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Implementation of Effective Law for Load Balancing
Sabah Mohammed,Edward A. Pingoy 사단법인 인문사회과학기술융합학회 2011 예술인문사회융합멀티미디어논문지 Vol.1 No.2
In this paper, we discuss about the implementation of an effective law for load balancing Content Delivery Networks (CDN). In this method we will only have the hardware implementation costs that will be giving the output of the program without software implementations costs. So for these requirements, we introduce the hardware driven flow slicing along with software driven load balancer which also reduce implementation costs when compared to the existing system method. So here, we get the effective output along with that we will be having our required method for better performance of the system.
Niki Shakeri,Jinan Fiaidhi,Sabah Mohammed,Tia-hoon Kim 보안공학연구지원센터 2014 International Journal of u- and e- Service, Scienc Vol.7 No.5
Recommender systems are now popular both commercially and in the research community, where many approaches have been suggested for providing recommendations. However, evaluating the affectivity of recommender systems is a challenging problem and most of the approaches used for evaluation are based on using some sort of a dataset. This paper describes a method for measuring the accuracy of a collaborative filtering based recommender systems called “User-Advertisement Simulation” that utilizes a simulation approach that creates artificial users and advertisements of a virtual market, then measures accuracy of the products’ ranking based on the user’s profile.
An overview of nanomaterials for industrial wastewater treatment
Sabah Mohamed Abdelbasir,Ahmed Esmail Shalan 한국화학공학회 2019 Korean Journal of Chemical Engineering Vol.36 No.8
Industrial wastewater is a universal environmental issue. Numerous organic pollutants, heavy metals, and non-disintegrating materials are present at extreme concentrations. Presently, removing these pollutants from industrial wastewater in an effective way has become a momentous issue. Efficient purification procedures are needed to remove those pollutants before disposal. In this direction, wastewater treatment has been one of the nanomaterial applications. Additionally, nanomaterials are innovationally effective for purifying water by using low-budget nanoadsorbents and nanofiltration. This review article highlights the use of nanomaterials for the removal of different polluting materials from industrial wastewater with a special focus on metal and metal oxide nanomaterials (NMs), carbonbased nanomaterials (CNMs) and nanofiber/nanocomposite membranes. The goal is to offer a recent overview and references in the area of emergent nanomaterials used for removing toxic pollutants from real industrial wastewater for researchers and industrializers.
Talib Mohammed Albayati,Ghanim Magbol Alwan,Omar Sabah Mahdy 한국화학공학회 2017 Korean Journal of Chemical Engineering Vol.34 No.1
The Magnetic nanoporous material Fe/MCM-41 was prepared, and its physical characterization studied, to determine the effect of its properties on separation efficiency of methyl orange (MO) from wastewater by adsorption process. The experimental results were analyzed for both adsorbent mesoporous material samples, MCM-41 and magnetic Fe/MCM-41, in order to select the best operating conditions for the different studied parameters, which are: constant temperature (20 oC), pH: (2) adsorbent dosage (0.03 gm), contact time (10minute) and concentrations (30mg/L). The results demonstrate that the adsorption processes can be well fitted by the Langmuir isotherm model for pure MCM-41, with a correlation coefficient of (0.999), and fitted by the Freundlich isotherm model for magnetic Fe/ MCM-41, with a correlation coefficient of (0.994). The adsorption kinetics of MO on to MCM-41 and Fe/MCM-41 are well described by a pseudo-second-order kinetic model.
Revisiting Medical Entity Recognition through the Guidelines of the Aurora Initiative
Praveen Kumar,Sabah Mohammed,Arnold Kim,Jinan Fiaidhi 보안공학연구지원센터 2016 International Journal of Bio-Science and Bio-Techn Vol.8 No.4
Clinical Document Processing is growing importance because of unstructured nature of clinical notes as well as limitation of crucial time of clinical professionals to analyses the unstructured clinical notes. Named entity recognition (NER) is a subtask of Clinical documentation processing which is important not only for text analysis but knowledge extraction. Although there are a number of clinical named entity recognition systems, they lack user flexibility and NER scalability. Clinical NER is a challenging work which required consistent research to improve clinical documentation. Accordingly, in this paper, keeping an eye on user’s flexibility, we combined the NER technique with DSL (Domain Specific Language) based user queries. This research focused to produce a prototype system which allows the user to input their queries about a clinical text in a syntax free language which will be reformulate into DSL format in background. The reformulated query then matches against the rules defined by using the DSL to get the matched rule-type. The DSL is created using Xtext framework specifically to create NER rules easily. Then NER is done as per the found NER rule-types. We used the lingpipe API to do the NER using unsupervised technique (dictionary based approach). Again considering user flexibility, research also focused on graphical visualization of the annotated recognized entities, flexibility to store the annotated document into database for later use as well as can conversion the recognized entities into CDA (Clinical Document Architecture) format for interoperability. This research is initiated and inspired by the Aurora research initiative which is an ongoing attempt lead by Dr. Arnold Kim to integrate the design of clinical documentation workflows from the physician perspective that starts with variety DSLs and ends with series of interpretations and analytics in the background
ExerAdventure: A Mobile 2D Platformer Game to Encourage Fitness
Navdeep Singh,Sabah Mohammed 한국컴퓨터게임학회 2021 한국컴퓨터게임학회논문지 Vol.34 No.2
Physical activity and exercise is an important step in the journey of a healthy lifestyle. It reduces the risk of developing many diseases like diabetes, cardiovascular diseases, and even cancer. In today’s world, we spend most of our time sitting in front of a computer or mobile phones for work and entertainment. This is one of the leading factors in a lack of physical activities and thus a decrease in the fitness level of many individuals. In this paper, we design a mobile 2D platformer game where progress inside the game world is dependent on physical activity in the real world. The game has two modes namely adventure and story mode. This design can motivate people to lead an active and healthy lifestyle. The physical activity monitoring is done solely through the pedometer of a smartphone held by the user while playing the game. The number of steps walked by the user determines the number of revives inside the adventure mode of the game. There are three levels in the story mode which are unlocked by walking more than a certain number of steps in the real world.
Developing Data Mining Techniques for Intruder Detection in Network Traffic
Amar Agrawal,Sabah Mohammed,Jinan Fiaidhi 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.8
In this paper we have proposed a hybrid intrusion detection system consisting of a misuse detection model based upon a Binary Tree of Classifiers as the first stage and an anomaly detection model based upon SVM Classifier as the second stage. The Binary Tree consists of several best known classifiers specialized in detecting specific attacks at a high level of accuracy. Combination of a Binary Tree and specialized classifiers will increase accuracy of the misuse detection model. The misuse detection model will detect only known attacks. In-order to detect unknown attacks, we have an anomaly detection model as the second stage. SVM has been used, since it’s the best known classifier for anomaly detection which will detect patterns that deviate from normal behavior. The proposed hybrid intrusion detection has been tested and evaluated using KDD Cup ’99, NSL-KDD and UNSW-NB15 dataset.