Showing papers by "Ghulam Ishaq Khan Institute of Engineering Sciences and Technology published in 2020"

Gender‐diverse boards and audit fees: What difference does gender quota legislation make?

Abstract: We investigate the effect of board (audit committee) gender diversity on audit fees in the French context. We also examine whether the relationship between the proportion of female directors and audit fees is moderated by the enactment of the gender quota law in 2011. We use the system GMM estimation approach on a matched sample of French firms listed in the SBF 120 index between 2002 and 2017. Consistent with the supply‐side perspective, we contend that female independent directors and female audit committee members, by improving board monitoring effectiveness, affect the auditor's assessment of audit risk, resulting in lower audit fees. Our findings also document that, by breaking the glass ceiling, the effectiveness of the gender quota law lies not in increasing the proportion of female insider directors, but in boosting the appointment of female independent directors and female audit committee members. Using the difference‐in‐difference approach, our results reveal that female independent directors and female audit committee members are more willing to assert their monitoring skills after the quota law, leading to lower audit fees. Moving beyond tokenism, we show that, after the quota law, the negative impact on non‐audit fees is strengthened only for female independent directors.

Elliptical metallic rings-shaped fractal metamaterial absorber in the visible regime

Abstract: Achieving the broadband response of metamaterial absorbers has been quite challenging due to the inherent bandwidth limitations. Herein, the investigation was made of a unique kind of visible light metamaterial absorber comprising elliptical rings-shaped fractal metasurface using tungsten metal. It was found that the proposed absorber exhibits average absorption of over 90% in the visible wavelength span of 400–750 nm. The features of perfect absorption could be observed because of the localized surface plasmon resonance that causes impedance matching. Moreover, in the context of optoelectronic applications, the absorber yields absorbance up to ~ 70% even with the incidence obliquity in the range of 0°–60° for transverse electric polarization. The theory of multiple reflections was employed to further verify the performance of the absorber. The obtained theoretical results were found to be in close agreement with the simulation results. In order to optimize the results, the performance was analyzed in terms of the figure of merit and operating bandwidth. Significant amount of absorption in the entire visible span, wide-angle stability, and utilization of low-cost metal make the proposed absorber suitable in varieties of photonics applications, in particular photovoltaics, thermal emitters and sensors.

Capacitive and diffusion-controlled mechanism of strontium oxide based symmetric and asymmetric devices

Abstract: A systematic approach has been employed to statistically analyze the Faradaic and non-Faradaic mechanism on electrodes. Two strategies have been adopted for device design, i.e. symmetric and asymmetric, by using the metal oxide synthesized via sonochemical method and activated carbon electrode. Structural and electrochemical characterization have been performed to investigate the morphological and electrochemical properties of electrode material. Both devices are electrochemically examined by using cyclic voltammetry (CV) and Galvanostatic charge discharge (GCD) measurements to evaluate the electrochemical performance. CV curves are further explored to study the capacitive and diffusive contribution in both devices. The diffusive-controlled contribution at low scan rate in asymmetric device is about 65% which is suitable for supercapattery applications while the symmetric device shows 91% diffusive contribution presenting better performance for battery applications. The strategy unveils the high capacitive and diffusive contribution in asymmetric and symmetric devices, respectively. Results reveal that same material can be exploited for supercapattery and battery applications by implementing different device architectures.

Selenide-chitosan as High-performance Nanophotocatalyst for Accelerated Degradation of Pollutants.

Abstract: Water pollution is one of the major global challenges today Water bodies are contaminated by the heavy release of waste effluents of textile industries, which includes intensively colored dye pollutants Herein, a ternary nanocomposite of bismuth copper selenide with small particle size and ternary metal selenide (TMS)-chitosan microspheres (TMS-CM) of the spherical porous surface were successfully synthesized SEM, XRD, EDX, FTIR, and UV/Vis spectrophotometry analysis revealed the structural and morphological characteristics of the newly synthesized nanocomposites SEM imaging showed the average diameter of TMS nanoparticle to be 33 nm The crystal size was calculated as 633 nm and crystalline structure as orthorhombic using XRD findings EDX confirmed the presence of Bi, Cu, and Se in the ternary nanocomposite The bandgap of 18 eV was calculated from Tauc's plot for the TMS nanocomposite SEM confirmed the successful synthesis of spherical TMS-CM microspheres of porous surface morphology with an average size of 8856 μm The presence of chitosan microspheres in the synthesis of TMS nanocomposite was identified by FTIR spectral analysis Furthermore, highly efficient photocatalytic degradation (up to 954%) of ARS was achieved within 180 min at pH 40 using 05 g of TMS-CM in sunlight The first-order kinetic model fitted well to the photocatalytic decontamination of ARS using TMS-CM with a rate constant of 61x10-2 min-1 The TMS-CM gave attractive results and high efficiency in photocatalytic degradation of ARS dye after reusing and regeneration of up to seven successive cycles The newly synthesized nanophotocatalyst could be efficiently used for the decontamination of dye polluted water from textile industries

