Showing papers by "Ghulam Ishaq Khan Institute of Engineering Sciences and Technology published in 2016"

Influence of organizational rewards on organizational commitment and turnover intentions

Abstract: Purpose – The purpose of this paper is to explore the relationship between extrinsic, intrinsic and social rewards and two components of organizational commitment and finally Chinese workers turnover intention in public and private sector. Design/methodology/approach – A questionnaire was utilized as the method for data collection. Structural equation modeling was utilized to examine survey data obtained from 202 employees in the southern part of China. Findings – The findings exhibit that extrinsic, social and intrinsic rewards were significantly related to affective and normative commitment. Findings suggest that satisfaction with extrinsic benefits, supervisor support, coworker support, autonomy, training and participation in decision making has substantial impact on employee’s affective and normative commitment. However, affective and normative commitment was negatively related to employee turnover intention. Research limitations/implications – This study covers different public and private-sector org...

Artificial intelligence techniques for driving safety and vehicle crash prediction

Abstract: Accident prediction is one of the most critical aspects of road safety, whereby an accident can be predicted before it actually occurs and precautionary measures taken to avoid it. For this purpose, accident prediction models are popular in road safety analysis. Artificial intelligence (AI) is used in many real world applications, especially where outcomes and data are not same all the time and are influenced by occurrence of random changes. This paper presents a study on the existing approaches for the detection of unsafe driving patterns of a vehicle used to predict accidents. The literature covered in this paper is from the past 10 years, from 2004 to 2014. AI techniques are surveyed for the detection of unsafe driving style and crash prediction. A number of statistical methods which are used to predict the accidents by using different vehicle and driving features are also covered in this paper. The approaches studied in this paper are compared in terms of datasets and prediction performance. We also provide a list of datasets and simulators available for the scientific community to conduct research in the subject domain. The paper also identifies some of the critical open questions that need to be addressed for road safety using AI techniques.

Room temperature spin valve effect in NiFe/WS₂/Co junctions.

Abstract: The two-dimensional (2D) layered electronic materials of transition metal dichalcogenides (TMDCs) have been recently proposed as an emerging canddiate for spintronic applications. Here, we report the exfoliated single layer WS2-intelayer based spin valve effect in NiFe/WS2/Co junction from room temperature to 4.2 K. The ratio of relative magnetoresistance in spin valve effect increases from 0.18% at room temperature to 0.47% at 4.2 K. We observed that the junction resistance decreases monotonically as temperature is lowered. These results revealed that semiconducting WS2 thin film works as a metallic conducting interlayer between NiFe and Co electrodes.

Influence of thermal radiation and Joule heating in the Eyring–Powell fluid flow with the Soret and Dufour effects

Abstract: A two-dimensional magnetohydrodynamic boundary layer flow of the Eyring–Powell fluid on a stretching surface in the presence of thermal radiation and Joule heating is analyzed. The Soret and Dufour effects are taken into account. Partial differential equations are reduced to a system of ordinary differential equations, and series solutions of the resulting system are derived. Velocity, temperature, and concentration profiles are obtained. The skin friction coefficient and the local Nusselt and Sherwood numbers are computed and analyzed.

An institutional perspective on entrepreneurship in a conflict environment: Evidence from Pakistan

Abstract: Purpose – In this paper, an institutional perspective is used to examine the different kinds of pressures on entrepreneurs manifest in a conflict environment. The purpose of this paper is to investigate how they respond to the conflict and establish legitimacy for their entrepreneurship in the challenging context of the north western areas of Pakistan. Design/methodology/approach – In this study, a qualitative approach is taken based on semi-structured interviews from 16 different firms in the Swat valley. Findings – The entrepreneurs undertake different strategies towards dealing with conflict and establishing legitimacy. These strategies are identified and examined in relation to the interactions between entrepreneurial behaviour and institutional pressures. Research limitations/implications – Qualitative research on a small sample inevitably presents a limitation on the generalisability of this work. Further research could employ quantitative methods to address this issue. One particular location is st...

