Identification of Hemorrhages in Iris Using Hybrid Morphological Method

In the field of ophthalmology, hemorrhage is the term used more often because of increasing diabetic patients. It’s a challenge amidst the ophthalmologist to distinguish the hemorrhage from the blood vessels, these lands in various problems. In the past various techniques were employed for the detection of the hemorrhage but they were not so accurate and often encountered misclassification between hemorrhage and blood vessels. Precise detection and classification of hemorrhage and blood vessel is very important in the diagnosis of many problems. This paper depicts a mechanized procedure for recognizing hemorrhages in fundus pictures. The acknowledgment of hemorrhages is one of the critical factors in the early finish of diabetic retinopathy. The algorithm proceeds through several steps such as image enhancement, image subtraction, morphological operations such as image thresholding, image strengthening, image thinning, erosion, morphological closing, image complement to suppress blood vessels and to highlight the hemorrhage

Internet of Things based Driver Exhaustion Detection System using Distributed Sensor Network

Accidents involving vehicles occur almost every day. Most of the accidents are caused due to exhaustion of driver’s consciousness but this cause goes almost unreported due to the absence of systems to detect the fatigue. Techniques to measure driver fatigue can be invasive or non-invasive. All in all, driver-related information uncover a more grounded relationship to the driver's carefulness level than vehicle-related ones, which experience the ill effects of a bigger affectability to outer parameters, for example, street and traffic conditions. A measure of the amount of grip that the driver applies on the steering wheel is a more direct and non-invasive measure of his fatigue. An alcohol sensor when added to this system can further be used to check if the variation in grip is due to the effect of alcohol. A suitable algorithm is developed to confirm the occurrence of driver fatigue. The GSM and the GPS units attached to the system can be useful in notifying the control room in the event of driver fatigue. This project can be very useful in detecting fatigues in drivers associated with vehicle fleets using IoT

A model of cryptographic network protection when using distributed Big Data arrays

Big Data arrays are used when analysing the accumulated information and identifying patterns that can be implemented in the form of documents or development strategies, depending on the type of object. The use of the Big Data analysis methodology makes it possible to assert that the formation of clusters for storing and using the obtained information is possible only with an active correlation and interaction between individual arrays. The novelty of the study is determined by the fact that the use of Big Data in the tasks of socio-economic development requires the simultaneous analysis of information from various institutions and establishments. The authors show that Big Data analysis for the purposes of socio-economic development is possible only if access to distributed networks is established. At the same time, network protection should be based on closed cryptographic protocols. The paper shows that the use of protocols of a cryptographic type also makes it possible to verify the received data. The practical significance of the study is determined by the structure of a distributed type network and formation of a model for using Big Data in the tasks of socio-economic development. This will allow in the long term to ensure the establishment of a civil society model and reduce both financial and credibility losses

COMBINATION OF PIXEL VALUE DIFFERENCING ALGORITHM WITH CAESAR ALGORITHM FOR STEGANOGRAPHY

Steganography is a method that can be used to secure information. Steganography is hiding information or messages into other media such as digital images, text, voice or video so as not to arouse suspicion of others. Steganography methods that are widely used today still have shortcomings regarding quality, capacity, and robustness. Therefore, it needs steganography methods other better, and to add to the information security, steganography can combine with cryptography. Steganography method used is the method of pixel value differencing (PVD). This approach can insert a message more to the pixels you pick a high contrast value. To increase the security level of information to be embedded into the image, use cryptography such as Caesar cipher algorithm. Caesar cipher is an algorithm that used as a standard encryption by using an alphabet. Research conducted that combine cryptography steganography in digital imagery. Then testing the steganographymethods used to determine the capacity of the image, the performance of the method pixel value differencing (PVD), the resulting image quality, and resistance to manipulation of image and Steganalysis

Implementation of Modified Median Filtering Algorithm for Salt & Pepper Noise Reduction on Imag e