Design of a wideband terahertz metamaterial absorber based on Pythagorean-tree fractal geometry

Abstract: Broadband absorption in the terahertz regime is a challenge and onerous to realize with a single layer metasurface. Self-similarity in fractal structures are exploiting metamaterial characteristics that offer a promising platform to design wideband microwave and optical devices. This paper presents a metamaterial absorber that consists of fractal geometry of Pythagorean-tree. The proposed metamaterial absorber demonstrates the wideband absorptivity in a terahertz spectrum ranging from 7.5–10 THz. Both transverse electric (TE)–and transverse magnetic(TM)–mode are taken up under different obliquity incidence angles to deeply study the angular dependence on absorption features of the Pythagorean-tree fractal meta-absorber (PTFMA). A numerical approach of interference theory is employed to verify the simulation results of the designed PTFMA. Further, the performance of the PTFMA was analyzed in terms of the figure of merit (FOM) and operational bandwidth (OBW) for different geometric parameters. Furthermore, surface electric field patterns and current distributions were studied to understand the absorption mechanism of the suggested PTFMA. The designed absorber would be a promising contender for bolometers, THz detection, and communication.

Electrochemical removal of methylene bleu dye in aqueous solution using Ti/RuO2–IrO2 and SnO2 electrodes

Abstract: The comparison of the degradation efficiency of two electrodes (Ti/RuO2–IrO2 and SnO2) has been evaluated using Methylene Bleu (MB) dye. The effect of several parameters on the degradation process ...

Biocompatibility and corrosion resistance of metallic biomaterials

Abstract: Abstract Biomaterials play a significant role in revolutionizing human life in terms of implants and medical devices. These materials essentially need to be highly biocompatible and inert to the human physiological conditions. This paper provides an in-depth, critical and analytical review on the previous research work and studies conducted in the field of metals and alloys used as implant materials including stainless steel, titanium and its alloys, cobalt chromium and others. Since the manufacturing of medical implants relies on selected grades of biomaterials, metals play a significant role in biomaterials market. This paper focuses on highlighting some basic principles of manufacturing implant materials underlying composition, structure and properties of these materials. Finally, attention is also given to the role of these implant materials on the betterment of human life in terms of their failures by critically analysing these materials.

A novel binary chaotic genetic algorithm for feature selection and its utility in affective computing and healthcare

Abstract: Genetic algorithm (GA) is a nature-inspired algorithm to produce best possible solution by selecting the fittest individual from a pool of possible solutions. Like most of the optimization techniques, the GA can also stuck in the local optima, producing a suboptimal solution. This work presents a novel metaheuristic optimizer named as the binary chaotic genetic algorithm (BCGA) to improve the GA performance. The chaotic maps are applied to the initial population, and the reproduction operations follow. To demonstrate its utility, the proposed BCGA is applied to a feature selection task from an affective database, namely AMIGOS (A Dataset for Affect, Personality and Mood Research on Individuals and Groups) and two healthcare datasets having large feature space. Performance of the BCGA is compared with the traditional GA and two state-of-the-art feature selection methods. The comparison is made based on classification accuracy and the number of selected features. Experimental results suggest promising capability of BCGA to find the optimal subset of features that achieves better fitness values. The obtained results also suggest that the chaotic maps, especially sinusoidal chaotic map, perform better as compared to other maps in enhancing the performance of raw GA. The proposed approach obtains, on average, a fitness value twice as better than the one achieved through the raw GA in the identification of the seven classes of emotions.

