Implementation of Otsu’s Method in Vein Locator Devices

Abstract—In finding the position of the vein for injection process can bring any difficulty particularly for the patient who has too deep vein position under the skin. Sometimes it causes the nurses do several injections to find the right vein position. This problem will make the patient uncomfortable. The objective of this research tries to solve that patients scaring through modifying normal IR CCTV camera to become a biomedical device in order to visualize vein location on a human hand. The normal IR CCTV camera is modified by removing the IR cut filter to allow mid-infrared wavelengths. In order to find the vein location, a few stages must be done such as remove the background, extracting into the single color plane, reversing the image, filtering, thresholding with Otsu’s method and eroding. This system was named with Vein Scanner System (VSS) which have function look like a scanner. To utilize the scanner recording process, this research used a stepper motor that has a function to perform scanning by moving the camera gradually along the desired point of the human hand. In controlling approach was used raspberry Pi as the core of the VSS to do image processing and to control camera position. Then, the Vein Locator Device was used to compare with the VSS to make sure the right vein. Finally, the VSS has succeeded to visualize the vein on hand

Multicriteria Resource Brokering in Cloud Computing for Streaming Service

By leveraging cloud computing such as Infrastructure as a Service (IaaS), the outsourcing of computing resources used to support operations, including servers, storage, and networking components, is quite beneficial for various providers of Internet application. With this increasing trend, resource allocation that both assures QoS via Service Level Agreement (SLA) and avoids overprovisioning in order to reduce cost becomes a crucial priority and challenge in the design and operation of complex service-based platforms such as streaming service. On the other hand, providers of IaaS also concern their profit performance and energy consumption while offering these virtualized resources. In this paper, considering both service-oriented and infrastructure-oriented criteria, we regard this resource allocation problem as Multicriteria Decision Making problem and propose an effective trade-off approach based on goal programming model. To validate its effectiveness, a cloud architecture for streaming application is addressed and extensive analysis is performed for related criteria. The results of numerical simulations show that the proposed approach strikes a balance between these conflicting criteria commendably and achieves high cost efficiency

Realtime IoT based Harmonics Monitoring System Review with Potential Low-Cost Devices with Experimental Case Study

This paper presents a harmonic analyzer that used IoT and smart apps for low-cost and portable solutions. We contribute a short review of harmonics measurement methods and experimental approaches for monitoring harmonics using an IoT-based system. The proposed device was built from a current sensor, a voltage sensor, and a microcontroller with an IoT transmitter which is integrated with Matlab© cloud and smart apps (android). In specific, we experimented with testing and validated our proposal using the standard instrument under a fair treatment. The measurement scenario was taken on the point of comment coupling in the building campus for 5 to 10 minutes of each comparable instrument. Based on experimental results, the proposed device could monitor the harmonics profile drawn by the loads in the building campus. The trade-off between cost and performance is founded as the truth that it takes about 1 minute to update the harmonics data. Furthermore, the average error of THDV is 5.7%, and THDI is 4.7% which is higher than the expensive instrument. These values are acceptable based on IEEE standards.  Besides, it could monitor harmonics in real-time through an android application which is easy to use and portable. In addition, the cost of making the proposed device is cheap compared to the price of the standard instruments in the market

Smartphone App for Heart Rate Monitoring and Its Impact on Education Toward Industry 4.0

 This paper presents the development of Smartphone app for monitoring the heart rate, which used as a tool for life-based learning. The app featured life-based experiments for undergraduates' students through do-it-by-your-self activities. This app was developed with Firebase to create a heart rate monitoring system interface as well as a framework for life-based experiments. Also, this app had video features as learning resources. We used an experimental method to evaluate the proposed system of learning. The subjects were 30 undergraduate students who were separated into two groups. Based on our survey, student learning outcomes increased by 35% compared to conventional experiments.

