A New Incremental Decision Tree Learning for Cyber Security based on ILDA and Mahalanobis Distance

A cyber-attack detection is currently essential for computer network protection. The fundamentals of protection are to detect cyber-attack effectively with the ability to combat it in various ways and with constant data learning such as internet traffic. With these functions, each cyber-attack can be memorized and protected effectively any time. This research will present procedures for a cyber-attack detection system Incremental Decision Tree Learning (IDTL) that use the principle through Incremental Linear Discriminant Analysis (ILDA) together with Mahalanobis distance for classification of the hierarchical tree by reducing data features that enhance classification of a variety of malicious data. The proposed model can learn a new incoming datum without involving the previous learned data and discard this datum after being learned. The results of the experiments revealed that the proposed method can improve classification accuracy as compare with other methods. They showed the highest accuracy when compared to other methods. If comparing with the effectiveness of each class, it was found that the proposed method can classify both intrusion datasets and other datasets efficiently

Novel inhibitors of the Staphylococcus aureus quorum sensing system

The recent rise of antibiotic resistant micro-organisms has led to an increased demand for the production of novel and effective antimicrobial therapies. Staphylococcus aureus is a Gram positive human pathogen that some clinical isolate has evolved resistance to all currently available ‘front line’ antibiotics. In this study a series of small molecules, both natural and synthetic, were assessed for their ability to inhibit S. aureus virulence factor production, in the hope to identify novel molecules that inhibit S. aureus pathogenicity. Such molecules have the advantage over classical antibiotics in that they do not generate a selective pressure that can cause the evolution of drug resistant strains. IQS (Integrated Quorum Sensing Signal, 2-(2-hydroxyphenyl)-thiazole-4-carbaldehyde), is a secondary metabolite produced by Pseudomonas aeruginosa that has been suggested to function as a quorum sensing signal molecule. Here, IQS was found to inhibit S. aureus exotoxin production. In an attempt to improve potency, a small library of structurally diverse IQS analogues was synthesised. Two analogues were shown to have increased potency relative to natural IQS. Interestingly, data suggest that the active analogues, which are structurally distinct, have a different mechanism of action. The use of both in vivo reporters and biochemical analysis with purified AgrA, the response regulator that transduces the S. aureus QS signal, suggested that the lead analogue (IQS3) binds to and disrupts the DNA binding of AgrA, thus inhibiting QS by S. aureus. RNAseq data support the biochemical analysis in that the expression of virulence genes by S. aureus treated with the lead analogue mirrors that an S. aureus QS mutant. Finally, the cytotoxicity of our lead analogues were assessed. Overall, data suggest that our lead IQS analogue is a good ‘starter’ molecule for further modification in the hope to increase anti-virulence properties whilst reducing cytotoxicity

Application of element decomposing method for solving integer problems

This research objective is to solve the integer problems by using an algorithm that applied to the element decomposing method (EDCM). Integer problem is a NP-hard when the problem is large-size, more time needed to solve the problem. The EDCM cuts a structure into several elements and reconnects elements at “nodes”. This process can disconnect other nodes that not connected with the element. Moreover, it appropriately need in optimization solutions for applications, in which can give answers faster by cutting the nodes in finding the answers. There’s 2 phases of step on this research. The first phase is input data and simplex method, while the second phase is creating and developing the algorithm from EDCM application. The comparison results show how two methods are carried out between EDCM and B&B Method. The results from two methods are focused on the value and solution step by step. According to the problem, it can be solved within the number of variables 2-15. The value of the difference in the answer is on average at 0.00% and solution step used for solving problem is less on average at 40.89 %

Analisa Pengaruh Human Error Terhadap Kecelakaa Kerja Di PT. Industri Kapal Indonesia Dengan Menggunakan Pendekatan Cross Sectional Method

One of the critical processes in offshore fabrication is the transfer of the offshore module (Top Side) from the top of the jetty to PT. The Indonesian Ship Industry is a company that is engaged in shipbuilding and ship repair. This company has implemented an environmental management system, occupational safety, and health. There is a relationship between human factors and work accidents. Therefore we need a study that aims to identify the human factors that cause work accidents, study the characteristics of human factors on respondents to work accidents, and analyze the influence of human factors on accidents. This study will apply a questionnaire method of 30 respondents to collect primary data from several respondents and is a cross-sectional study. The results showed that 15 (50%) workers had minor injuries, 3 (10%) workers had serious accidents, and 12 (40%) workers had never been injured. It is expected that the company will provide sufficient information to workers about the importance of OHS, be more intensive in providing training programs, hold safety contests by providing rewards for workers and that workers will be able to increase discipline in the use of personal protective equipment and increase awareness to create a work environment safety.Salah satu proses yang kritikal ketika fabrikasi offshore yaitu proses transfer offshore module (Top Side) dari atas jetty ke PT. Indusri Kapal Indonesia merupakan perusahaan yang berusaha dalam bidang pembuatan kapal dan perbaikan kapal, Perusahaan ini telah menerapkan sistem manajemen lingkungan, keselamatan dan kesehatan kerja. terdapat hubungan antara faktor manusia dengan kecelakaan kerja. Karena itu diperlukan suatu penelitian yang bertujuan untuk mengidentifikasi faktor-faktor manusia yang menyebabkan kecelakaan kerja, mempelajari karakteristik faktor manusia pada responden terhadap kecelakaan kerja dan menganalisis pengaruh faktor manusia terhadap kecelakaan. Penelitian ini akan menerapkan metode kuesioner sebanyak 30 respoden untuk mengumpulkan data primer dari beberapa responden dan merupakan penelitian cross-sectional study (pendekatan silang). Hasil penelitian menunjukkan terdapat 15 respoden(50%) pekerja mengalami cedera ringan, 3 respoden (10%) pekerja perna mengalami kecelakaan berat, dan 12 respoden (40%) pekerja tidak pernah mengalami cedera. Diharapkan perusahaan memberikan informasi yang cukup kepada pekerja tentang pentingnya K3, lebih intensif dalam memberikan program pelatihan (training), mengadakan kontes-kontes keselamatan dengan memberikan reward bagi pekerja, serta pekerja mampu meningkatkan kedisiplinan dalam penggunaan APD dan meningkatkan kesadaran untuk menciptakan lingkungan kerja yang aman