Noise is one form of issue in the image, salt & pepper noise is the kind of noise that can be made using a special technique or also due to the conversion from analog signals to digital, the noise can be improved by using algorithms such as the mean filtering, the mid-point filtering and median filtering, median filtering algorithm is widely used for repair image quality, this article will discuss the modification of the median filtering to improve noise in the image by taking the average of neighboring pixels by 2 points from the value of the center clockwise, the value is taken to be processed to retrieve the value of the middle and then the overall result value will be divided to replace the center pixel value 3x3 spatial window

A prototype fire detection implemented using the Internet of Things and fuzzy logic

Dangerous fires often occur because slow fire spots have the potential to become big fires that are difficult to extinguish. An example of this danger are peatlands in Riau, Indonesia. These dangerous conditions can be ameliorated by first detecting them. A device was developed that can detect fire hotspots by using the Internet of Things (IoT) and fuzzy logic. This early prototype fire detection tool could identify hotspots in the peatlands by using fire sensors, temperature sensors, servo motors, buzzers and surveillance cameras controlled by a WEMOS ESP8266 microcontroller and by applying the fuzzy logic method to analyse the intensity of the detected flames. Based on an experiment using the prototype, fire detection devices with an IoT connection can speed up the monitoring of fire hotspots, and the use of fuzzy logic can minimise false warnings from fire detection devices. The prototype could be used as a medium of learning for high school students majoring in computer engineering and networking

A prototype fire detection implemented using the Internet of Things and fuzzy logic

Dangerous fires often occur because slow fire spots have the potential to become big fires that are difficult to extinguish. An example of this danger are peatlands in Riau, Indonesia. These dangerous conditions can be ameliorated by first detecting them. A device was developed that can detect fire hotspots by using the Internet of Things (IoT) and fuzzy logic. This early prototype fire detection tool could identify hotspots in the peatlands by using fire sensors, temperature sensors, servo motors, buzzers and surveillance cameras controlled by a WEMOS ESP8266 microcontroller and by applying the fuzzy logic method to analyse the intensity of the detected flames. Based on an experiment using the prototype, fire detection devices with an IoT connection can speed up the monitoring of fire hotspots, and the use of fuzzy logic can minimise false warnings from fire detection devices. The prototype could be used as a medium of learning for high school students majoring in computer engineering and networking

A prototype fire detection implemented using the Internet of Things and fuzzy logic

Dangerous fires often occur because slow fire spots have the potential to become big fires that are difficult to extinguish. An example of this danger are peatlands in Riau, Indonesia. These dangerous conditions can be ameliorated by first detecting them. A device was developed that can detect fire hotspots by using the Internet of Things (IoT) and fuzzy logic. This early prototype fire detection tool could identify hotspots in the peatlands by using fire sensors, temperature sensors, servo motors, buzzers and surveillance cameras controlled by a WEMOS ESP8266 microcontroller and by applying the fuzzy logic method to analyse the intensity of the detected flames. Based on an experiment using the prototype, fire detection devices with an IoT connection can speed up the monitoring of fire hotspots, and the use of fuzzy logic can minimise false warnings from fire detection devices. The prototype could be used as a medium of learning for high school students majoring in computer engineering and networking

Analysis of Library Book Borrower Patterns Using Apriori Association Data Mining Techniques

The library is one of the most important facilities because it manages collections of written works, printed works, and recorded works and can provide information resources as well as be a driving force for the advancement of an educational institution. Conventional libraries will have piles of book borrowing transaction data recorded in the agenda book, which is only an archive, and the placement of books far apart, which causes members to take longer to find books when borrowing books of different types, is an issue that must be addressed. To overcome these two issues, a recommendation for an intelligent system is required. This study was carried out in one of Indonesia\u27s vocational schools, with data collected through observation and interviews with librarians. The goal of this study is to examine the borrowing pattern of books using association data mining techniques. The association method used is a priori, and it will result in recommendations for association rules. The result of the association rule with reference to the 2-itemset with the highest value is a combination of Religion book and Physical Education book with 8 percent support and 100 percent confidence, whereas the association rule with 3-itemset reference resulted in 4 rules with 6 percent support and 100 percent confidence. The result is an application that can generate association rules for book recommendations and book placement recommendations