Intelligent Clustering in Vehicular ad hoc Networks

( Farhan Aadil ),( Salabat Khan ),( Khalid Bashir Bajwa ),( Muhammad Fahad Khan ),( Asad Ali ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.8

A network with high mobility nodes or vehicles is vehicular ad hoc Network (VANET). For improvement in communication efficiency of VANET, many techniques have been proposed; one of these techniques is vehicular node clustering. Cluster nodes (CNs) and Cluster Heads (CHs) are elected or selected in the process of clustering. The longer the lifetime of clusters and the lesser the number of CHs attributes to efficient networking in VANETs. In this paper, a novel Clustering algorithm is proposed based on Ant Colony Optimization (ACO) for VANET named ACONET. This algorithm forms optimized clusters to offer robust communication for VANETs. For optimized clustering, parameters of transmission range, direction, speed of the nodes and load balance factor (LBF) are considered. The ACONET is compared empirically with state of the art methods, including Multi-Objective Particle Swarm Optimization (MOPSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO) based clustering techniques. An extensive set of experiments is performed by varying the grid size of the network, the transmission range of nodes, and total number of nodes in network to evaluate the effectiveness of the algorithms in comparison. The results indicate that the ACONET has significantly outperformed the competitors.

An Efficient Optimization Technique for Node Clustering in VANETs Using Gray Wolf Optimization

( Muhammad Fahad Khan ),( Farhan Aadil ),( Muazzam Maqsood ),( Salabat Khan ),( Bilal Haider Bukhari ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.9

Many methods have been developed for the vehicles to create clusters in vehicular ad hoc networks (VANETs). Usually, nodes are vehicles in the VANETs, and they are dynamic in nature. Clusters of vehicles are made for making the communication between the network nodes. Cluster Heads (CHs) are selected in each cluster for managing the whole cluster. This CH maintains the communication in the same cluster and with outside the other cluster. The lifetime of the cluster should be longer for increasing the performance of the network. Meanwhile, lesser the CH's in the network also lead to efficient communication in the VANETs. In this paper, a novel algorithm for clustering which is based on the social behavior of Gray Wolf Optimization (GWO) for VANET named as Intelligent Clustering using Gray Wolf Optimization (ICGWO) is proposed. This clustering based algorithm provides the optimized solution for smooth and robust communication in the VANETs. The key parameters of proposed algorithm are grid size, load balance factor (LBF), the speed of the nodes, directions and transmission range. The ICGWO is compared with the well-known meta-heuristics, Multi-Objective Particle Swarm Optimization (MOPSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO) for clustering in VANETs. Experiments are performed by varying the key parameters of the ICGWO, for measuring the effectiveness of the proposed algorithm. These parameters include grid sizes, transmission ranges, and a number of nodes. The effectiveness of the proposed algorithm is evaluated in terms of optimization of number of cluster with respect to transmission range, grid size and number of nodes. ICGWO selects the 10% of the nodes as CHs where as CLPSO and MOPSO selects the 13% and 14% respectively.

Development of the High Voltage EIS Instrument for the Evaluation of the Residual Useful Life of the Batteries

Farhan Farooq(파르한),Asad khan(칸 아사드),Lee Seung June(이승준),Woojin Choi(최우진) 전력전자학회 2019 전력전자학술대회 논문집 Vol.2019 No.11

Multi-aging Effects on Vegetable Based Oils for Transformer Insulation in HV Systems

Khan Irfanullah,Abid Muhammad Ahtasham,Ullah Kaleem,Ullah Zahid,Haider Aun,Ahmad Farhan Ammar,Zia Zain,Ali Sahibzada Muhammad 대한전기학회 2021 Journal of Electrical Engineering & Technology Vol.16 No.5

Liquid insulation media is used for insulation and cooling purpose inside the transformer. Currently, transformers are using petroleum based mineral oil, which poses a serious hazardous environmental impact, since the mineral oil is non-renewable and non-biodegradable. Although, the increased cost and depleting nature of mineral oil cause an emergent need to use suitable alternatives to mineral oils that are biodegradable and environmentally friendly. In response to this resource issue, various vegetable oils, namely Sunfl ower oil, Soya bean oil, and a blend of Sunfl ower and Olive (BSO) oil are suitable alternatives for transformer insulation in high voltage systems. The afore-mentioned vegetable oils are subjected to multi-aging and comparative analysis is performed with mineral oil. Further, the dielectric and thermal properties of vegetable oils are tested before and after aging. Fourier Transform Infrared spectroscopy, water content, breakdown voltage, viscosity, fl ash point, tan delta, and pour point tests are performed on vegetable oils before and after aging. Finally, a comparative analysis of vegetable oils with mineral oil is provided to prove the effi cacy of the proposed vegetable oils. The BSO oil resulted in higher breakdown strength and good thermal behavior when subjected to the abovementioned various diagnostic measurement tests in comparison to other oils