A novel core@shell magnetic molecular imprinted nanoparticles for selective determination of folic acid in different food samples

Abstract: In this work, magnetic molecularly imprinted polymers (MMIPs) were synthesized and tested for the determination of folic acid (FA) in different food samples. The MMIPs were polymerized at the surface of Fe3O4@SiO2 magnetic nanoparticles (MNPs) using acrylonitrile (functional monomer), ethylene glycol dimethacrylate (EGDMA) as cross-linking agent and azobiisobutyronitrile (AIBN) as an radical initiator. The morphological, topological and chemical characteristics of the MMIPs were investigated by field emission scanning electron microscopy (FESEM), high resolution transmission electron microscopy (HRTEM) and Fourier transform infrared (FTIR) techniques. The physico-chemical characterization, such as adsorption capacities and selectivity of MMIPs was investigated and compared with the respective MNIPs. The adsorption experimental data demonstrate that maximum adsorption capacity of MMIP at equilibrium was 8 mg g− 1 and than the adsorption process of FA over MMIPs follows Freundlich adsorption isotherm model and pseudo-first-order reaction kinetic. For evaluation of this new proposed material, the recovery studies were carried out in spiked samples at different concentration levels and the obtained values were in the range of 95–104% for orange and for spinach the recoveries were between 99.5 and 102.5%. The relative standard deviations (RSD) for the recoveries were < 0.5% for both samples. These results demonstrate that this novel MMIP material can be efficiently used for the selective extraction of folic acid from different food complex matrices.

Employing artificial neural networks for constructing metadata-based model to automatically select an appropriate data visualization technique

Abstract: Display Omitted Solution to automatically select appropriate visualization technique based on metadata is presented.A purpose built dataset extracted from existing knowledge in the field is used to train classifiers.A comparison of the results obtained from the best ANN architecture is performed with five other classifiers.The proposed system outperforms four classifiers in terms of accuracy and five classifiers based on running time.The work brings new perspective in the field of visualization. Advances in computing technology have been instrumental in creating an assortment of powerful information visualization techniques. However, the selection of a suitable and effective visualization technique for a specific dataset and a data mining task is not trivial. This work automatically selects an appropriate visualization technique based on the given metadata and the task that a user intends to perform. The appropriate visualization is predicted based on an artificial neural network (ANN)-based model which classifies the input data into one of the eight predefined classes. A purpose built dataset extracted from the existing knowledge in the discipline is utilized to train the neural network. The dataset covers eight visualization techniques, including: histogram, line chart, pie chart, scatter plot, parallel coordinates, map, treemap, and linked graph. Various architectures using different numbers of hidden units, hidden layers, and input and output data formats have been evaluated to find the optimal neural network architecture. The performance of neural networks is measured using: confusion matrix, accuracy, precision, and sensitivity of the classification. Optimal neural network architecture is determined by convergence time and number of iterations. The results obtained from the best ANN architecture are compared with five other classifiers, k-nearest neighbor, nave Bayes, decision tree, random forest, and support vector machine. The proposed system outperforms four classifiers in terms of accuracy and all five classifiers based on execution time. The trained neural network is also tested on twenty real-world benchmark datasets, where the proposed approach also provides two alternate visualizations, in addition to the most suitable one, for a particular dataset. A qualitative comparison with the state-of-the-art approaches is also presented. The results show that the proposed technique assists in selecting an appropriate visualization technique for a given dataset with high accuracy.

Fabrication and investigation of cellulose acetate-copper oxide nano-composite based humidity sensors

Abstract: Cellulose acetate-copper oxide (CA-CuO) nano-composite based smart humidity sensors have been fabricated by using instrument-less novel technology, which is being introduced first time by our group. In this technology no major instrument is involved in the fabrication process. The composites are developed by solution and mechanical mixing techniques to fabricate film and pellet type sensors, respectively. The composition and surface morphologies are analyzed by field emission scanning electron microscopy (FESEM) and energy dispersive spectroscopy (EDS). Results of investigation show that the sensing range is from 0 to 90% relative humidity (RH) and sensing mechanism is based on change in resistance and capacitance with change in humidity. With change in humidity from 0 to 90% RH the resistance decreases by 1093 times, while the capacitance increases by 127 times. Average change in resistance and capacitance is up to 3.8 MΩ/%RH and 19.2 pF/%RH, respectively. The adsorption-desorption behavior and the consequences of measuring frequency have been discussed in detail. The fabricated sensors are attractive to develop reliable humidity meter for environmental monitoring and industrial applications.

Profiling drivers based on driver dependent vehicle driving features

Abstract: This work addresses the problem of profiling drivers based on their driving features. A purpose-built hardware integrated with a software tool is used to record data from multiple drivers. The recorded data is then profiled using clustering techniques. k-means has been used for clustering and the results are counterchecked with Fuzzy c-means (FCM) and Model Based Clustering (MBC). Based on the results of clustering, a classifier, i.e., an Artificial Neural Network (ANN) is trained to classify a driver during driving in one of the four discovered clusters (profiles). The performance of ANN is compared with that of a Support Vector Machine (SVM). Comparison of the clustering techniques shows that different subsets of the recorded dataset with a diverse combination of attributes provide approximately the same number of profiles, i.e., four. Analysis of features shows that average speed, maximum speed, number of times brakes were applied, and number of times horn was used provide the information regarding drivers' driving behavior, which is useful for clustering. Both one versus one (SVM) and one versus rest (SVM) method for classification have been applied. Average accuracy and average mean square error achieved in the case of ANN was 84.2 % and 0.05 respectively. Whereas the average performance for SVM was 47 %, the maximum performance was 86 % using RBF kernel. The proposed system can be used in modern vehicles for early warning system, based on drivers' driving features, to avoid accidents.

