The Determinants of Pakistan’s Bilateral Trade and Trade Potential with World: A Gravity Model Approach

Nonlinear measurement of gravity model with PPML regression technique has become admired for modeling international trade flows since it approves a better accounting for zero flows and excessive values in distribution tail. In the present study, we have endeavored to investigate the bilateral trade milieu of Pakistan with 198 trading cohorts over the time epoch (1992-2016) 25 years and to stumble on latent markets in case of Pakistan’s bilateral trade. The empirical results revealed that market size, bilateral exchange rates, income differential, common religion, border, and trade agreements positively influence bilateral trade volume while bilateral distance and landlocked countries showed a negative relationship towards bilateral trade of Pakistan with rest of the world. The outcome also illustrates that the trade pattern of Pakistan hinges on the Heckscher-Ohlin (H-O) theory, therefore, can be explained by the dissimilarity in factor endowments whereas the WTO membership does not have any influence on bilateral trade of Pakistan. Pakistan owns satisfactory potential to enhance its bilateral trade with nearly 102 countries. The highest potential lies with countries Saudi Arabia, Malaysia, Somalia, Hong Kong, Iran and USA whereas actual trade has exceeded with countries like China, Oman, Spain, UAE, Germany, and the UK. Hence, there is need to address all measures to improve bilateral trade with potential countries moreover per se Pakistan can perhaps decrease or handle the trade discrepancy by targeting these economies, to bring about a reasonable quality in mutual trading relations

Modelling of abrasive waterjet milled footprints

Abrasive waterjet (AWJ) cutting is one of the most promising fast emerging non-traditional cutting technologies. It is highly competitive for machining difficult-to-cut materials like ceramics, composites and titanium alloys as compared to other nonconventional processes (e.g. laser, EDM) which are either technologically inappropriate or fail to be cost-effective. However, at the moment most of the usage of the AWJ machining lies in the area of the through cutting applications and to perform controlled depth cutting (milling) is still at craftsmanship level. This is due to the facts that: (i) AWJ machining is based on employing a jet plume as a "soft body" tool, the footprint of which not only depends on the jet energy parameters (e.g. pressure, abrasive mass flow rate, etc) but also on the jet kinematic parameters (e.g. jet traverse speed) which make controlling of the jet penetration depth very difficult; (ii) there is absence of the appropriate and reliable models that can simulate and predict the AWJ milled footprints and this is one of the major obstructions constraining the use of the AWJ milling applications. The aim of this thesis is to develop accurate models for predicting the A WJ milled footprints. The workpiece material considered is a titanium based superalloy (Ti-6Al- 4V) which is extensively used in the aerospace and medical industry. Two modelling approaches; finite element (FE) modelling and mathematical modelling are presented in this work. Considerable numbers of experiments are conducted to generate the data for validating the results from the models. The models presented in the current study are closer to the real life conditions occurring during the A WJ machining as compared to the state of the art in modelling of AWJ machining. Regarding the FE modelling, the abrasive particles (i.e. garnet) are modeled as elastic with a tensile failure criterion with various non-spherical shapes (rhombic, triangular and trapezoidal) and sharp cutting edges in contrast to the usual approach of assuming them as rigid spherical particles. The effects of mass flow rate of the abrasive particles, traverse speed of the AWJ plume across the workpiece and Gaussian spatial distribution of the abrasive particles in the jet plume are also incorporated in the FE model. The FE model is developed to an extent that it can simulate the footprints as a result of overlapping passes of the AWJ. The simulated jet footprints from the FE models are in good agreement (maximum errors ≤ 15%) with the experimental results. From the mathematical modelling point of view, a model is developed that can accurately predict the AWJ milled footprints with root-mean-squared errors less than 9%. The model takes into account the effects of jet incidence angles, traverse speeds and arbitrarily-moving jet-paths within the target surface. The model is computationally inexpensive and can be used for real time predictions of footprints during CNC machining. The current study provides the reliable models that can be employed for accurate prediction of the abrasive waterjet milled footprints at various process parameters which is a necessary step towards the exploitation of the A WJ machining for controlled depth cutting applications and its automation

