopy, scanning electron microscopy, X‐ray diffraction, zeta analyser, total chlorophyll contents, TCCs, membrane stability index, MSI, malondialdehyde, sugar level, proline concentration, hydrogen peroxide, RWC, relative water content, total flavonoid content, phenolic content, ascorbate POX, guaiacol POX