Decoupled Downlink-Uplink Coverage Analysis with Interference Management for Enriched Heterogeneous Cellular Networks

Abstract: Heterogeneous cellular networks (HetCNets) offer a promising solution to cope with the current cellular coverage crunch. Due to the large transmit power disparity, while following maximum power received (MPR) association scheme, a larger number of users are associated with macro-cell BS (MBS) than small-cell BSs (SBSs). Therefore, an imbalance load arrangement takes place across the HetCNets. Hence, using cell range expansion-based cell association, we can balance the load across the congested MBS. However, using MPR association scheme, users’ offloading leads to two challenges: 1) macro-cell interference , in which the MBS interferes with the offloaded users, and 2) coupled downlink-uplink cell association , in which a random user associates with a single tier’s base station (BS) both in uplink (UL) and downlink (DL) directions. This paper aims to address these problems while considering a two-tier scenario consisting of small-cell and macro-cell tiers. For the MBS interference mitigation, we employ a reverse frequency allocation (RFA) scheme. Besides coupled DL–UL association (Co-DUA), this paper also highlights the notion of decoupled DL–UL association (De-DUA). In De-DUA, a random user associates with two different tiers’ BSs, i.e., with one tier’s BS in the DL direction and with the other tier’s BS in the UL direction. Our results illustrate that, in comparison with the Co-DUA, De-DUA with RFA employment achieves a better coverage performance.

Synthesis, modeling and photovoltaic properties of a benzothiadiazole based molecule for dye-sensitized solar cells

Abstract: A benzothiadiazole based solution-processable organic dye D1 (N 4-Phenyl-N 4,N 7,N 7-tri{4-[(2-ethoxycarbonyl)-2-cyanovinyl]phenyl}benzo[c][1,2,5]thiadiazole-4,7-diamine) was synthesized. Dye-sensitized solar cells (DSSCs) were fabricated based on D1 and a commercially available benzothiadiazole based RK1 dye. The photovoltaic parameters of these cells were studied under simulated AM 1.5 illumination (100 mW cm−2). The DSSC sensitized by RK1 dye provided a power conversion efficiency of 5.7 % with high values of short-circuit photocurrent density, open-circuit photovoltage, and fill factor. Under the same conditions, the cell sensitized with D1 dye showed a very poor performance due to the lower values of short-circuit photocurrent density and open-circuit photovoltage. In order to provide insight into poor performance of the DSSC sensitized by D1, molecular structure of D1 was analyzed by density functional theory. Its frontier orbitals were calculated to investigate effectiveness of charge transport and reasons of the poor performance. This computational study revealed that the photovoltaic performance of the benzothiadiazole based DSSCs can be enhanced significantly by inserting a phenyl ring between the benzothiadiazole unit and the anchoring group.

Design and analysis of capacitance based Bio-MEMS cantilever sensor for tuberculosis detection

Abstract: Recently, Micro Electro-Mechanical systems (MEMS) have been vital in molecular diagnosis. In this paper, micro-cantilever beam based bio-sensing system is designed and analyzed for the detection of bio-molecules. Modal and static analysis is performed to study the vibration frequencies and deflection of cantilever respectively. The surface of the cantilever is coated with the anti-bodies of the suspected antigen in a patient's blood. The anti-bodies are specific for specific antigens. Hence, the presence of mycobacterium tuberculosis in a suspected patient's blood is identified through the deflection of cantilever beam. The deflection of the beam is detected using capacitance method. 3D finite element analysis is performed to study the stability, sensitivity and modal frequencies of the cantilever beam(s). The modal frequencies are very important in vibration to voltage conversion of a capacitor for deflection detection. Fixed beam and stepped beam are also considered for comparison. The model is found to be cost effective as well as simple when compared to the conventional techniques like ELISA and PCR.

