The Impact of Trade Liberalization on Economic Growth: A case study of Pakistan

This study empirically analyzes the impact of trade liberalization on the economic growth of Pakistan over the period 1972 to 2014 .Gross fixed capital formation, Trade liberalization, Labor force participation, inflation, interest rate are important explanatory variables. While economic growth which is measured by (GDP) is dependent variable used for the model specification. The study used Johensen co-integration approach developed by Johensen and Jeselius (1990).The results show that trade liberalization and gross fixed capital have positive and significant impact on economic growth. Inflation and interest rate have negative impact on economic growth. And labor force has positive impact on economic growth. Positive correlation between trade liberalization and economic growth has been explored in this study. Keywords: Trade liberalization (LIBE), Economic growth (GDP), Co-Integration, Labour force participation (LFP), Interest rate (INT), Inflation (INF)

Collaborative detection of black hole and gray hole attacks for secure data communication in VANETs

Vehicle ad hoc networks (VANETs) are vital towards the success and comfort of self-driving as well as semi-automobile vehicles. Such vehicles rely heavily on data management and the exchange of Cooperative Awareness Messages (CAMs) for external communication with the environment. VANETs are vulnerable to a variety of attacks, including Black Hole, Gray Hole, wormhole, and rush attacks. These attacks are aimed at disrupting traffic between cars and on the roadside. The discovery of Black Hole attack has become an increasingly critical problem due to widespread adoption of autonomous and connected vehicles (ACVs). Due to the critical nature of ACVs, delay or failure of even a single packet can have disastrous effects, leading to accidents. In this work, we present a neural network-based technique for detection and prevention of rushed Black and Gray Hole attacks in vehicular networks. The work also studies novel systematic reactions protecting the vehicle against dangerous behavior. Experimental results show a superior detection rate of the proposed system in comparison with state-of-the-art techniques

UV-Light Mediated Biosynthesis of Silver Nanowires; Characterization, Dye Degradation Potential and Kinetic Studies

Herrin, a simple and eco-friendly method for the synthesis of silver nanowires (Ag-NWs) has been reported. Silver nanowires were synthesized using Psidium guajava seed extract that acted as a reducing agent as well as a stabilizing agent for silver nitrate solution. Synthesis was carried out at 50 °C temperature under continuous UV-irradiation. Silver nanowires were initially characterized by a UV-visible and FTIR spectrophotometer. In addition, morphology and particle size of synthesized Ag-NWs were determined using Field Emission Scanning Electron Microscopy and X-ray diffraction (XRD) techniques. Nanowires were found to have 12.8 μm length and 200–500 nm diameter and cubic phase morphology. Furthermore, the catalytic potential of Ag-NWs for the degradation of methyl orange dye (MO) was determined. The selected dye was degraded successfully that confirmed the catalytic potential of Ag-NWs. The authors concluded that Ag-NWs can be synthesized using plant extract having excellent morphological features as well as impressive catalytic potential

Web-based dynamic visualization of 3D spatial data

Abstract True 3D GIS requires lot of efforts from GIS research community both in academia as well as from software vendors. Visualizing 3D spatial data from DBMS for such 3D system is one of the issues and problems in 3D GIS domain. This paper discusses the dynamic visualization of 3D spatial data such as buildings and other large objects using geo-DBMS couples with Web that works with VRML and X3D modeling languages. The modeling of the 3D objects are based on the Simplified Data Model (SDM). The experiment will be presented by using digital 3D building datasets and the approach is applicable for tasks like 3D strata title and buildings management. Finally, it discusses the limitations and shortcomings of the current approach, and identifies future research and development tasks. Key words: 3D spatial data, VRML, X3D, visualization, and GeoDBMS

Collaborative Detection of Black Hole and Gray Hole Attacks for Secure Data Communication in VANETs

Vehicle ad hoc networks (VANETs) are vital towards the success and comfort of self-driving as well as semi-automobile vehicles. Such vehicles rely heavily on data management and the exchange of Cooperative Awareness Messages (CAMs) for external communication with the environment. VANETs are vulnerable to a variety of attacks, including Black Hole, Gray Hole, wormhole, and rush attacks. These attacks are aimed at disrupting traffic between cars and on the roadside. The discovery of Black Hole attack has become an increasingly critical problem due to widespread adoption of autonomous and connected vehicles (ACVs). Due to the critical nature of ACVs, delay or failure of even a single packet can have disastrous effects, leading to accidents. In this work, we present a neural network-based technique for detection and prevention of rushed Black and Gray Hole attacks in vehicular networks. The work also studies novel systematic reactions protecting the vehicle against dangerous behavior. Experimental results show a superior detection rate of the proposed system in comparison with state-of-the-art techniques

Spatio-temporal object relational model in (STORM)

This chapter presents a universal Object-Relational framework for spatio-temporal data modeling. Spatiotemporal data modeling aims to extend the existing data models to include space and time in order to better describe the dynamics real world. Space time are the most important and basic information in the real world. Many applications demand for spatio-temporal supports such type of applications include forecast prediction systems recording weather change process, surveillance applications, transportation systems, mobile communication systems and geographical and environmental systems and so on. However, the existing database techniques still problematic in supporting the spatio-temporal information management. After almost 20 years’ research, representation of space and time in databases and functional applications are still problematic

Current and Emerging Adsorbent Technologies for Wastewater Treatment: Trends, Limitations, and Environmental Implications

Wastewater generation and treatment is an ever-increasing concern in the current century due to increased urbanization and industrialization. To tackle the situation of increasing environmental hazards, numerous wastewater treatment approaches are used—i.e., physical, chemical, and biological (primary to tertiary treatment) methods. Various treatment techniques being used have the risks of producing secondary pollutants. The most promising technique is the use of different materials as adsorbents that have a higher efficacy in treating wastewater, with a minimal production of secondary pollutants. Biosorption is a key process that is highly efficient and cost-effective. This method majorly uses the adsorption process/mechanism for toxicant removal from wastewater. This review elaborates the major agricultural and non-agricultural materials-based sorbents that have been used with their possible mechanisms of pollutant removal. Moreover, this creates a better understanding of how the efficacy of these sorbents can be enhanced by modification or treatments with other substances. This review also explains the re-usability and mechanisms of the used adsorbents and/or their disposal in a safe and environmentally friendly way, along with highlighting the major research gaps and potential future research directions. Additionally, the cost benefit ratio of adsorbents is elucidated