Institute of Space Technology
  • Islamabad, Punjab, Pakistan
Recent publications
The residential sector of Pakistan is a prime consumer of energy. With the fossil fuel-dependent energy generation setup and an increasing energy supply-demand gap, Pakistan is headed towards an energy fiasco. Therefore, drastic measures are required to enhance the energy efficiency of residential buildings in Pakistan. The current study is aimed to numerically investigate the energy performance enhancement of residential buildings by integrating Phase Change Materials (PCM) in the building envelopes of five major cities of Pakistan having different climates. The numerical computations are carried out in open-source building-simulation software, EnergyPlus. Initially, fifteen suitable PCMs are evaluated for a single-room base case house. CrodaTherm24 having a melting temperature of 24 • C with a thickness of 40 mm is found to be the optimum PCM choice when it is placed on the inner sides of building envelopes. It is then integrated into typical single-Storey and two-Storey multi-zone residential buildings. For a single-Storey building, the average monthly energy saving of 44.9% is achieved in Islamabad, 35% in Karachi, 32% in Lahore, 35% in Peshawar, and 49.6% in Quetta while for two-Storey buildings the average monthly energy saving of 12%, 21.4%, 15.5%, 12.9%, and 13.5% are achieved, respectively. The economic feasibility of implementing PCM in building envelopes is evaluated through static and dynamic payback period calculations. The usage of PCM for energy efficiency enhancements of residential buildings is found to be economically feasible for Lahore, Karachi, and Peshawar whereas, it is unsuitable for Islamabad and Quetta.
Surveillance Systems Application based on deep learning algorithms is speedily growing in a broad range of fields such as Facial Recognition, Real Time Attendance Systems etc. Identifying several appearances in a real time environment is very crucial due to its difficult and heterogenous environmental conditions and blocking effects. We used state-of-the-art YOLOv5 model for investigating the efficiency of surveillance system with very limited experimental analysis. We used Face Detection Dataset & Benchmark (FDDB) and Celebrity Face Recognition (CFR) Dataset for training from scratch and for testing over YOLOv5 and private dataset taken from run-time video stream. Experimentations showing that we got 93% accuracy on FDDB on the other hand 99% accuracy on the tailored dataset. Comparison has been made for the analysis showing that our algorithm has produced better outcomes with the predecessor editions of YOLOv5 like YOLOv4 and YOLOv3 respectively. The aforementioned models are also validated over the run-time streaming, and it has the ability to recognize many faces with maximal precision.
Smart devices in various application areas are becoming increasingly prevalent for efficient handling of multiple critical activities. One such area of interest is high-security militarized environments. Due to military zones’ harsh and unpredictable nature, monitoring devices deployed in such environments must operate without power interruption for extended time periods. Therefore, it is essential to choose an appropriate application design for operating these “things” in the internet of things (IoT) environment such that energy can be conserved throughout the operating span of an application. This paper presents two application modules and analyzes their performance in terms of energy conservation considering a military-based IoT-Fog architecture. The two modules are: A sequential application module, and a master-worker application module. Experimental results show that the master-worker module incurs lower energy consumption and communication overhead than the sequential application module. Significantly, the master-worker module exhibits a lower delay in tuple execution by almost four milliseconds while also accounting for lower simulation time and higher network utilization. The module achieves significant savings in energy consumption, making it more effective in handling smart devices.
The limited forest resources with a higher deforestation rate per annum, Pakistan ranks the second highest in Asia. FAO reported that the annual forest cover change rate during 1990–2000 was −1.8% and increased to −2.2 % between 2000–2010. Most of Pakistan's total forest resources, dominantly natural forest, are situated in the Northern regions. Stepping into the corridor of the 21st century, the Spatio-temporal analysis has been evolved using Satellite Remote Sensing data aided with Geographic Information System) GIS) platforms. The study is carried out over the mountainous vegetation land of Malam Jabba, district Swat, Khyber Pakhtunkhwa, Pakistan. Due to varying topography and the region being part of the agro-forestry zone, drastic changes were observed in vegetation and built-up areas. The vegetation cover has been identified and classified based on elevation throughout the area. This study has provided essential insights into vegetation cover change over a period of four decades. Vegetation cover is classified into high to very high, medium, and low to very low. The Landsat and the SRTM DEM satellite imageries were exported to the ERDAS software for pre-and post-processing, and for further analysis ArcGIS 10.5 was used, where the vegetation density change for each period was computed from the pixels by using vegetation indices like VCI, NDVI, and SAVI. The results show a significant decline from 1980 to 2010 in vegetation density in the Northwestern direction; however, an increasing trend can be seen in 2020 due to awareness and the Government’s Billion Tree Tsunami initiative. Such studies can significantly benefit researchers and decision-makers interested in satellite remote sensing for forest and other vegetation cover monitoring and management at a regional scale.