Design and implementation of waveguide bandpass filter using complementary metaresonator

Abstract: During past few years, designing of complementary metamaterials-based microwave devices have extensively increased. In this paper, passband filter for rectangular waveguide is designed using complementary symmetric split-ring resonator (CSSRR). By varying different geometrical parameters of CSSRR, the passband frequency and bandwidth can be varied. Effect of design parameter on quality factor of filter is also calculated. By appropriate choice of CSSRR geometrical parameters, a filter is proposed which gives passband of 2 GHz. The results are calculated numerically using HFSS 14.0.

A robust H ∞ control for unmanned aerial vehicle against atmospheric turbulence

Abstract: Unmanned aerial vehicles (UAVs) experience different atmospheric uncertainties during the flight operation. These uncertainties caused the problem in the stability and the desired performance of the system. This research paper is structured to nullify the influence of atmospheric turbulence and ground effect on the unmanned aerial vehicle to control the roll angle. The model of Dryden turbulence is used as it is one of the major disturbances affecting the UAVs and then dynamic output feedback robust controller is synthesized using linear matrix inequality (LMI) approach to minimize the effect of atmospheric turbulence in the plant. This research managed to design controller so that it can meet both robustness and stability requirements. To investigate the performance of proposed technique, robust control effort is compared with optimal LQR control law. The simulation results show that robust dynamic output feedback control has achieved good transient and steady state performance than LQR optimal control against atmospheric turbulence.

A Heterogeneous Service-Oriented Deep Packet Inspection and Analysis Framework for Traffic-Aware Network Management and Security Systems

Abstract: A variety of Web-based applications, mobile apps, and other over the top data services with affordable 3G/4G enabled smart devices are major factors for enormous increase in heterogeneous data traffic at enterprise and mobile networks. This creates challenges regarding traffic management and requires traffic-aware intelligent network management to deliver sustained quality of experience for subscribers. Deep packet inspection and analysis (DPIA) provides base platform for development of traffic-aware intelligent network management and security systems. However, computationally complex DPIA-related packet processing for high speed data traffic makes these systems expensive. Furthermore, conventionally these traffic-aware network management and security systems are deployed in enterprise networks with independent and dedicated DPIA-related processing resources and require multiple copies of passively provisioned high speed data from network, while performing similar DPIA operations over the same data again and again. This duplicate deployment of expensive software and hardware resources for DPIA processing eventually results in higher capital expenditures as well as operational expenditures for network operators. We have proposed a novel service-oriented framework for heterogeneous deep packet inspection and analysis (SoDPI) that simultaneously provides diversified DPIA services to multiple client applications for network management and security operations in high-speed networks. Proposed framework provides flexible and comprehensive API-based service interface for client applications to register required DPIA services. SoDPI framework implementation is based on commodity hardware and deploys shared set of DPIA-related packet processing components, requiring only single copy of passive data provisioned from network. Experimental evaluations show that novel SoDPI framework requires considerably reduced amount of software and hardware resources to fulfill heterogeneous DPIA packet processing requirements for multiple client applications in comparison with conventional network management and security applications with dedicated DPIA components. This results in lower cost impacts for network operators with more network manageability.

Assessment of material properties of AISI 316L stainless steel using non-destructive testing

Abstract: Ultrasonic testing (UT) is one of the most widely used non-destructive testing techniques for the characterisation and the evaluation of materials. In this work, material properties of AISI 316L stainless steel are assessed using UT. Changes in ultrasound velocity, attenuation and hardness are observed in heat-treated material at different temperatures. Specimens analysed at granular level through optical and scanning electron microscope exhibited change in the grain structure at various heat treatment temperatures. It was observed that the change in grain size also affected the mechanical vis-a-vis ultrasonic properties. In conclusion, the empirical results are also deduced in form of a relationship between UT parameters and mechanical properties of the material.

Temperature-dependent nuclear partition functions and abundances in the stellar interior

Abstract: We calculate the temperature-dependent nuclear partition functions (TDNPFs) and nuclear abundances for 728 nuclei, assuming nuclear statistical equilibrium (NSE). The theories of stellar evolution support NSE. Discrete nuclear energy levels have been calculated microscopically, using the pn-QRPA theory, up to an excitation energy of 10 MeV in the calculation of the TDNPFs. This feature of our paper distinguishes it from previous calculations. Experimental data is also incorporated wherever available to ensure the reliability of our results. Beyond 10 MeV, we employ a simple Fermi gas model and perform integration over the nuclear level densities to approximate the TDNPFs. We calculate nuclidic abundances, using the Saha equation, as a function of three parameters: stellar density, stellar temperature and the lepton-to-baryon content of stellar matter. All these physical parameters are considered to be extremely important in the stellar interior. The results obtained in this paper show that the equilibrium configuration of nuclei remains unaltered by increasing the stellar density (only the calculated nuclear abundances increase by roughly the same order of magnitude). Increasing the stellar temperature smoothes the equilibrium configuration showing peaks at the neutron-number magic nuclei.

