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Abid Farooq,Surendar Moogi,장성호,KANNAPU HARI PRASAD REDDY,Soheil Valizadeh,Ashfaq Ahmed,Su Shiung Lam,박영권 한국공업화학회 2021 Journal of Industrial and Engineering Chemistry Vol.94 No.-
Steam-gasification of linear low-density polyethylene (LLDPE) waste to hydrogen-rich gas has beenstudied systematically over nickel (10 wt.%) loaded on a variety of supports (Al2O3, CeO2, and CeO2-ZrO2)synthesized using a novel solvent deficient method (SDM). The hydrogen selectivity order of the catalystswas reported as Ni/CeO2-ZrO2>Ni/CeO2>Ni/Al2O3. The highest catalytic H2 selectivity of the Ni/CeO2-ZrO2 catalyst was reported to be76 vol.%, and was attributed to the smaller nickel crystals that werefinely dispersed on the support, and to formation of Ce1-xZrxO2-d solid solutions. The Ce1-xZrxO2-d solidsolution in the Ni/CeO2-ZrO2 catalyst was observed to be bi-functional, thus reflecting the acceleration ofthe water gas shift and the oxidation of carbon to CO and CO2. The better resistance of the Ni/CeO2-ZrO2catalyst towards coke deposition also indicated its potential for commercial-scale applications for thesteam gasification of plastics. Therefore, this research provides an advanced route to recycle LLDPE plasticwaste into hydrogen fuel, which presents both economical and environmental benefits.
( Abid Farooq ),( Young-kwon Park ) 한국공업화학회 2021 공업화학 Vol.32 No.3
Emulsions were prepared using a mixture of bio-oil obtained from the pyrolysis of sawdust in an N<sub>2</sub> environment and Quercus mongolica in a CH<sub>4</sub> environment for both non-catalytic and catalytic cases. Both prepared emulsions were examined by measuring the physical stability and Fourier transform infrared spectroscopy. The emulsion with HLB 5.8 (Span 80 and Atlox 4916) for the ratio of bio-oil (B-oil and C-oil): surfactant: diesel = 10% : 3% : 87% showed stability for 15 days. Combining oils produced in N<sub>2</sub> and CH<sub>4</sub> environments could be a potential solution for generating high-quality emulsions with a high heating value.
Enhanced stability of bio-oil and diesel fuel emulsion using Span 80 and Tween 60 emulsifiers
Farooq, Abid,Shafaghat, Hoda,Jae, Jungho,Jung, Sang-Chul,Park, Young-Kwon Elsevier 2019 Journal of Environmental Management Vol.231 No.-
<P><B>Abstract</B></P> <P>Bio-oil (biomass pyrolysis oil) has some undesirable properties (e.g., low heating value, high corrosiveness, and high viscosity) that restrain its direct use as a transportation fuel. The emulsification of bio-oil and diesel is an effective and convenient method to use bio-oil in the present transportation fuel infrastructure. The addition of an emulsifying agent (emulsifier or surfactant) to two immiscible liquids of diesel and bio-oil is an important step in emulsification. The hydrophilic–lipophilic balance (HLB) value, according to the chemical structure and characteristics of the emulsifier, is a key parameter for selecting a surfactant. In this study, an ether treatment of raw bio-oil was carried out to separate the ether-soluble fraction of bio-oil from its heavy (dark brown and highly viscous) fraction, and the ether-extracted bio-oil (EEO) was processed further for emulsification into diesel fuel. The effects of the HLB value of the emulsifier and the contents of EEO, diesel, and emulsifier on the stability of the EEO/diesel emulsion were investigated. To optimize the HLB value of the emulsifier, different HLB values (4.3–8.8), which were prepared by mixing different amounts of Span 80 and Tween 60 as surfactants, were used for the EEO and diesel emulsification. A HLB value of 7.3 with diesel, EEO, and emulsifier contents of 90, 5, 5 wt%, and 86, 7.4, 6.6 wt% resulted in EEO/diesel emulsions (without phase separation) stable for 40 and 35 days, respectively. Measurement of the high heating value (HHV) of the emulsified fuels gave a 44.32 and 43.68 MJ/kg values for the EEO to emulsifier mass ratios of 5:5 and 7.4:6.6, respectively. The stability of emulsified EEO and diesel was verified by TGA and FT-IR methods.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Emulsification of ether-extracted bio-oil (EEO) in diesel was done at room temperature. </LI> <LI> Span 80 and Tween 60 in individual or combination form were used as emulsifiers. </LI> <LI> EEO/diesel emulsion was stable for 40 days, while no stratification was happened. </LI> <LI> Stability of EEO/diesel emulsion after 40 days was confirmed by TGA and FTIR. </LI> <LI> HHV of EEO/diesel emulsion was as high as 44 MJ/kg (near to diesel HHV of 45 MJ/kg). </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>
Challenges and Issues of Resource Allocation Techniques in Cloud Computing
( Adnan Abid ),( Muhammad Faraz Manzoor ),( Muhammad Shoaib Farooq ),( Uzma Farooq ),( Muzammil Hussain ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.7
In a cloud computing paradigm, allocation of various virtualized ICT resources is a complex problem due to the presence of heterogeneous application (MapReduce, content delivery and networks web applications) workloads having contentious allocation requirements in terms of ICT resource capacities (resource utilization, execution time, response time, etc.). This task of resource allocation becomes more challenging due to finite available resources and increasing consumer demands. Therefore, many unique models and techniques have been proposed to allocate resources efficiently. However, there is no published research available in this domain that clearly address this research problem and provides research taxonomy for classification of resource allocation techniques including strategic, target resources, optimization, scheduling and power. Hence, the main aim of this paper is to identify open challenges faced by the cloud service provider related to allocation of resource such as servers, storage and networks in cloud computing. More than 70 articles, between year 2007 and 2020, related to resource allocation in cloud computing have been shortlisted through a structured mechanism and are reviewed under clearly defined objectives. Lastly, the evolution of research in resource allocation techniques has also been discussed along with salient future directions in this area.
