Analisis Faktor Risiko Merokok, Stres Dan Riwayat Keluarga Yang Berhubungan Dengan Kejadian Penyakit Jantung Koroner

Heart disease is the number one cause of death in the world, including Indonesia. According to the World Health Organization (WHO), 60 % of all causes of death of heart disease are coronary heart disease (CHD). Coronary heart disease can attack at reproductive age and cause of sudden cardiac arrest and death. This study aims to determine smoking, stress and family history are risk factors associated with the incidence of coronary heart disease. This research is an observational analytic study with case control design. This research was done at the General Hospital Bahteramas Southeast Sulawesi Province in February-March 2014. Sample in this study consisted of 49 respondents of cases and 49 respondents of controls were taken by purposive sampling with matching on age, sex, blood pressure, dyslipidemia, diabetes mellitus, body mass index and history of alcohol consumption. Data collection using medical records and questionnaires. The statistical test using odds ratio with 95% confidence intervals. The results showed that smoking is a risk factor associated with the incidence of coronary heart disease (OR = 2.450, 95 % CI = 1.050 - 5.713), stress is a risk factor that is associated with the incidence of coronary heart disease (OR = 6.250, 95 % CI = 2.353 -16.598) and family history are risk factors associated with the incidence of coronary heart disease (OR = 9.4, 95 % CI = 2.005 - 44.061). Smoking, stress and family history are risk factor associated with coronary heart disease with opportunities respectively at 2,4 times, 6,2 times and 9,4 times compared with control population

External attacks on automotive system through wireless communication channels

The reliance of today’s automotive system on electronics control system is expected to make the cars to be state-of-the-art vehicle. However, this technology dependency results in the cars to be exposed to attacks by the hacker through the manipulation of electronics system. Previously, for the attacker to compromise car’s system, he/she must access the car directly and internally. However, with the incorporation of wireless technologies such as Bluetooth and cellular into automotive system for example in its telematic units, the attacks are evolved from internal attacks into remote attack where the adversary does not have to internally access the car’s system. This paper analyses the vulnerabilities of the automotive system by the remote attacks performed through Bluetooth and cellular. Once the vulnerabilities were analyzed, the threats imposed by these vulnerabilities are accessed. Two scenarios namely theft and surveillance are used to exemplify the threats that are carried by the vulnerability of the automotive system to the remote attacks. From the vulnerability analysis and threat assessment, it can be deduced that the automotive system is vulnerable to attacks and proper countermeasure must be taken to curb the implication from the attacks.Keywords: Hardware Trojan, Insertion, Third-part IP, Trus

The extract region of interest in high-resolution palmprint using 2d image histogram entropy function

The segmentation of high-resolution palmprint is has been challenged and the research in this filed is still limited because of variations in location and distortion of these images. To achieve superior recognition result, accurate segmentation of a region of interest is very crucial. Therefore, in this paper, a novel palmprint extraction method has been presented using a 2D image histogram entropy function and mathematical dilation. The proposed method has two phases. The first phase is the binarization image where the histogram of the image will be determined after applying a median filter to remove noise and then calculating the 2D image histogram entropy function. Finally, the maximum entropy that will be the adaptive threshold value to build a binary palmprint image will be selected. The second phase is to extract the ROI, apply a dilation method on the binary image, then dividing the dilate image into four regions and finding four reference points depending on the white percentage and finally the ROI will be extracted. The publically available high-resolution palmprint THUPALMLAB has been used for testing. The result indicates a high percentage of accuracy up to 93%. The findings strongly indicate that the proposed method was able to extract the palm's ROI more consistently. These ROIs will be used in the recognition system instead of whole palmprints and hence assists in improving the performance of a traditional palmprint system. High-resolution palmprint images are highly used in the forensic application

The challenges of extract, transform and load (ETL) for data integration in near real-time environment

Organization with considerable investment into data warehousing, the influx of various data types and forms require certain ways of prepping data and staging platform that support fast, efficient and volatile data to reach its targeted audiences or users of different business needs. Extract, Transform and Load (ETL) system proved to be a choice standard for managing and sustaining the movement and transactional process of the valued big data assets. However, traditional ETL system can no longer accommodate and effectively handle streaming or near real-time data and stimulating environment which demands high availability, low latency and horizontal scalability features for functionality. This paper identifies the challenges of implementing ETL system for streaming or near real-time data which needs to evolve and streamline itself with the different requirements. Current efforts and solution approaches to address the challenges are presented. The classification of ETL system challenges are prepared based on near real-time environment features and ETL stages to encourage different perspectives for future research