Indentation and deformation behavior of FeCo-based bulk metallic glass alloys

Abstract: FeCo-based bulk metallic glass with the compositions (Fe0.5Co0.5)69−xNb6B25+x (x=0, 2, 4) were cast using electric arc melting and suction casting technique. The samples were tested and analyzed in as-cast, sub-Tg annealed and partially crystalline conditions. Vicker’s microhardness was found to increase after annealing and partial crystallization. For high boron content hardness values approaching 1400 HV were obtained in partially crystalline samples. A compressive strength value of 4776 MPa was calculated using hardness data. Sub-Tg annealing resulted in a decrease in the size of deformation zone formed underneath the hardness indenter after indentation. The bulk metallic glass alloys were embrittled by the partial crystallization treatment. It resulted in the formation of corner cracks during indentation. The size of the deformation zone increased with an increase in load. Semicircular and radial type of shear bands were observed as in the deformation zone with a higher number of radial shear bands observed in the annealed samples compared to as-cast samples. A comparison is made between the size of the deformation zone obtained experimentally and that predicted by the available models.

Analysis of interference avoidance with load balancing in heterogeneous cellular networks

Abstract: In heterogeneous cellular networks (HCNets) smallcells are overlaid with macro-cells to handle heavy cellular data traffic in an efficient way. To achieve fast and reliable access to data with a better coverage it is necessary to offload users to the underutilized small-cells from the congested macro-cells. Sharing of the same licensed frequency spectrum by smallcells and macro-cells results in heavy cross-tier interference which significantly affects the downlink SINR. In this paper, we investigate and analyze a joint frequency-division duplex based cross-tier complementary spectrum sharing technique which is also regarded as reverse frequency allocation (RFA) scheme with load balancing. This scheme mitigates inter-cell interference (ICI) and better balances the load across the network. It also guarantees enhanced spectral efficiency and coverage probability, particularly for cell edge users (CEUs). Numerical results indicate that load balancing together with RFA is necessary to enhance the coverage of CEU in co-channel HCNets.

Role of copper addition on properties of bulk metallic glass materials

Abstract: In this paper the role of copper addition has been studied to examine thermal, mechanical, magnetic and corrosion properties of the Fe43Co22Ni7B19Si5Nb4 bulk metallic glass alloy material. It is found that the copper addition in alloys exhibited low supercooled liquid region as compared to copper-free alloy. It is observed that microhardness was reduced in Cu-containing alloy with generation of shear bands along faces of micro indent impression while in Cu-free alloy straight and long microcracks appeared at the indent corners indicating its brittle behavior. The magnetic properties slightly decrease with Cu addition however the corrosion resistance of Cu-containing alloy showed superior properties indicating commercial benefits in aggressive environment.

A proposed optimized solution for wireless power transfer using magnetic resonance coupling

Abstract: In this modern system, power is part of our lives. These days power is being transmitted through wires and it has some limitations like in medical area or in robotics because it's difficult to be connected with wires all the time. Rechargeable batteries are also not feasible solution because they needed to be charged regularly and also carry some weight and space. In medical area pacemakers and defibrillators need to be installed inside human skin and required to replace their batteries after specific interval of time. But using wireless power transfer we can charger their batteries without cutting skin. Wireless power transfer (WPT) is under development technology these days. Researchers have developed many techniques to transfer power without wires but recently MIT researcher's demonstration got attention when they transmitted 60W over a distance of two meters using WPT magnetic resonance technique but the efficiency and range remained serious problem. This paper will describe optimized model of maximum wireless power transfer and also way to increase the range between transmitting and receiving coil.

Flexible impedance and capacitive tensile load Sensor based on CNT composite

Abstract: In this paper, the fabrication and investigation of flexible impedance and capacitive tensile load sensors based on carbon nanotube (CNT) composite are reported. On thin rubber substrates, CNTs are deposited from suspension in water and pressed at elevated temperature. It is found that the fabricated load cells are highly sensitive to the applied mechanical force with good repeatability. The increase in impedance of the cells is observed to be 2.0 times while the decrease in the capacitance is found to be 2.1 times as applied force increases up to 0.3 N. The average impedance and capacitive sensitivity of the cell are equal to 3.4 N−1 and 1.8 N−1, respectively. Experimental results are compared with the simulated values, and they show that they are in reasonable agreement with each other.