The integration of blockchain and IoT enables promising solutions in decentralized environments in contrast with centralized systems. The blockchain brings forth features such as fault tolerance, security, and transparency of the data in IoT devices. As there is requirement of consensus among the network nodes to agree on a single-state-of-ledger, nonetheless, the extensive computational requirement for the consensus protocol becomes a limitation in resource-constrained IoT devices with limited battery, computation, and communication capabilities. This study proposes an empirical approach on the adoption of blockchain in a supply chain environment. Furthermore, a modified version of the Raft consensus protocol is proposed for use in supply-chain environment on the permissioned blockchain Hyperledger. In Raft consensus protocol, each transaction is directed to the leader node that transmits it to the follower nodes, making the leader node the bottleneck thus inhibiting the scalability and throughput of the system. This also results in high latency for the network. The modified RAFT consensus protocol (mRAFT) is based on the idea of utilizing the idle follower nodes in disseminating the vote requests and log replication messages. A detailed empirical evaluation of the solution built on Hyperledger Caliper is performed to demonstrate the applicability of the system. The improved workload division on the peers boosts the throughput and latency of the system in ordering service that enhances the overall efficiency of the system.
In recent years, natural polymers have replaced synthetic polymers for antibacterial orthopedic applications owing to their excellent biocompatibility and biodegradability. Zein is a biopolymer found in corn. The lacking mechanical stability of zein is overcome by incorporating bioceramics, e.g., mesoporous bioactive glass nanoparticles (MBGNs). In the present study, pure zein and zein/Zn–Mn MBGN composite coatings were deposited via electrophoretic deposition (EPD) on 316L stainless steel (SS). Zn and Mn were co-doped in MBGNs in order to make use of their antibacterial and osteogenic potential, respectively. A Taguchi design of experiment (DoE) study was established to evaluate the effect of various working parameters on the morphology of the coatings. It was observed that coatings deposited at 20 V for 5 min with 4 g/L concentration (conc.) of Zn–Mn MBGNs showed the highest deposition yield. Uniform coatings with highly dispersed MBGNs were obtained adopting these optimized parameters. Scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR) were employed to investigate the morphology and elemental composition of zein/Zn–Mn MBGN composite coatings. Surface properties, i.e., coating roughness and wettability analysis, concluded that composite coatings were appropriate for cell attachment and proliferation. For adhesion strength, various techniques, including a tape test, bend test, pencil hardness test, and tensile test, were performed. Wear and corrosion analysis highlighted the mechanical and chemical stability of the coatings. The colony forming unit (CFU) test showed that the zein/Zn–Mn MBGN composite coating was highly effective against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) due to the presence of Zn. The formation of a hydroxyapatite (HA)-like structure upon immersion in the simulated body fluid (SBF) validated the in vitro bioactivity of the coating. Moreover, a WST-8 assay depicted that the MG-63 cells proliferate on the composite coating. It was concluded that the zein/Zn–Mn MBGN coating synthesized in this work can be used for bioactive and antibacterial orthopedic applications.
The fabrication of complete quantum dot based hole and electron transport layers for perovskite solar cells is carried out with different compositions of hybrid electron transport layers including carbon and inorganic based quantum dots, in an ambient environment. The experimental efficiency of cells is plotted against the percentage composition of quantum dots in electron transport layer, and unknown efficiencies of other compositions of electron transport layer are estimated by extrapolating the graph, with a minimal set-up of only three devices. This makes it a smart minimal set-up design that extrudes maximum information in a minimum time period for a range of perovskite solar cells. The efficiency of solar cells is associated with the LUMO levels of electron transport layers including pure and hybrid materials, where the LUMO is calculated by different methods including density-functional theory calculations. This smart formulation will allow us to use minimal setups in the future to characterize multiple perovskite solar cells simultaneously.