Modelling of abrasive waterjet milled footprints

Abrasive waterjet (AWJ) cutting is one of the most promising fast emerging non-traditional cutting technologies. It is highly competitive for machining difficult-to-cut materials like ceramics, composites and titanium alloys as compared to other nonconventional processes (e.g. laser, EDM) which are either technologically inappropriate or fail to be cost-effective. However, at the moment most of the usage of the AWJ machining lies in the area of the through cutting applications and to perform controlled depth cutting (milling) is still at craftsmanship level. This is due to the facts that: (i) AWJ machining is based on employing a jet plume as a "soft body" tool, the footprint of which not only depends on the jet energy parameters (e.g. pressure, abrasive mass flow rate, etc) but also on the jet kinematic parameters (e.g. jet traverse speed) which make controlling of the jet penetration depth very difficult; (ii) there is absence of the appropriate and reliable models that can simulate and predict the AWJ milled footprints and this is one of the major obstructions constraining the use of the AWJ milling applications. The aim of this thesis is to develop accurate models for predicting the A WJ milled footprints. The workpiece material considered is a titanium based superalloy (Ti-6Al- 4V) which is extensively used in the aerospace and medical industry. Two modelling approaches; finite element (FE) modelling and mathematical modelling are presented in this work. Considerable numbers of experiments are conducted to generate the data for validating the results from the models. The models presented in the current study are closer to the real life conditions occurring during the A WJ machining as compared to the state of the art in modelling of AWJ machining. Regarding the FE modelling, the abrasive particles (i.e. garnet) are modeled as elastic with a tensile failure criterion with various non-spherical shapes (rhombic, triangular and trapezoidal) and sharp cutting edges in contrast to the usual approach of assuming them as rigid spherical particles. The effects of mass flow rate of the abrasive particles, traverse speed of the AWJ plume across the workpiece and Gaussian spatial distribution of the abrasive particles in the jet plume are also incorporated in the FE model. The FE model is developed to an extent that it can simulate the footprints as a result of overlapping passes of the AWJ. The simulated jet footprints from the FE models are in good agreement (maximum errors ≤ 15%) with the experimental results. From the mathematical modelling point of view, a model is developed that can accurately predict the AWJ milled footprints with root-mean-squared errors less than 9%. The model takes into account the effects of jet incidence angles, traverse speeds and arbitrarily-moving jet-paths within the target surface. The model is computationally inexpensive and can be used for real time predictions of footprints during CNC machining. The current study provides the reliable models that can be employed for accurate prediction of the abrasive waterjet milled footprints at various process parameters which is a necessary step towards the exploitation of the A WJ machining for controlled depth cutting applications and its automation

Comparative Economic Benefits of Different Oat Varities in Rainfed Areas of Pothwar, Pakistan

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Effect of 3 Key Factors on Average End to End Delay and Jitter in MANET

A mobile ad-hoc network (MANET) is a self-configuring infrastructure-less network of mobile devices connected by wireless links where each node or mobile device is independent to move in any desired direction and thus the links keep moving from one node to another. In such a network, the mobile nodes are equipped with CSMA/CA (carrier sense multiple access with collision avoidance) transceivers and communicate with each other via radio. In MANETs, routing is considered one of the most difficult and challenging tasks. Because of this, most studies on MANETs have focused on comparing protocols under varying network conditions. But to the best of our knowledge no one has studied the effect of other factors on network performance indicators like throughput, jitter and so on, revealing how much influence a particular factor or group of factors has on each network performance indicator. Thus, in this study the effects of three key factors, i.e. routing protocol, packet size and DSSS rate, were evaluated on key network performance metrics, i.e. average delay and average jitter, as these parameters are crucial for network performance and directly affect the buffering requirements for all video devices and downstream networks

Multi Criteria Optimization Approach for Dressing of Vitrified Grinding Wheel

Rotary diamond dressers are widely used for the dressing to improve the efficiency of vitrified grinding wheel. The paper focuses on the process parameters, i.e., feed speed of dresser, depth of cut, grinding wheel velocity, velocity ratio between grinding wheel and rotary dresser, number of pass and dressing method (up-cut or down-cut) in rotary diamond dressing. The objective is to investigate the effect of these process parameters with their interactions for two response parameters, dressing ratio and overlapped dressed area. As far as the response parameters are concerned, the goal is to maximize dressing ratio and minimize overlapped dressed area simultaneously. Thirty-six experiments were designed and performed. Analysis of variance and multi-criteria optimization approach are opted to find out significant process parameters and optimal parameter setting. Finally, the significant process parameters, dressing method and number of pass are identified as well and the optimal parameter setting is also determined