Ultrathin broadband metasurface-based absorber comprised of tungsten nanowires

Abstract: An ultrathin broadband metasurface-based absorber, comprised of tungsten nanowires, was studied under the normal and oblique incidence of transverse electric (TE) and transverse magnetic (TM) waves. The effect of geometrical parameters on the absorption spectra was investigated through the surface electric field and power patterns at certain operating wavelengths. The structure was found to exhibit nearly perfect absorption in the ultraviolet (UV) span of ~350–400 nm and ~85% absorptivity in the visible spectral range of ~400–750 nm. The attempt was also made to validate the simulation results with that obtained upon homogenization of the metasurface using the effective medium theory. Further, to optimize the results, the performance of the proposed absorber was analyzed in terms of the figure of merit and operating bandwidth, the highest values of which were obtained to be 95% and 450 nm, respectively. With the viewpoint of achieving relatively wideband absorption, it is expected that the proposed absorber can be effectively used in biosensing, solar cell and thermal emitter applications.

On the specially designed fractal metasurface-based dual-polarization converter in the THz regime

Abstract: A specially designed fractal metasurface-based structure was investigated as a dual-polarization converter operating in the terahertz (THz) band. The proposed converter has the ability to perform both the linear-to-cross (LX) and linear-to-circular (LC) polarization conversions. In the former kind of operation, it exhibits three unity polarization conversion ratio (PCR) peaks at 1.10 THz, 2.13 THz and 3.46 THz frequencies, whereas in the latter situation, the conversion was achieved over three operating bands, namely 1.2–1.83 THz, 2.52–3.10 THz and 3.78–3.90 THz. The effect of oblique incidence on the performance of metasurface (used in designing the converter) was also studied, and fairly stable operation could be determined. The obtained results indicate the proposed converter to have possible potentials in imaging, antenna engineering and certain other photonic devices used in the fields of medical diagnostics, sensing, and other related measurements.

Integration of green supply chain management practices in construction supply chain of CPEC

Abstract: China Pakistan Economic Corridor (CPEC) projects are widely spread throughout Pakistan with the potential to have a massive impact on Pakistan’s economic future. CPEC projects have, therefore, made it imperative that green practices are adapted to provide sustainability to the CPEC projects. The adoption of green supply chain management (GSCM) framework will significantly increase the value attained from CPEC projects through the increased benefits to the socio-cultural and economic conditions of Pakistan without causing harm to the environment. The purpose of this paper is to identify and rank the GSCM practices for implementation in the construction industry of Pakistan according to expert opinion.,This study targets the experts who are employed as supply chain managers in the different construction industries of Pakistan. The opinions of these experts have been extracted through an online questionnaire that was based on six alternatives along with four criteria. The tool of multi-criteria decision making (MCDM) that is a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) has been used to analyze the results.,Six alternatives that have been used for this study are green design, green procurement, green production, green warehousing, green transportation and green recycling. The top-ranked alternative as a practice for GSCM is green warehousing followed by green production. The lowest ranked alternative in this study is green recycling. The alternatives have been ranked on the basis of “cc” values derived through TOPSIS.,As the advancement in the construction industry will definitely going to impact the environmental sustainability of the country, the results derived through this research will assist the managers of the construction industry of Pakistan to adopt best practices among green supply chain in order to lower their impact.,Framework using TOPSIS in order to find the best GSCM practice in Pakistan has not been reported before this study.

Sustainable hybrid electric vehicle selection in the context of a developing country

Abstract: The ever increasing global warming is affecting both the environment and quality of life. The dependency on the usage of fossil fuels for transportation and power generation sector is harming the environment in terms of greenhouse gas (GHG) emissions. To limit the use of fossil fuel, the world has to move towards a renewable, clean, and economical form of energy. In the transportation sector, the paradigm shift towards electric mobility is a step towards the same goal. For a developing country like Pakistan, due to the lacking charging infrastructure, load shedding of electricity, and high cost of non-renewable electrical energy, a country like Pakistan cannot go dependent on fully electric vehicles (EVs). The country has to shift from normal internal combustion engine vehicles (ICEVs) to hybrid electric vehicles (HEVs). This paper aims to select the most sustainable HEV in the context of a developing country, Pakistan. Using the multi-criteria decision making (MCDM) technique, i.e., fuzzy Technique for Order Performance by Similarity to Ideal Solution (TOPSIS), based on ten criteria and seven alternatives, it has been found that Toyota Aqua outperforms among all the other alternatives in terms of economic, social, and environmental perspective. Furthermore, to move towards hybrid technology, the government has to give relaxation in terms of customs duty and should encourage auto manufacturers to set up local industries of such vehicles in the country.

