Utilizing open source software running in inexpensive high performance computing system for cfd applications

The high cost of conducting research is a significant issue for the successfulness of any research project. For research activities involving flow simulation, the licensing fee for the numerical software and the cost to acquire powerful machine are the main factors contributing to the high cost. This paper reports our experiences in setting up a cost effective way of doing computational fluid dynamics (CFD). The actions involve two areas, i.e., software and hardware. For the software, open source softwares are utilized, particularly the OpenFOAM(r) as the CFD package. For the hardware, a parallel computer made from a cluster of inexpensive desktop computer is constructed. This architecture is found able to meet our requirement in investigating various flow problems that include aeroacoustics, vibration and wind engineering for ventilation

New Multi-step Worm Attack Model

The traditional worms such as Blaster, Code Red, Slammer and Sasser, are still infecting vulnerable machines on the internet. They will remain as significant threats due to their fast spreading nature on the internet. Various traditional worms attack pattern has been analyzed from various logs at different OSI layers such as victim logs, attacker logs and IDS alert log. These worms attack pattern can be abstracted to form worms’ attack model which describes the process of worms’ infection. For the purpose of this paper, only Blaster variants were used during the experiment. This paper proposes a multi-step worm attack model which can be extended into research areas in alert correlation and computer forensic investigation

A New Generic Taxonomy on Hybrid Malware Detection Technique

Malware is a type of malicious program that replicate from host machine and propagate through network. It has been considered as one type of computer attack and intrusion that can do a variety of malicious activity on a computer. This paper addresses the current trend of malware detection techniques and identifies the significant criteria in each technique to improve malware detection in Intrusion Detection System (IDS). Several existing techniques are analyzing from 48 various researches and the capability criteria of malware detection technique have been reviewed. From the analysis, a new generic taxonomy of malware detection technique have been proposed named Hybrid-Malware Detection Technique (Hybrid-MDT) which consists of Hybrid- Signature and Anomaly detection technique and Hybrid-Specification based and Anomaly detection technique to complement the weaknesses of the existing malware detection technique in detecting known and unknown attack as well as reducing false alert before and during the intrusion occur

Similarity in Programs

An overview of the concept of program similarity is presented. It divides similarity into two types - syntactic and semantic - and provides a review of eight categories of methods that may be used to measure program similarity. A summary of some applications of these methods is included. The paper is intended to be a starting point for a more comprehensive analysis of the subject of similarity in programs, which is critical to understand if progress is to be made in fields such as clone detection

A new hybrid of fuzzy c-means method and fuzzy linear regression model in predicting manufacturing income

Analysis by human perception could not be solved using traditional method since uncertainty within the data have to be dealt with first. Thus, fuzzy structure system is considered. The objectives of this study are to determine suitable cluster by using fuzzy c-means (FCM) method, to apply existing methods such as multiple linear regression (MLR) and fuzzy linear regression (FLR) as proposed by Tanaka and Ni and to improve the FCM method and FLR model proposed by Zolfaghari to predict manufacturing income. This study focused on FLR which is suitable for ambiguous data in modelling. Clustering is used to cluster or group the data according to its similarity where FCM is the best method. The performance of models will measure by using the mean square error (MSE), the mean absolute error (MAE) and the mean absolute percentage error (MAPE). Results shows that the improvisation of FCM method and FLR model obtained the lowest value of error measurement with MSE=1.825 11 10 , MAE=115932.702 and MAPE=95.0366. Therefore, as the conclusion, a new hybrid of FCM method and FLR model are the best model for predicting manufacturing income compared to the other model

Transition metal oxide (NiO, CuO, ZnO)-doped calcium oxide catalysts derived from eggshells for the transesterification of refined waste cooking oil

This paper reports the synthesis of new transition metal oxide-modified CaO catalysts derived from eggshells for the transesterification of refined waste cooking oil. CaO is a well-known base catalyst for transesterification. However, its moderate basicity and low surface area have restricted its catalytic performance. Therefore, a new attempt was made to modify the CaO catalyst with transition metal oxides, including Ni, Cu and Zn oxides, via simple wetness impregnation method. The catalytic performance of the resulting modified CaO-based catalysts was evaluated through the transesterification reaction using refined waste cooking oil. The results showed that the NiO/CaO(10 : 90)(ES) catalyst calcined at 700 degrees C, demonstrated being highly potential as a catalyst. It gave the highest biodiesel production (97.3%) at the optimum conditions of 1 : 18 oil-to-methanol molar ratio, 6 wt% catalyst loading and 180 minutes reaction time as verified by response surface methodology (RSM). The high catalytic activity of NiO/CaO(10 : 90)(ES)(700 degrees C) was attributed to its high basicity (8.5867 mmol g(-1)) and relatively large surface area (7.1 m(2) g(-1)). The acid value and free fatty acids of the biodiesel produced under optimal process conditions followed the EN 14214 and ASTM D6751 limit with 0.17 mg KOH per g (AV) and 0.09 mg KOH per g (FFA), respectively

The structure of a major surface antigen SAG19 from Eimeria tenella unifies the Eimeria SAG family

In infections by apicomplexan parasites including Plasmodium, Toxoplasma gondii, and Eimeria, host interactions are mediated by proteins including families of membrane-anchored cysteine-rich surface antigens (SAGs) and SAG-related sequences (SRS). Eimeria tenella causes caecal coccidiosis in chickens and has a SAG family with over 80 members making up 1% of the proteome. We have solved the structure of a representative E. tenella SAG, EtSAG19, revealing that, despite a low level of sequence similarity, the entire Eimeria SAG family is unified by its three-layer αβα fold which is related to that of the CAP superfamily. Furthermore, sequence comparisons show that the Eimeria SAG fold is conserved in surface antigens of the human coccidial parasite Cyclospora cayetanensis but this fold is unrelated to that of the SAGs/SRS proteins expressed in other apicomplexans including Plasmodium species and the cyst-forming coccidia Toxoplasma gondii, Neospora caninum and Besnoitia besnoiti. However, despite having very different structures, Consurf analysis showed that Eimeria SAG and Toxoplasma SRS families each exhibit marked hotspots of sequence hypervariability that map to their surfaces distal to the membrane anchor. This suggests that the primary and convergent purpose of the different structures is to provide a platform onto which sequence variability can be imposed

Re-cognizing the new self: The neurocognitive plasticity of self-processing following facial transplantation.

The face is a defining feature of our individuality, crucial for our social interactions. But what happens when the face connected to the self is radically altered or replaced? We address the plasticity of self-face recognition in the context of facial transplantation. While the of a new face following facial transplantation is a medical fact, the of a new identity is an unexplored psychological outcome. We traced the changes in self-face recognition before and after facial transplantation to understand if and how the transplanted face gradually comes to be perceived and recognized as the recipient's own new face. Neurobehavioral evidence documents a strong representation of the pre-injury appearance pre-operatively, while following the transplantation, the recipient incorporates the new face into his self-identity. The acquisition of this new facial identity is supported by neural activity in medial frontal regions that are considered to integrate psychological and perceptual aspects of the self