Using BDH for the Message Authentication in VANET

The transport message security provided by vehicles in VANETs is quite important; vehicle message should be real-time and it will be not complicated to validate message calculation. The method proposed in the essay is mainly to validate the identity by means of Bilinear Diffie-Hellman method, and make vehicles validate the authenticity of RSU and TA’s identity and the effectiveness of key. RSU and TA only need to validate vehicle identity, without helping vehicles produce any key. When vehicle identity validation is completed, vehicles will produce public value and transmit it to other RSU and vehicles, while other vehicles could validate the identity through the message from the sender and public value from RSU. The advantages of the method proposed in this essay are listed as follows. (1) Vehicles, RSU, and TA can validate mutual identities and the effectiveness of keys. (2) Vehicles can produce public value functions automatically, thus reducing key control risks. (3) Vehicles do not need to show certificates to validate their identities, preventing the certificates from attacking because of long-term exposure. (4) Vehicles adopt a pseudonym ID challenge to validate their own identities during the process of handoff. (5) Vehicle messages can be validated using the Bilinear Diffie-Hellman (BDH) method without waiting for the RSU to validate messages, thus improving the instantaneity of messaging. The method proposed in the essay can satisfy source authentication, message integrity, nonrepudiation, privacy, and conditional untraceability requirements

Comparison of queen honey bee colony migration with various MPPTs on photovoltaic system under shaded conditions

Shaded conditions cause a decrease in the performance of photovoltaic (PV) systems. In this situation, the power versus voltage curve shows two maximum power points, namely local (LMPP) and global (GMPP). The main challenge for extracting the maximum power from a PV system during shading conditions is the existence of a false maximum or LMPP along with a true maximum or GMPP. Traditional maximum power point tracking (MPPT) has faced hurdles in overcoming the situation. Therefore, this paper describes the implementation of Queen Honey Bee Migration (or QHBM for short) to track GMPP of PV systems, which called QHBM MPPT. The highlight of this paper is the simulation results of QHBM MPPT on PV systems under various shading conditions. We implemented QHBM MPPT on a boost converter installed on a 1200 Wp PV system. We conducted a simulation using MATLAB® with five scenarios which aim to show the various shadows that PV systems might encounter in reality. The MPPT QHBM is tested repeatedly and then the average value is taken to measure performance in MPP tracking. The average value is used to calculate tracking efficiency, number of iteration or convergence time. We also compared QHBM with other methods, namely incremental conductance (IC) and Particle Swarm Optimization (PSO). The results obtained show that the QHBM and PSO MPPTs outperform the IC MPPT in terms of efficiency, convergence time and the number of iterations. IC MPPTs oscillate under shading conditions since no knowledge of GMPP. Both PSO and QHBM MPPTs know GMPP from scouts or particles, respectively. Therefore, PSO and QHBM MPPTs are better than IC MPPT in various shading case

Shared nearest neighbour in text mining for classification material in online learning using mobile application

There are many resources for media learning in online learning that all of the teachers made many media which it made a problem if there have the same subject and material. This problem made online learning having a big database and many materials made useless because the material has the same purpose. The big problem in overload database is that online learning can’t be accessed by everyone. This research to fix this problem developed an algorithm in Artificial Intelligence for the classification of material in online learning with the same subject and purpose so that teachers can use already media. This algorithm is text mining and Shared Nearest Neighbour (SSN) that is embedded in the mobile application to display the classification and the location of searching media in database online learning. The testing in this research applied in 142 media with 130 data training and 12 data testing is the result of testing is 94.7% of the accuracy of the algorithm and The average of validation is 73.33%

Emotion detection based on column comments in material of online learning using artificial intelligence

Many universities use online learning as media learning that each material of media which includes videos, textual content, or audio may be given remarks from college students. The lecture desires to recognize approximately the feelings of college students which include happy, disappointed, or unhappy when they accessed the media and instructors get an assessment of pleasant from their media. This study constructed a utility cellular for the detection of emotion from column remarks in the media online. The mobile application makes use of synthetic intelligence to type textual content from remarks and to decide the emotion of college students. The mobile application on a cellular device. The set of rules with inside the utility is k-Nearest Neighbour for the textual content mining feature in this study. The information of trying out these studies is commenting on YouTube channels and online studying which include SIPEJAR. The result of trying it out is that the common accuracy is 0,697, the value of recall is 0.5595, and the common precision is 0, 4421 and the accuracy for the utility of this mobile app is 70% for detection emotion-primarily based totally on a column of remark in the media online