S6AE: Securing 6LoWPAN Using Authenticated Encryption Scheme.

Abstract: IPv6 over Low Power Wireless Personal Area Networks (6LoWPAN) has an ample share in the Internet of Things. Sensor nodes in 6LoWPAN collect vital information from the environment and transmit to a central server through the public Internet. Therefore, it is inevitable to secure communications and allow legitimate sensor nodes to access network resources. This paper presents a lightweight Authentication and Key Exchange (AKE) scheme for 6LoWPAN using an authenticated encryption algorithm and hash function. Upon successful authentication, sensor nodes and the central server can establish the secret key for secure communications. The proposed scheme ensures header verification during the AKE process without using IP security protocol and, thus, has low communication and computational overheads. The logical correctness of the proposed scheme is validated through Burrows–Abadi–Needham logic. Furthermore, automatic security analyses by using AVISPA illustrate that the proposed scheme is resistant to various malicious attacks in 6LoWPANs.

Lightweight and Privacy-Preserving Template Generation for Palm-Vein-Based Human Recognition

Abstract: The use of human biometrics is becoming widespread and its major application is human recognition for controlling unauthorized access to both digital services and physical localities. However, the practical deployment of human biometrics for recognition poses a number of challenges, such as template storage capacity, computational requirements, and privacy of biometric information. These challenges are important considerations, in addition to performance accuracy, especially for authentication systems with limited resources. In this paper, we propose a wave atom transform (WAT)-based palm-vein recognition scheme. The scheme computes, maintains, and matches palm-vein templates with less computational complexity and less storage requirements under a secure and privacy-preserving environment. First, we extract palm-vein traits in the WAT domain, which offers sparser expansion and better capability to extract texture features. Then, the randomization and quantization are applied to the extracted features to generate a compact, privacy-preserving palm-vein template. We analyze the proposed scheme for its performance and privacy-preservation. The proposed scheme obtains equal error rates (EERs) of 1.98%, 0%, 3.05%, and 1.49% for PolyU, PUT, VERA and our palm-vein datasets, respectively. The extensive experimental results demonstrate comparable matching accuracy of the proposed scheme with a minimum template size and computational time of 280 bytes and 0.43 s, respectively.

Gene encoder: a feature selection technique through unsupervised deep learning-based clustering for large gene expression data

Abstract: Cancer is a severe condition of uncontrolled cell division that results in a tumor formation that spreads to other tissues of the body. Therefore, the development of new medication and treatment methods for this is in demand. Classification of microarray data plays a vital role in handling such situations. The relevant gene selection is an important step for the classification of microarray data. This work presents gene encoder, an unsupervised two-stage feature selection technique for the cancer samples’ classification. The first stage aggregates three filter methods, namely principal component analysis, correlation, and spectral-based feature selection techniques. Next, the genetic algorithm is used, which evaluates the chromosome utilizing the autoencoder-based clustering. The resultant feature subset is used for the classification task. Three classifiers, namely support vector machine, k-nearest neighbors, and random forest, are used in this work to avoid the dependency on any one classifier. Six benchmark gene expression datasets are used for the performance evaluation, and a comparison is made with four state-of-the-art related algorithms. Three sets of experiments are carried out to evaluate the proposed method. These experiments are for the evaluation of the selected features based on sample-based clustering, adjusting optimal parameters, and for selecting better performing classifier. The comparison is based on accuracy, recall, false positive rate, precision, F-measure, and entropy. The obtained results suggest better performance of the current proposal.

Influence of Mo addition on the structural and electrochemical performance of Ni-rich cathode material for lithium-ion batteries.

Abstract: Molybdenum modified LiNi0.84Co0.11Mn0.05O2 cathode with different doping concentrations (0–5 wt.%) is successfully prepared and its electrochemical performances are investigated. It is demonstrated that molybdenum in LiNi0.84Co0.11Mn0.05O2 has a positive effect on structural stability and extraordinary electrochemical performances, including improved long-term cycling and high-rate capability. Among all samples, the 1 wt. % molybdenum LiNi0.84Co0.11Mn0.05O2 delivers superior initial discharge capacity of 205 mAh g−1 (0.1 C), cycling stability of 89.5% (0.5 C) and rate capability of 165 mAh g−1 (2 C) compared to those of others. Therefore, we can conclude that the 1 wt. % molybdenum is an effective strategy for Ni-rich LiNi0.84Co0.11Mn0.05O2 cathode used in lithium ion batteries.