For the first time, the present review critically evaluates biodegradable polymer matrix composites containing graphene-related materials (GRMs) for antibacterial applications while discussing their development, processing routes, mechanical properties, and antibacterial activity. Due to its suitable biological properties and processability, chitosan has been the most widely used biodegradable polymer for the fabrication of GRM-containing composites with antibacterial properties. The majority of biodegradable polymers (including cellulose-, gelatine-, PVA-, PCL-, and PHA-based polymers) exhibit little to no antibacterial effect alone; however, they show significant antibacterial activity (>70%) when combined with GRMs. In vitro and in vivo studies indicate that GRMs functionalization with biodegradable polymers also reduces potential GRM cytotoxicity. Overall, GRMs in biodegradable polymer matrices provide attractive antibacterial activity against a broad spectrum of bacteria (>30 different bacteria) along with improved mechanical properties over pristine polymers, where the type and the degree of improvement provided by GRMs depend on the specific matrix. For example, the addition of GRMs into chitosan, PVA, and PCL matrices increases their tensile strength by 80%, 180%, and 40%, respectively. Challenges remain in understanding the effects of processing routes and post-processing methods on the antibacterial activity and biocompatibility of biodegradable polymer/GRM composites. Given their promising properties and functionality, research on these composites is expected to further increase along with the implementation of new composite systems. These would include a wide range of applications, e.g., wound dressings, tissue engineering, drug delivery, biosensing, and photo-thermal therapy, as well as non-medical use, e.g., antibacterial food packaging, water treatment, and antibacterial fabrics. Statement of significance : Graphene-related materials (GRMs) in polymer matrices can provide excellent antibacterial activity against a broad spectrum of bacteria together with improved mechanical properties (e.g., tensile strength and elastic modulus) over pristine polymers; thus, research efforts and applications of biodegradable polymer matrix composites containing GRMs have increased notably in the last ten years. For the first time, the present review critically evaluates biodegradable polymer matrix composites containing GRMs for antibacterial applications while discussing their development, processing routes, mechanical properties, and antibacterial activity. Future research directions for each composite system are proposed to shed light on overcoming the existing challenges in composite performance (e.g., mechanical properties, toxicity) reported in the literature.
Wireless body area networks (WBANs) are becoming a popular and convenient mechanism for IoT-based health monitoring applications. Maintaining the energy efficiency of the nodes in WBANs without degrading network performance is one of the crucial factors for the success of this paradigm. Obtaining routes for data packets should be a dynamic decision depending on network conditions. Consequently, in this paper, a novel cost-based routing protocol ZITA has been proposed that addresses primary issues of WBAN routing, such as timeliness, link quality, temperature control, and energy efficiency while finding the next hop for data packets. Zipf’s law is applied for relay selection to ensure the distribution of forwarding load among the potential relays. ZITA controls the transmission power level adaptively in order to cope with the time-varying channel conditions following multi-hop architecture. The protocol is simulated and the results show that the protocol gives better performance in terms of data received by the sink, heat dissipation of the wearable as well as implantable sensor nodes, and load sharing among relay nodes.
This review focuses on the therapeutic effects of ions when released in physiological environments. Recent studies have shown that metallic ions like Ag+, Sr2+, Mg2+, Mn2+, Cu2+, Ca2+, P+5, etc., have shown promising results in drug delivery systems and regenerative medicine. These metallic ions can be loaded in nanoparticles, mesoporous bioactive glass nanoparticles (MBGNs), hydroxyapatite (HA), calcium phosphates, polymeric coatings, and salt solutions. The metallic ions can exhibit different functions in the physiological environment such as antibacterial, antiviral, anticancer, bioactive, biocompatible, and angiogenic effects. Furthermore, the metals/metalloid ions can be loaded into scaffolds to improve osteoblast proliferation, differentiation, bone development, fibroblast growth, and improved wound healing efficacy. Moreover, different ions possess different therapeutic limits. Therefore, further mechanisms need to be developed for the highly controlled and sustained release of these ions. This review paper summarizes the recent progress in the use of metallic/metalloid ions in regenerative medicine and encourages further study of ions as a solution to cure diseases.