Sarir Uddin,Abid Zaman,Imtiaz Rasool,Sadiq Akbar,Muhammad Kamran,Nasir Mehboob,Asad Ali,Abid Ahmad,Muhammad Farooq Nasir,Zafar Iqbal 한양대학교 세라믹연구소 2020 Journal of Ceramic Processing Research Vol.21 No.6
The effects of Ba substitution on the phase analysis, microstructure and microwave dielectric properties of Ca1-xBaxTiO3ceramics were prepared through conventional solid state reaction route. The X-ray diffraction analysis of the samples showedthat the specimens Ca1-xBaxTiO3 presented single phase compound with orthorhombic structure in the range of x=0.0 to 0.7when sintered at 1300oC for 3hrs in air. From the morphological point of view, it consists of round and rod shaped grains withporous microstructure. The substitution of Ba2+ ions over Ca2+, the microwave dielectric constant (εr) diminishes from 145 to52 whereas the quality factor (Qxf) will increases from 8105 to 24305 GHz and temperature coefficient of resonant frequencydecreases from 705 to 80 ppm/oC (at 3 GHz).
초음파 파쇄기를 사용하여 디젤과 에테르 추출 바이오오일의 에멀젼화
박영권,황유진,( Abid Farooq ),정재훈 한국공업화학회 2019 한국공업화학회 연구논문 초록집 Vol.2019 No.0
열분해로 얻어진 바이오오일은 높은 점도와 산도 및 많은 양의 수분으로 인하여 바로 엔진에서 사용되어지지 않는다. 엔진에 사용되기 위해서는 에멀젼화 기술을 이용하여 디젤과 혼합해서 사용되어야 한다. 따라서 본 연구에서는 Oak 톱밥을 450°C에서 열분해하여 얻어진 바이오오일을 중유, 경유 및 에테르 추출 오일로 분리하였고 그 중에서 낮은 점도와 적은 수분량을 가진 에테르 추출 오일을 디젤과의 에멀젼화에 이용하였다. 에테르 추출 오일의 에멀젼화는 초음파 파쇄기를 사용하여 진행되었으며 초음파의 출력, HLB 값, 유화제 양, 온도 및 바이오오일과 디젤 비율과 같은 여러 조건을 가지고 실험을 진행하여 안정성을 테스트하였다. <sup>**</sup> 이 논문은 2017년도 정부(산업통상자원부)의 재원으로 한국에너지기술평가원의 지원을 받아 수행된 연구임(No. 20173010092430).
Cyber threats: taxonomy, impact, policies, and way forward
Annas W. Malik,Adnan Abid,Shoaib Farooq,Irfan Abid,Naeem A. Nawaz,Kashif Ishaq 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.7
The continuous evolution and proliferation of computer technology and our increasing dependence on computer technology have created a new class of threats: "cyber threats." These threats can be defined as activities that can undermine a society's ability to maintain internal or external order while using information technology. Cyber threats can be mainly divided into two categories, namely cyber-terrorism and cyber-warfare. A variety of malware programs are often used as a primary weapon in these cyber threats. A significant amount of research work has been published covering different aspects of cyber threats, their countermeasures, and the policy-making for cyber laws. This article aims to review the research conducted in various important aspects of cyber threats and provides synthesized information regarding the fundamentals of cyber threats; discusses the countermeasures for such threats; provides relevant details of high-profile cyber-attacks; discusses the developments in global policy-making for cyber laws, and lastly presents promising future directions in this area.
Analysis of LinkedIn Jobs for Finding High Demand Job Trends Using Text Processing Techniques
Kazi, Abdul Karim,Farooq, Muhammad Umer,Fatima, Zainab,Hina, Saman,Abid, Hasan International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.10
LinkedIn is one of the most job hunting and career-growing applications in the world. There are a lot of opportunities and jobs available on LinkedIn. According to statistics, LinkedIn has 738M+ members. 14M+ open jobs on LinkedIn and 55M+ Companies listed on this mega-connected application. A lot of vacancies are available daily. LinkedIn data has been used for the research work carried out in this paper. This in turn can significantly tackle the challenges faced by LinkedIn and other job posting applications to improve the levels of jobs available in the industry. This research introduces Text Processing in natural language processing on datasets of LinkedIn which aims to find out the jobs that appear most in a month or/and year. Therefore, the large data became renewed into the required or needful source. This study thus uses Multinomial Naïve Bayes and Linear Support Vector Machine learning algorithms for text classification and developed a trained multilingual dataset. The results indicate the most needed job vacancies in any field. This will help students, job seekers, and entrepreneurs with their career decisions