Rearrangement of Coordinate Selection for Triangle Features Improvement in Digit Recognition

Triangle geometry feature demonstrated as useful properties in classifying the image. This feature has been implemented in numerous recognition field such as biometric area, security area, medical area, geological area, inspection area and digit recognition area. This study is focusing on improving triangle features in digit recognition. Commonly, triangle features are explored by determining three points of triangle shape which represent as A, B and C to extract useful features in digit recognition. There is possibilities triangle shape cannot be formed when chosen coordinate are in line. Thus, a prior study has proposed an improvement on triangle selection point technique by determining the position of coordinate A, B and C use gradient value to identify the triangle shape can be modelled or vice versa. The suggested improvement is based on the dominant distribution which only covers certain areas of an image. Hence, a method named Triangle Point using Three Block (Tp3B) was proposed in this study. The proposed method proposes the arrangement of selection coordinate point based on three different blocks which where all coordinates points of an image were covered. Experiments have developed over image digit dataset of IFCHDB, HODA, MNIST and BANGLA which contains testing and train data of each. Features classification accuracy tested using supervised machine learning (SML) which is Support Vector Machine (SVM). Experimental results show, the proposed technique gives a promising result for dataset HODA and MNIST

Intestinal and Blood Parasites of Man in Timor

Survey tinja dan darah dipulau Timor guna menentukan distribusi dan prevalensi penyakit parasit diantara penduduk telah dilakukan pada bulan Juli dan Agustus tahun 1972 sebagai kelanjutan dari deretan survey yang dilakukan oleh Direktorat Jenderal Pencegahan Pemberantasan Penyakit menular Departemen Kesehatan, Bagian Parasitologi dan Pathologi Umum Fakultas Kedokteran Universitas Indonesia dan US Namru-2 di Indonesia. Sejumlah 445 sediaan tinja untuk pemeriksaan parasit usus, 581 sediaan darah untuk pemeriksaan parasit malaria dan 663 sediaan darah untuk pemeriksaan parasit filaria telah diambil dari penduduk cara merata di 7 desa pada 3 kabupaten di Timor, Nusa Tenggara Timur. Enam puluh delapan per cent diantara penduduk melihatkan satu atau lebih parasit usus didalam tinjanya dimana cacing tambang merupakan parasit usus yang terbanyak. Ascaris lumbricoides ketemukan jauh lebih kurang daripada di Jawa, Sumatra dan Sulawesi, juga diketemukan perbedaan itara "intestinal parasite rate" di Timor Indonesia dan Timor Portugis. Dua belas percent penduduk yang diperiksa melihatkan parasit malaria didalam darahnya sedangkan parasit filaria ditemukan sebanyak 8 percent. Plasmodium falciparum merupakan parasit malaria yang terbanyak ditemukan, ia jenis parasit fdaria yang ditemukan adalah "Timor microfilaria" dan Wuchereria bancrofti dimana yang pertama merupakan parasit yang terbanyak diantara penduduk yang diperiksa

Antidesma montanum: biochemistry and bioactive compounds

Antidesma montanum is commonly known as a mountain currant tree. Its fruits and leaves are utilized locally for food and traditional medicine, meanwhile the stem is used as source of wood. The fruit contains bioactive constituents of steroid glycosides, saponins, flavonoids, polyphenols and tannins that exhibited higher antioxidant activity than at certain concentrations of standard antioxidants (i.e. vitamin E, ascorbic acid, and trolox). The leave extracts known to inhibit the activities of α-amylase and α-glucosidase in diabetic therapy. Furthermore, the leave extracts also possessed scavenging activity against both hydroxyl and superoxide anion radicals, and inhibited the nitric oxide production. Meanwhile, another studies reported on the anti-inflammatory effect of Antidesma montanum, being used to treat eye diseases, and relieving chest pain. The leaves are used externally against headache and thrush in children, for diuretic and removing kidney stone, anti-dermatitis and skin disease curing effect. A tea from the leaves is used as a tonic for mothers after giving birth and applied topically to ulcers and lumbar pains. The roots are used to treat measles, chickenpox, malaria, and stomach ache. Nevertheless, extensive research is needed to confirm the reputed beneficial effects of Antidesma montanum in traditional medicine

Pengaruh Air Lindi Tempat Pembuangan Akhir Sampah Suwung terhadap Kualitas Air Tanah Dangkal di Sekitarnya di Kelurahan Pedungan Kota Denpasar

Garbage Dump (GD) of Suwung which is located at the Village of Pedungan, South Denpasar District is dump ofgarbage coming from the City of Denpasar and Badung Regency. GD of Suwung operates with open dumping so that it ispotential to pollute the surrounding shallow ground water. This study was conducted to know the characteristics ofleachate, its effect to the quality of water around the GD and the quality of water according to water standard quality forthe need of drinking water and its status of its Pollution Index.This study was conducted with the taking of water sampleof leachate, taken in two locations, in the northern part of the GD and in the southern part of the GD. The water sample ofshallow ground water was taken at 4 location samples by considering the distance of the location from the GD. In eachlocation sample, 10 sample points were taken which were then composited into one. The analysis of physical, chemical,and microbiological characteristics of leachate and the quality of shallow ground water was done in-situ and in thelaboratory. The results obtained from the analysis compared them descriptively with tables and graphs and calculation ofthe Pollution Index (PI) of the quality of shallow underground water.The results of the study show that all the parameters of leachate did not meet the requirement of Standard Qualityof Domestic Waste Water Regulation of Bali Governor Number 8 of 2007. The quality of leachate from the Suwung GDaffected the quality of shallow ground water in all locations (L1, L2, and L3). The greatest effect in the location whosedistance is between 1 – 125 m from the GD (L1) is parameter of TDS, BOD5, COD, DO, PO4, NO3, NO2, NH3, Fe, Cl,H2S, Phenol, and total Coliform, the location whose distance is between 125 – 250 m from the GD (L2) is the parameter of TDS, BOD5, COD, DO, PO4, NO2, NH3, Cl, H2S, Phenol, and total Coliform, and the location whose distance isbetween 250 – 375 m from the GD (L3) is the parameter of BOD5, COD, DO, PO4, NO2, NH3, H2S, Phenol, and TotalColiform. At the location is far from the GD as a control location (L4) is the parameter of DO, PO4, NO2, NH3, Phenol,and Total Coliform. For the Index of Pollution in the sample locations L1, L2, and L3 was categorized into heavilypolluted level and L4 (as control) was categorized into lightly polluted level

Adoption of machine learning techniques in software effort estimation: an overview

Nowadays the significant trend of the effort estimation is in demand. It needs more data to be collected and the stakeholders require an effective and efficient software for processing, which makes the hardware and software cost development becomes steeply increasing. This scenario is true especially in the area of large industry, as the size of a software project is becoming more complex and bigger, the complexity of estimation is continuously increased. Effort estimation is part of the software engineering economic study on how to manage limited resources in a way a project could meet its target goal in a specified schedule, budget and scope. It is necessary to develop or adopt a useful software development process in executing a software development project by acting as a key constraint to the project. The accuracy of estimation is the main critical evaluation for every study. Recently, the machine learning techniques are becoming widely used in many effort estimation problems but there are limitations in some of the models and the variation research is still not enough. This paper presents an overview of the effort estimation using machine learning techniques and will be useful for researchers to provide future direction in the field of machine learning adoption in software effort estimation