The Effect of Demographic Characteristics on Job Performance: An Empirical Study from Pakistan

Sherbaz KHAN,Rizwana RASHEED,Aamir RASHID,Qamar ABBAS,Farhan MAHBOOB 한국유통과학회 2022 The Journal of Asian Finance, Economics and Busine Vol.9 No.2

This holistic research focused on the interactive relationship of different factors with a unique relationship with the dependent variable. The first research objective of the study was to identify the most significant factor that has an impact on Job performance while being mediated. The second objective was to see the moderating effect of gender on the relationship between transformation leadership and innovation on job performance. This research followed a purely quantitative research paradigm with a structured questionnaire to quantify the information collected from 96 respondents for the empirical analysis. For testing the research hypotheses, IBM SPSS version 24 and SmartPLS version 3.2.8 softwares were used to run the structural equation modeling to establish the causal relationship between the study variables. Most of the variables were found with a significant impact on job performance. Further, the hypotheses H3, H6, and H10 were rejected as these contributed insignificant towards the research model. This research was limited to specific educational institutions and businesses, and the timeframe was restrictive. The findings of this research can benefit policymakers and the operational side of various industries. Future research may consider the difference in gender in predicting employee engagement through leadership and innovation.

Semantic Interoperability in Heterogeneous IoT Infrastructure for Healthcare

Jabbar, Sohail,Ullah, Farhan,Khalid, Shehzad,Khan, Murad,Han, Kijun WILEY INTERSCIENCE 2017 WIRELESS COMMUNICATIONS AND MOBILE COMPUTING Vol.2017 No.-

<P>Interoperability remains a significant burden to the developers of Internet of Things’ Systems. This is due to the fact that the IoT devices are highly heterogeneous in terms of underlying communication protocols, data formats, and technologies. Secondly due to lack of worldwide acceptable standards, interoperability tools remain limited. In this paper, we proposed an IoT based Semantic Interoperability Model (IoT-SIM) to provide Semantic Interoperability among heterogeneous IoT devices in healthcare domain. Physicians communicate their patients with heterogeneous IoT devices to monitor their current health status. Information between physician and patient is semantically annotated and communicated in a meaningful way. A lightweight model for semantic annotation of data using heterogeneous devices in IoT is proposed to provide annotations for data. Resource Description Framework (RDF) is a semantic web framework that is used to relate things using triples to make it semantically meaningful. RDF annotated patients’ data has made it semantically interoperable. SPARQL query is used to extract records from RDF graph. For simulation of system, we used Tableau, Gruff-6.2.0, and Mysql tools.</P>

Grey wolf optimization based clustering algorithm for vehicular ad-hoc networks

Fahad, Muhammad,Aadil, Farhan,Rehman, Zahoor-ur-,Khan, Salabat,Shah, Peer Azmat,Muhammad, Khan,Lloret, Jaime,Wang, Haoxiang,Lee, Jong Weon,Mehmood, Irfan Elsevier 2018 Computers & electrical engineering Vol.70 No.-

<P>In vehicular ad-hoc network (VANETs), frequent topology changes occur due to fast moving nature of mobile nodes. This random topology creates instability that leads to scalability issues. To overcome this problem, clustering can be performed. Existing approaches for clustering in VANETs generate large number of cluster-heads which utilize the scarce wireless resources resulting in degraded performance. In this article, grey wolf optimization based clustering algorithm for VANETs is proposed, that replicates the social behaviour and hunting mechanism of grey wolfs for creating efficient clusters. The linearly decreasing factor of grey wolf nature enforces to converge earlier, which provides the optimized number of clusters. The proposed method is compared with well-known meta-heuristics from literature and results show that it provides optimal outcomes that lead to a robust routing protocol for clustering of VANETs, which is appropriate for highways and can accomplish quality communication, confirming reliable delivery of information to each vehicle. (C) 2018 Elsevier Ltd. All rights reserved.</P>

The effect of thermocycling on the bonding of different restorative materials to access opening through porcelain fused to metal restorations