A machine learning-based investigation utilizing the in-text features for the identification of dominant emotion in an email

Abstract: Identification of emotion hidden in limited text is an active research problem. This work presents a framework for the same using email text. The present work is based on machine learning methods and utilizes three classifiers and three feature selection methods. The novelty of the proposed framework is the utilization of in-text features to identify emotion contained in short texts and development of a dataset for this purpose. Six emotions, namely, neutral, happy, sad, angry, positively surprised, and negatively surprised are utilized here based on baseline theories on human emotion. Experiments are performed on three datasets including a benchmark and one local dataset. These experiments are performed by extracting 14 in-text features from the data. The proposed framework is evaluated using four standard evaluation metrics. Based on the feature selection results, experiments are performed on the datasets under consideration by vertically partitioning them into all features, top features, and bottom features. Qualitative and quantitative comparison of the proposed work is also made with two state-of-the-art methods. The obtained results suggest better performance of the current work with an average accuracy of 83%. The proposed framework can be utilized in an assortment of domains to identify human emotion by providing limited text as an input.

Highly sensitive wide range linear integrated temperature compensated humidity sensors fabricated using Electrohydrodynamic printing and electrospray deposition

Abstract: Percentage relative humidity is dependent on environmental temperature but the fact is ignored in most of research on humidity sensors. Secondly, the physical size of sensors should be small enough to enable integration on a commercial microchip. In this work, an integrated micro temperature plus humidity sensor system is presented that compensates for the effect of surrounding temperature on the output resistance of humidity sensor. The sensors were fabricated using Electrohydrodynamic drop-on-demand (EHD-DOD) printing for the electrodes, and Electrospray deposition (ESD) for active layer fabrication of humidity sensors. Electrode line widths were 10 μm while the combined area of both sensors was ∼2 mm2. Meander type silver patterns were used as resistive temperature sensors and interdigitated transducer (IDT) electrodes were used for humidity sensors. The active layer of humidity sensors was fabricated using a novel composite of Polyethylene Oxide (PEO) and 2D Molybdenum disulfide (MoS2) flakes to achieve a highly sensitive (85 kΩ/%RH) and almost linear response for a wide detection range (0–80% RH) of relative humidity. A mathematical model relating the outputs of both sensors was developed to compensate for the effects of temperature. The system presents optimal solution for commercialization ready temperature compensated integrated micro temperature and humidity sensors fabricated through all printing techniques.

Phase engineering with all-dielectric metasurfaces for focused-optical-vortex (FOV) beams with high cross-polarization efficiency

Abstract: Metasurfaces, the two-dimensional (2D) metamaterials, facilitate the implementation of abrupt phase discontinuities using an array of ultrathin and subwavelength features. These metasurfaces are considered as one of the propitious candidates for realization and development of miniaturized, surface-confined, and flat optical devices. This is because of their unprecedented capabilities to engineer the wavefronts of electromagnetic waves in reflection or transmission mode. The transmission-type metasurfaces are indispensable as the majority of optical devices operate in transmission mode. Along with other innovative applications, previous research has shown that Optical-Vortex (OV) generators based on transmission-type plasmonic metasurfaces overcome the limitations imposed by conventional OV generators. However, significant ohmic losses and the strong dispersion hampered the performance and their integration with state-of-the-art technologies. Therefore, a high contrast all-dielectric metasurface provides a compact and versatile platform to realize the OV generation. The design of this type of metasurfaces relies on the concept of Pancharatnam-Berry (PB) phase aiming to achieve a complete 2π phase control of a spin-inverted transmitted wave. Here, in this paper, we present an ultrathin, highly efficient, all-dielectric metasurface comprising nano-structured silicon on a quartz substrate. With the help of a parameter-sweep optimization, a nanoscale spatial resolution is achieved with a cross-polarized transmission efficiency as high as 95.6% at an operational wavelength of 1.55 µm. Significantly high cross-polarized transmission efficiency has been achieved due to the excitation of electric quadrupole resonances with a very high magnitude. The highly efficient control over the phase has enabled a riveting optical phenomenon. Specifically, the phase profiles of two distinct optical devices, a lens and Spiral-Phase-Plate (SPP), can be merged together, thus producing a highly Focused-Optical-Vortex (FOV) with a maximum focusing efficiency of 75.3%.