Effect of Sowing Dates and Seed Rates on the Agro-Physiological Traits of Wheat

Wheat yield in Pakistan is very low due to improper seed rate and not sowing the crop at proper time. Delay in sowing of wheat causes linear reduction in grain yield. To evaluate the effect of seed rates and sowing dates on agro-physiological traits of wheat an experiment was conducted at New Developmental Farm, The University of Agriculture Peshawar-Pakistan during winter 2012-13. Randomized complete block design (RCBD) with split plot arrangement having three replications was used. Sowing dates (29th October, 10th November, 24th November, 10th December, 26th December and 10th January) were kept in the main plots, whereas, seed rates (120,150,180 kg ha-1) were allotted to sub plots. Wheat variety “SIRAN-2010” was sown in a plot size of 5m x 1.8m (9 m2), having six rows with row to row distance of 30 cm and row length 5m. All the standard agronomic practices were uniformly adopted for the whole experiment. Results showed that maximum spikes m-2 (411), grains spike-1 (52), thousand grains weight (43 g), biological yield (12327 kg ha-1) and grain yield (5587 kg ha-1) were recorded in plots sown at 10th November. Seed rate of 150 kg ha-1 showed maximum number of grains spike-1 (44), spikes m-2 (307), thousand grains weight (37g), biological yield (9568 kg ha-1) and grain yield (4296 kg ha-1). It was concluded from the results that wheat should preferably be sown between 29th October and 24th November at 150 kg ha-1 seed rate to get higher grain yield in Peshawar valley

Enhancing EDM Machining Precision through Deep Cryogenically Treated Electrodes and ANN Modelling Approach

The critical applications of difficult-to-machine Inconel 617 (IN617) compel the process to be accurate enough that the requirement of tight tolerances can be met. Electric discharge machining (EDM) is commonly engaged in its machining. However, the intrinsic issue of over/undercut in EDM complicates the achievement of accurately machined profiles. Therefore, the proficiency of deep cryogenically treated (DCT) copper (Cu) and brass electrodes under modified dielectrics has been thoroughly investigated to address the issue. A complete factorial design was implemented to machine a 300 μm deep impression on IN617. The machining ability of DCT electrodes averagely gave better dimensional accuracy as compared to non-DCT electrodes by 13.5% in various modified dielectric mediums. The performance of DCT brass is 29.7% better overall compared to the average value of overcut (OC) given by DCT electrodes. Among the non-treated (NT) electrodes, the performance of Cu stands out when employing a Kerosene-Span-20 modified dielectric. In comparison to Kerosene-Tween-80, the value of OC is 33.3% less if Kerosene-Span-20 is used as a dielectric against the aforementioned NT electrode. Finally, OC’s nonlinear and complex phenomena are effectively modeled by an artificial neural network (ANN) with good prediction accuracy, thereby eliminating the need for experiments

Effect of different cooling strategies on surface quality and power consumption in finishing end milling of stainless steel 316

In this paper, an experimental investigation into the machinability of AISI 316 alloy during finishing end milling operation under different cooling conditions and with varying process parameters is presented. Three environmental-friendly cooling strategies were utilized, namely, dry, minimal quantity lubrication (MQL) and MQL with nanoparticles (Al$_{2}$O$_{3}$),and the variable process parameters were cutting speed and feed rate. Power consumption and surface quality were utilized as the machining responses to characterize the process performance. Surface quality was examined by evaluating the final surface roughness and surface integrity of the machined surface. The results revealed a reduction in power consumption when MQL and MQL + Al$_{2}$O$_{3}$ strategies were applied compared to the dry case by averages of 4.7% and 8.6%, respectively. Besides, a considerable reduction in the surface roughness was noticed with average values of 40% and 44% for MQL and MQL + Al$_{2}$O$_{3}$ strategies, respectively, when compared to the dry condition. At the same time, the reduction in generated surface roughness obtained by using MQL + Al$_{2}$O$_{3}$condition was marginal (5.9%) compared with using MQL condition. Moreover, the results showed that the improvement obtained in the surface quality when using MQL and MQL + Al$_{2}$O$_{3}$ coolants increased at higher cutting speed and feed rate, and thus, higher productivity can be achieved without deteriorating final surface quality, compared to dry conditions. From scanning electron microscope (SEM) analysis, debris, furrows, plastic deformation irregular friction marks, and bores were found in the surface texture when machining under dry conditions. A slight smoother surface with a nano-polishing effect was found in the case of MQL + Al$_{2}$O$_{3}$ compared to the MQL and dry cooling strategies. This proves the effectiveness of lubricant with nanoparticles in reducing the friction and thermal damages on the machined surface as the friction marks were still observed when machining with MQL comparable with the case of MQL + Al$_{2}$O$_{3}$