The obligate intracellular bacterium Orientia tsutsugamushi differentiates into a developmentally distinct extracellular state

Orientia tsutsugamushi (Ot) is an obligate intracellular bacterium in the family Rickettsiaceae that causes scrub typhus, a severe mite-borne human disease. Its mechanism of cell exit is unusual amongst Rickettsiaceae, as Ot buds off the surface of infected cells enveloped in plasma membrane. Here, we show that Ot bacteria that have budded out of host cells are in a distinct developmental stage compared with intracellular bacteria. We refer to these two stages as intracellular and extracellular bacteria (IB and EB, respectively). These two forms differ in physical properties: IB is both round and elongated, and EB is round. Additionally, IB has higher levels of peptidoglycan and is physically robust compared with EB. The two bacterial forms differentially express proteins involved in bacterial physiology and host-pathogen interactions, specifically those involved in bacterial dormancy and stress response, and outer membrane autotransporter proteins ScaA and ScaC. Whilst both populations are infectious, entry of IB Ot is sensitive to inhibitors of both clathrin-mediated endocytosis and macropinocytosis, whereas entry of EB Ot is only sensitive to a macropinocytosis inhibitor. Our identification and detailed characterization of two developmental forms of Ot significantly advances our understanding of the intracellular lifecycle of an important human pathogen

A genetic algorithm approach to optimising random forests applied to class engineered data

In numerous applications and especially in the life science domain, examples are labelled at a higher level of granularity. For example, binary classification is dominant in many of these data sets, with the positive class denoting the existence of a particular disease in medical diagnosis applications. Such labelling does not depict the reality of having different categories of the same disease; a fact evidenced in the continuous research in root causes and variations of symptoms in a number of diseases. In a quest to enhance such diagnosis, data sets were decomposed using clustering of each class to reveal hidden categories. We then apply the widely adopted ensemble classification technique Random Forests. Such class decomposition has two advantages: (1) diversification of the input that enhances the ensemble classification; and (2) improving class separability, easing the follow-up classification process. However, to be able to apply Random Forests on such class decomposed data, three main parameters need to be set: number of trees forming the ensemble, number of features to split on at each node, and a vector representing the number of clusters in each class. The large search space for tuning these parameters has motivated the use of Genetic Algorithm to optimise the solution. A thorough experimental study on 22 real data sets was conducted, predominantly in a variety of life science applications. To prove the applicability of the method to other areas of application, the proposed method was tested on a number of data sets from other domains. Three variations of Random Forests including the proposed method as well as a boosting ensemble classifier were used in the experimental study. The results prove the superiority of the proposed method in boosting up the accuracy

The utility of an AMR dictionary as an educational tool to improve public understanding of antimicrobial resistance

Background: Communicating about antimicrobial resistance (AMR) to the public is challenging.   Methods: We developed a dictionary of terms commonly used to communicate about AMR. For each term, we developed learning points to explain AMR and related concepts in plain language.  We conducted a pilot evaluation in 374 high school students in Ubon Ratchathani, Thailand. In three 50-minute sessions, students were asked to answer five true/false questions using a paper-based questionnaire. The first session assessed their understanding of AMR at baseline, the second after searching the internet, and the third after the provision of the printed AMR dictionary and its web address.    Results: We developed the AMR dictionary as a web-based application (www.amrdictionary.net). The Thai version of the AMR dictionary included 35 terms and associated learning points, seven figures displaying posters promoting AMR awareness in Thailand, and 66 recommended online videos. In the pretest, the proportion of correct responses to each question ranged from 10% to 57%; 10% of the students correctly answered that antibiotics cannot kill viruses and 57% correctly answered that unnecessary use of antibiotics makes them ineffective. After the internet searches, the proportions of correct answers increased, ranging from 62% to 89% (all p&lt;0.001). After providing the AMR dictionary, the proportions of correct answers increased further, ranging from 79% to 89% for three questions (p&lt;0.001), and did not change for one question (p=0.15). Correct responses as to whether taking antibiotics often has side-effects such as diarrhoea reduced from 85% to 74% (p&lt;0.001). The dictionary was revised based on the findings and comments received. Conclusions: Understanding of AMR among Thai high school students is limited. The AMR dictionary can be a useful supportive tool to increase awareness and improve understanding of AMR. Our findings support the need to evaluate the effectiveness of communication tools in the real-world setting.</ns3:p