Data capturing multiple axes of tree size and shape, such as a tree's stem diameter, height and crown size, underpin a wide range of ecological research - from developing and testing theory on forest structure and dynamics, to estimating forest carbon stocks and their uncertainties, and integrating remote sensing imagery into forest monitoring programs. However, these data can be surprisingly hard to come by, particularly for certain regions of the world and for specific taxonomic groups, posing a real barrier to progress in these fields. To overcome this challenge, we developed the Tallo database, a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. These data were collected at 61,856 globally distributed sites, spanning all major forested and non-forested biomes. The majority of trees in the database are identified to species (88%), and collectively Tallo includes data for 5,163 species distributed across 1,453 genera and 187 plant families. The database is publicly archived under a CC-BY 4.0 licence and can be access from: https://doi.org/10.5281/zenodo.6637599. To demonstrate its value, here we present three case studies that highlight how the Tallo database can be used to address a range of theoretical and applied questions in ecology - from testing the predictions of metabolic scaling theory, to exploring the limits of tree allometric plasticity along environmental gradients and modelling global variation in maximum attainable tree height. In doing so, we provide a key resource for field ecologists, remote sensing researchers and the modelling community working together to better understand the role that trees play in regulating the terrestrial carbon cycle.
Metal matrix composites (MMCs) have wide applications due to being lightweight, their high strength, and immense resistance to wear. To explore new generation materials like aluminum-based metal matrix composites (AMCs) for wide engineering applications, the present work aimed at investigating the effect of changes in composition, sintering time, and temperature on the hardness and surface roughness of AMCs containing SiC and ZrSiO4 in wt % of 5, 20, 30, and 40 binary and hybrid sample pallets. The samples have been prepared by powder metallurgy (PM) method under 1000 psi pressure. After compaction, the above pallets sintered at different temperatures ranging from 500 °C to 1100 °C with an increment of 200 °C and 15 min intervals for four levels of temperature and time, respectively. Afterwards, sensitivity analysis has been done by investigating the effect of chemical composition, sintering time, and sintering temperature of the binary and hybrid composites on hardness and surface roughness. Morphological studies on the composites were carried out using field emission scanning electron microscope (FESEM) with energy dispersive spectroscopy (EDS). It has been observed that hardness is increased by increasing the sintering temperature in the case of SiC, whereas surface roughness did not change much by changing the composition. Additionally, a rise in temperature lead to liquid-state sintering. SEM images obtained during the elemental analysis showed that porosity is generated within the samples after sintering due to the higher melting point of reinforcements compared to a base metal, i.e., aluminum. Mathematical equations have also been developed via regression analysis using Minitab and excel for the confirmation and validation of experimental data. Analysis of Variance (ANOVA) has also been done, and its tables are shown and discussed in the paper. Hence, the most optimized findings relating the changes in the composition of reinforcements, sintering temperature, and sintering time (input variables) with porosity, hardness, and surface roughness have been presented in the current study.
T-spherical fuzzy sets, the direct extension of fuzzy sets, intuitionistic fuzzy sets and picture fuzzy sets are examined in this composition, and a mathematical examination among them is set up. A T-spherical fuzzy set can demonstrate phenomenon like choice utilizing four trademark capacities indicating the level of choice of inclusion, restraint, resistance, and exclusion, another example of such situation is that human opinion cannot be restricted to yes or no but it can be yes, abstain, no and refusal. T-spherical fuzzy set can deal the said situation with a boundless space. With the assistance of some mathematical outcomes, it is talked about that current similarity measures have a few drawbacks and could not be implemented where the data is in T-spherical fuzzy mode. Thus, some new similarity measures in T-spherical fuzzy environment are proposed, with the assistance of certain outcomes, it is demonstrated that the suggested similarity measures are generalization of current ones. Further the proposed similarity measures are applied in pattern recognition with numerical supportive examples. The maximum spanning tree clustering algorithm has been extended into T-spherical fuzzy context and supports our theory with numerical examples. A parallel investigation of fresh and existing similarity measures have been made and some of the benefits of designated work have been discussed.
Cloud computing is a rapidly growing paradigm which has evolved from having a monolithic to microservices architecture. The importance of cloud data centers has expanded dramatically in the previous decade, and they are now regarded as the backbone of the modern economy. Cloud-based microservices architecture is incorporated by firms such as Netflix, Twitter, eBay, Amazon, Hailo, Groupon, and Zalando. Such cloud computing arrangements deal with the parallel deployment of data-intensive workloads in real time. Moreover, commonly utilized cloud services such as the web and email require continuous operation without interruption. For that purpose, cloud service providers must optimize resource management, efficient energy usage, and carbon footprint reduction. This study presents a conceptual framework to manage the high amount of microservice execution while reducing response time, energy consumption, and execution costs. The proposed framework suggests four key agent services: (1) intelligent partitioning: responsible for microservice classification; (2) dynamic allocation: used for pre-execution distribution of microservices among containers and then makes decisions for dynamic allocation of microservices at runtime; (3) resource optimization: in charge of shifting workloads and ensuring optimal resource use; (4) mutation actions: these are based on procedures that will mutate the microservices based on cloud data center workloads. The suggested framework was partially evaluated using a custom-built simulation environment, which demonstrated its efficiency and potential for implementation in a cloud computing context. The findings show that the engrossment of suggested services can lead to a reduced number of network calls, lower energy consumption, and relatively reduced carbon dioxide emissions.