Mohammed M. AL-Moaleem,Farhan Khalid Shah,Nausheen Saied Khan,Amit Porwal 대한치과보철학회 2011 The Journal of Advanced Prosthodontics Vol.3 No.4

PURPOSE Porcelain fused to metal (PFM) crowns provide the best treatment option for teeth that have a large or defective restoration. More than 20% of teeth with PFM crowns or bridges require non-surgical root canal treatment (NSRCT). This may be due to the effect of restorative procedures and the possible leakage of bacteria and or their by-products, which leads to the demise of the tooth pulp. Thus, this study was planned to compare the ability of the restorative materials to seal perforated PFM specimens. MATERIALS AND METHODS The study evaluates the ability of amalgam, composite or compomer restorative materials to close perforated PFM specimen's in-vitro. Ninety PFM specimens were constructed using Ni-Cr alloys and feldspathic porcelain, and then they were divided into 3 groups: amalgam (A), composite + Exite adhesive bond (B) and compomer + Syntac adhesive bond (C). All the PFM samples were embedded in an acrylic block to provide complete sealing of the hole from the bottom side. After the aging period, each group was further divided into 3 equal subgroups according to the thermocycling period (one week for 70 cycles, one month for 300 cycles and three months for 900 cycles). Each subgroup was put into containers containing dye (Pelikan INK), one maintained at 5℃ and the other at 55℃, each cycle for 30 sec time. The data obtained was analyzed by SPSS, 2006 using one way ANOVA test and student t-test and significant difference level at (P<.01). RESULTS The depth of dye penetration was measured at the interfaces of PFM and filling materials using Co-ordinate Vernier Microscope. The lowest levels of the dye penetration for the three groups, as well as subgroups were during the first week. The values of dye leakage had significantly increased by time intervals in subgroups A and C. CONCLUSION It was seen that amalgam showed higher leakage than composite while compomer showed the lowest level of leakage.

A New Hybrid Approach of Clustering Based Probabilistic Decision Tree to Forecast Wind Power on Large Scales

He Chuan,Mansoor Khan,Liu Tianqi,Ullah Farhan 대한전기학회 2021 Journal of Electrical Engineering & Technology Vol.16 No.2

The wind power forecasting plays a vital role in renewable energy production. Due to the dynamic and uncertain behavior of wind, it is really hard to catch the actual features of wind for accurate forecasting measures. The patchy and instability of wind leading to the assortment of training samples have a main infl uence on the forecasting accuracy. For this purpose, an accurate forecasting method is needed. This paper proposed a new hybrid approach of clustering based probabilistic decision tree to forecast wind power effi ciently. The collected data is screened for noisy information and selected those variables which mainly contribute in accurate predictions. Then, the wind data is normalized using mean and standard deviation to extract playing level fi elds for each feature. Based on the similarity of the data behavior, the K-means clustering algorithm is applied to classify the samples into diff erent groups which contain the historical wind data. Further, the Naïve Bayes (NB) tree is proposed to extract probabilities for each feature in the clusters. The NB tree is a hybrid model of C4.5 and NB methods that successfully applied on three big real-world wind datasets (hourly, monthly, yearly) collected from National Renewable Energy Laboratory (NREL). The forecasting accuracy exposed that the proposed method could forecast an accurate wind power from hours to years’ data. Comprehensive comparisons are made of the proposed method with the most popular state of the art techniques which show that this method provides more accurate prediction results.

An Adaptive Control of Smart Appliances with Peak Shaving Considering EV Penetration

Zunaib Maqsood Haider,Farhan H. Malik,M. Kashif Rafique,Soon-Jeong Lee(이순정),Jun-Hyeok Kim(김준혁),Khawaja Khalid Mehmood,Saad Ullah Khan,Chul-Hwan Kim(김철환) 대한전기학회 2016 전기학회논문지 Vol.65 No.5

Electric utilities may face new threats with increase in electric vehicles (EVs) in the personal automobile market. The peak demand will increase which may stress the distribution network equipment. The focus of this paper is on an adaptive control of smart household appliances by using an intelligent load management system (ILMS). The main objectives are to accomplish consumer needs and prevent overloading of power grid. The stress from the network is released by limiting the peak demand of a house when it exceeds a certain point. In the proposed strategy, for each smart appliance, the customers will set its order/rank according to their own preferences and then system will control the household loads intelligently for consumer reliability. The load order can be changed at any time by the customer. The difference between the set and actual value for each load’s specific parameter will help the utility to estimate the acceptance of this intelligent load management system by the customers.