Object's shadow removal with removal validation

We introduce in this paper, a shadow detection and removal method for moving objects especially for humans and vehicles. An effective method is presented for detecting and removing shadows from foreground figures. We assume that the foreground figures have been extracted from the input image by some background subtraction method. A figure may contain only one moving object with or without shadow. The homogeneity property of shadows is explored in a novel way for shadow detection and image division technique is used. The process is followed by filtering, removal, boundary removal and removal validation

Inhibitory Activity of Andrographolide and Andrograpanin on the Rate of PGH2 Formation

Cyclooxygenase (COX) or prostaglandin H2 synthase (PGHS) catalyzes the conversion of arachidonic acid into prostaglandins. Nonsteroidal anti-inflammatory drugs (NSAIDs) work by inhibiting both COX-1 and COX-2 isoforms, thus disturbing this reaction. In Indonesia, Andrographis paniculata (local name: sambiloto), is empirically used to reduce inflammation by consuming the herb tea of this plant. This work studied the inhibitory activity of andrographolide and andrograpanin, diterpenoids of the plant, on the rate of prostaglandin formation. Previous works have proven that andrographolide inhibited PGE2 production in LPS-induced human fibroblast cells. This study was performed by measuring the absorbance of TMPD (tetramethyl-p-phenyldiamine) oxidized by andrographolide and andrograpanin. Acetosal was used as a control drug. The rate of PGH2 formations on either COX-1 or COX- 2 was affected by andrographolide and andrograpanin. Andrographolide and andrograpanin interact longer with COX-1 than COX-2. Andrographolide shows weak inhibition on the rate of PGH2 formation, whilst andrograpanin might be further developed for potential antiinflammatory drugs. Keywords: Andrographis paniculata, anti-inflammatory, COX, cyclooxygenase, prostaglandi

The new Convolutional Neural Network (CNN) local feature extractor for automated badminton action recognition on vision based data

Automated action recognition is useful for improving the performance of the athletes through notational analysis. The notational analysis is usually used by the coach or notational analyst to study the movement patterns, strategy and tactics. Therefore, action recognition is the main key before further analysis can be done. This paper focused on developing an automated badminton action recognition using vision based dataset. 1496 badminton match image frames of 5 actions were studied - smash, clear, drop, net shot and lift. At first, the dataset was classified into 0.8:0.2 for training and testing the classification task by machine learning. Secondly, features of the training dataset were extracted using the Alexnet Convolutional Neural Network (CNN) model. In extracting the features, we introduced the new local feature extractor technique that extracts features at the fc8 layer. After collecting all the features at the fc8 layer, features were being classified by using machine learning classifier which is linear Support Vector Machine (SVM). The experiment was repeated using a normal global feature extractor technique. Lastly, both of the new local and global feature extractor techniques were repeated using GoogleNet CNN model to compare the performance between AlexNet and GoogleNet model. The results show that the new local feature extractor using AlexNet CNN model has the best performance accuracy which is 82.0%

Pengembangan Perangkat Pembelajaran Persamaan Lingkaran Menggunakan Pendekatan Saintifik Berbantuan Geogebra

This research is a research and development that aims to develop learning tools such as student worksheets (LKS) and lesson plans (RPP) on the circles equation. The approach used is scientific approach with the help of Geogebra.The development is done by following 4D models of development that is only done 3 phases: define, design and development without doing disseminate phase. The quality of development products are Valid, Practical and effective. The validation is done by two validators and after validated the products were tested in the classroom to determine it's practicality and effectiveness level. The subject of this reasearch were the two validators and 22 students of 11th grade senior high school

Pengembangan Perangkat Pembelajaran Matematika dengan Pendekatan Saintifik untuk Meningkatkan Penalaran Siswa pada Materi Peluang di SMA Kelas XII

Penelitian ini dimaksudkan untuk mengembangkan perangkat pembelajaran matematika berbasis pendekatan saintifik untuk meningkatkan penalaran siswa pada materi peluang di SMA kelas XII yang valid, praktis, dan efektif. Model pengembangan yang digunakan dalam penelitian ini adalah model Dick and Carey. Perangkat pembelajaran yang dikembangkan berupa RPP dan LKS. RPP dan LKS disusun dengan mengacu pada pendekatan saintifik yang memuat 5M (mengamati, menanya, mengumpulkan informasi, menalar, mengomunikasikan). LKS yang disusun juga memuat langkah penalaran model Polya yaitu: 1) pengamatan terhadap suatu permasalahan, 2) Perumusan dugaan dari permasalahan tersebut, 3) generalisasi, dan 4) verifikasi dugaan menggunakan permasalahan baru. Dari penelitian ini telah dihasilkan perangkat pembelajaran yang valid, praktis, dan efektif