With the rapid population growth, the annual plastic waste generation is increasing. There is a dire need for reusing plastic waste. If plastic waste is not recycled it ends up in landfills; ocean garbage patches or is incinerated; which causes different environmental problems, and if pollution from incineration plants is controlled then the plant becomes so expensive that not all countries can afford it. The addition of plastic waste to the flexible pavement has become an attractive option because this improves flexible pavement performance and eliminates the environmental problem. Huge work is done on waste addition in the bituminous mix but this review paper focuses on research done on utilizing plastic wastes as a modifier in a bituminous mix of flexible pavement.
We present results of first-principles calculations for double perovskite Sr2CrSbO6 in its high temperature phase (cubic). Through electro-magnetic and elastic investigation our study reveals that this compound is semi-conductor, ferromagnetic and brittle. In addition, the thermoelectric properties have been determined for this perovskite in its cubic phase. The mechanical and thermal parameters such as Debye temperature (θD) and Grüneisen parameter (γ) were also computed for calculation of the lattice thermal conductivity (κL). The figure of merit (ZT), Power factor (PF), Seebeck coefficient (S), electrical conductivity and the lattice thermal conductivity were calculated in the temperature range from 50 K to 1000 K. A very high Seebeck coefficient, high electrical conductivity (in good agreement with the nature of a semiconductor) and a figure of merit close to unity were obtained for this perovskite suggesting a great potential for thermoelectrical applications. The results are discussed in view of future experiments.
To meet the demands for more effective and ecofriendly food packaging strategies, the potential of nisin-loaded rhamnolipid functionalized nanofillers (rhamnosomes) has been explored after embedding in hydroxypropyl-methylcellulose (HPMC) and κ-carrageenan (κ-CR)-based packaging films. It was observed that intrinsically active rhamnosomes based nanofillers greatly improved the mechanical and optical properties of nano-active packaging (NAP) films. Incorporation of rhamnosomes resulted in higher tensile strength (5.16 ± 0.06 MPa), Young's modulus (2777 ± 0.77 MPa), and elongation (2.58 ± 0.03%) for NAP than active packaging containing free nisin (2.96 ± 0.03 MPa, 1107 ± 0.67 MPa, 1.48 ± 0.06%, respectively). NAP demonstrated a homogenous distribution of nanofillers in the biopolymer matrix as elucidated by scanning electron microscopy (SEM). Thermogravimetric analysis (TGA) confirmed that NAP prepared with nisin-loaded rhamnosomes was thermally stable even above 200 °C. Differential scanning calorimetry (DSC) analyses revealed that addition of nisin in nanofillers resulted in a slight increase in Tg (108.40 °C), indicating thermal stability of NAP. Fourier transform infrared spectroscopy (FTIR) revealed slight shift in all characteristic bands of nano-active packaging, which indicated the embedding of rhamnosomes inside the polymer network without any chemical interaction. Finally, when tested on chicken breast filets and cheese slices under refrigerated storage conditions, NAP demonstrated broad-spectrum antimicrobial activity (up to 4.5 log unit reduction) and inhibited the growth of Listeria monocytogenes, Staphylococcus aureus, Pseudomonas aeruginosa, and Escherichia coli. These results suggest that HPMC and κ-CR-based NAP containing functionalized nanofillers can serve as an innovative packaging material for the food industry to improve the safety, quality, and shelf-life of dairy and meat products. Supplementary information: The online version contains supplementary material available at 10.1007/s11947-022-02815-2.
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342 members
Umar Bhatti
  • Department of Aeronautics and Astronautics
Aamir Habib
  • Department of Electrical Engineering
Saad Nauman
  • MS and E
Abdul Faheem Khan
  • Materials science & Engineering
B.M. Ghauri
  • Department of Remote Sensing and Geographic Information Science
Information
Address
1, Islamabad Highway, 44000, Islamabad, Punjab, Pakistan
Head of institution
Imran Rahman
Website
www.ist.edu.pk
Phone
+92-51-9075100
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+92-51-9273310