Wearable inertial sensor for human activity recognition in field hockey: Influence of sensor combination and sensor location

Having a systemic system in recognizing activity in sports is very essential along with enhancing the performance analysis in sport. As the system is required to provide a quality, reliable and unbiased notational data for determining the strength and weakness of field hockey players. Therefore, this study is analysing the accelerometer and gyroscope signal on of the four inertial sensors attached to the upper body chest, waist, right and left wrist and formulate the best model in using the wearable sensor for human activity recognition in the field hockey which are passing, drive, drag flick, dribbling, receiving and tackling. Set of features such as mean, standard deviation, maximum and minimum peak are extracted from each inertial sensor signal as an input vector for classification purpose. Results from the study shows that the recognition using combination of all four sensors achieved the highest performance of 96.7% accuracy; and waist and left wrist is recommended if single sensor based human activity recognition is preferred

Badminton player detection using faster region convolutional neural network

Nowadays, coaches and sport analyst are concerning about sport performance analysis through sport video match. However, they still used conventional method which is through manual observation of the full video that is very troublesome because they might miss some meaningful information presence in the video. Several previous studies have discussed about tracking ball movements, identification of player based on jersey color and number as well as player movement detection in various type of sport such as soccer and volleyball but not in badminton. Therefore, this study focused on developing an automated system using Faster Region Convolutional Neural Network (Faster R-CNN) to track the position of the badminton player from the sport broadcast video. In preparing the dataset for training and testing, several broadcast videos were converted into image frames before labelling the region which indicate the players. After that, several different trained Faster R-CNN detectors were produced from the dataset before tested with different set of videos to evaluate the detector performance. In evaluating the performance of each detector model, the average precision was obtained from precision recall graph. As a result, this study revealed that the detector successfully detects the player when the detector is being fed with more generalized dataset

Evaluation of kinect sensor in mechanical horse simulator for equine-assisted therapy

Equine-Assisted therapy (EAT) is one of therapy strategy practiced for disabled people to improve physical functions which can be performed using either real horse or mechanical house simulator. In EAT based on horse simulator, there is no automatic tracking tools that are being used to track movement, speed, position or posture of rider on horses during equine-Assisted therapy. Hence, this study aims to evaluate the potential application of Kinect as the sensor for automated tracking of rider speed on a mechanical horse simulator. This sensor is used to capture skeletal data of rider riding mechanical horse simulator for three increasing speed and to analyze the skeletal data using the boxplot approach. From 25 human joints that could be detected, there are four joints that are significance and stable joints to represent the speed which are joint 2 (neck), joint 3 (head), joint 4 (left shoulder) and joint 8 (right shoulder)

Electrochemistry Study on the Relationship Between Grain Boundary State and Corrosion Behavior of Ultrafine Grained Iron Chromium Alloy

ELECTROCHEMISTRY STUDY ON THE RELATIONSHIP BETWEEN GRAIN BOUNDARY STATE AND CORROSION BEHAVIOR OF ULTRAFINE GRAINED IRON CHROMIUM ALLOY. Research on stainless steel corrosion resistance continues to grow today. This reality cannot be separated from the needs of stainless steels in various fields, one of which is bio-implant. In this research, the effect of grain size on the corrosion behavior of iron-chromium (Fe-Cr) alloy was investigated. Coarse grain Fe-Cr alloy was first processed with equal channel angular pressing (ECAP) for eight cycles to obtain ultrafine grain structure. The coarse and ultrafine grain samples then were then tested using XRD, SEM-EBSD, and the pitting corrosion properties tested using potentiodynamic polarization method in NaCl 1 M solution. The result of XRD dan SEM-EBSD shows that the initial sample is truly has a coarse grain structure, while ECAP produces an ultrafine grain structure. Corrosion test results showed that the ultrafine grain sample had better pitting corrosion resistance compared to the coarse grain sample. This behavior is related to the rate of passivation that depends on non-equilibrium grain boundaries, which can be easily observed in the ultrafine grain structure. Based on these results, it can be concluded that the ultrafine grain Fe-Cr alloy has a better corrosion resistance compared to the coarse grain