Model Deteksi Kebakaran Hutan dan Lahan Menggunakan Transfer Learning DenseNet201

Kebakaran hutan dan lahan di Indonesia merupakan peristiwa yang sering terjadi dan menimbulkan kerugian yang signifikan dalam bidang kesehatan, ekologi, dan sosial. Faktor manusia dan alam berperan dalam memicu terjadinya kebakaran ini. Namun, penanganan kebakaran hutan dan lahan masih menghadapi kendala dalam memprediksi lokasi titik panas secara akurat, sehingga pengendalian yang optimal sulit dilakukan. Oleh karena itu, diperlukan pengembangan sistem cerdas untuk mendeteksi kebakaran hutan dan lahan dengan lebih efektif. Penelitian ini bertujuan untuk menciptakan sebuah model yang mampu mendeteksi kebakaran hutan dan lahan dengan menggunakan pendekatan transfer learning, dengan memanfaatkan arsitektur DenseNet201 guna meningkatkan akurasi deteksi. Dataset yang digunakan dalam penelitian ini berasal dari Fire Forest Dataset pada situs Kaggle. Proses ekstraksi fitur dilakukan menggunakan arsitektur DenseNet201, dan model yang dihasilkan diuji dengan menggunakan metode confusion matrix untuk mengklasifikasikan gambar menjadi dua kelas, yaitu kelas api dan non-api. Melalui pelatihan menggunakan arsitektur DenseNet201, diperoleh model yang efektif dalam mendeteksi kebakaran hutan dan lahan. Hasil pengujian dengan menggunakan data uji sebanyak 380 data menunjukkan tingkat akurasi sebesar 99% dalam mengenali gambar kebakaran hutan dan lahan. Penelitian ini memberikan kontribusi penting dalam pengembangan teknologi deteksi kebakaran hutan dan lahan. Penggunaan pendekatan transfer learning dengan arsitektur DenseNet201 memiliki potensi untuk meningkatkan akurasi deteksi kebakaran yang lebih baik. Diharapkan penelitian ini dapat memberikan landasan bagi pengembangan sistem cerdas yang lebih canggih dan efektif dalam mengatasi masalah kebakaran hutan dan lahan, serta melindungi lingkungan dan kesehatan masyarakat di Indonesia

Model Deteksi Kebakaran Hutan dan Lahan Menggunakan Transfer Learning DenseNet201

Kebakaran hutan dan lahan di Indonesia merupakan peristiwa yang sering terjadi dan menimbulkan kerugian yang signifikan dalam bidang kesehatan, ekologi, dan sosial. Faktor manusia dan alam berperan dalam memicu terjadinya kebakaran ini. Namun, penanganan kebakaran hutan dan lahan masih menghadapi kendala dalam memprediksi lokasi titik panas secara akurat, sehingga pengendalian yang optimal sulit dilakukan. Oleh karena itu, diperlukan pengembangan sistem cerdas untuk mendeteksi kebakaran hutan dan lahan dengan lebih efektif. Penelitian ini bertujuan untuk menciptakan sebuah model yang mampu mendeteksi kebakaran hutan dan lahan dengan menggunakan pendekatan transfer learning, dengan memanfaatkan arsitektur DenseNet201 guna meningkatkan akurasi deteksi. Dataset yang digunakan dalam penelitian ini berasal dari Fire Forest Dataset pada situs Kaggle. Proses ekstraksi fitur dilakukan menggunakan arsitektur DenseNet201, dan model yang dihasilkan diuji dengan menggunakan metode confusion matrix untuk mengklasifikasikan gambar menjadi dua kelas, yaitu kelas api dan non-api. Melalui pelatihan menggunakan arsitektur DenseNet201, diperoleh model yang efektif dalam mendeteksi kebakaran hutan dan lahan. Hasil pengujian dengan menggunakan data uji sebanyak 380 data menunjukkan tingkat akurasi sebesar 99% dalam mengenali gambar kebakaran hutan dan lahan. Penelitian ini memberikan kontribusi penting dalam pengembangan teknologi deteksi kebakaran hutan dan lahan. Penggunaan pendekatan transfer learning dengan arsitektur DenseNet201 memiliki potensi untuk meningkatkan akurasi deteksi kebakaran yang lebih baik. Diharapkan penelitian ini dapat memberikan landasan bagi pengembangan sistem cerdas yang lebih canggih dan efektif dalam mengatasi masalah kebakaran hutan dan lahan, serta melindungi lingkungan dan kesehatan masyarakat di Indonesia

CHARACTERIZATION AND FODDER PRODUCTION POTENTIAL OF LOCAL COWPEA GERMPLASM

ABSTRACT In order to improve the acute scarcity of fresh fodder in the country, four local fodder legumes (cowpea) namely CP-1, CP-8, CP-31 and CP-801 were compared for plant characteristics and fresh fodder production potential at NWFP Agricultural University, Peshawar. CP-1 required minimum days to emergence (4.7 days), flowering (87 days) and pod formation (94.7 days) and the shortest plant length (235 cm). CP-8 produced the longest plants (382 cm) though statistically not different than CP-31 and CP-801. CP-8 gave the maximum grain yield (969lg.ha -1 ); seeds pod -1 (11.3) and 100 seed weight (11.4g). The pods plant -1 and grain yield ha -1 produced by CP-1 were significantly lower than the other three germplasms. Generally the fresh fodder yield in all germplasms gradually increased from 14 ton ha -1 , 50 days after emergence to 64.2 ton ha -1 ,125 days after emergence. However, slight decline was observed with further interval of 25 days. CP-8 produced 30-40 percent more fresh fodder than the other germplasm, and accumulated 638 kg ha -1 fresh fodder compared with CP-1 (460 kg ha -1 ). It is concluded that maximum fresh fodder can be obtained 125 days after emergence and CP-8 gave the maximum grains as well as fresh fodder yield among the germplasms tested. Keywords: fodder production, cowpea, germplasm, plant characterization, yield. INTRODUCTION Although livestock is one of the major component of sustainable agriculture in NWFP particularly in mountainous areas, yet the scarcity of fodder is the major constraint in livestock production. The deficiency in nutrient supply has been estimated as 40.57 % in dry matter, 52.95 % in crude protein and 38.75 % in TDN, which will grow further due to increase in livestock population and diminishing trend in feed supply. The area occupied by fodder crops (6.84 %) supplies only 6.8 % of the feed resources of the province. Development in fodder and forages could be achieved through development in fodder research. Although Cowpea (Vigna ungiculata (L) Walp) is a minor component of sustainable agriculture, grown for its mature seeds, immature fruits and leaves and as feed for livestock, yet its potential as a quality fodder has not been explored. The present study aimed to characterize and determine the fodder production potential of local cowpea germplasm, while evaluating seventeen cowpea genotypes for forage production in potwar rainfed area. Bhatti et al. (1983) reported 27.25 t ha -1 fresh fodder and 5.7 t ha -1 DM for the top ranking genotype with the highest number of branches and leaves. Similarly Jatasra, (1983) testing twenty cowpea cultivars in semi arid tract of Havyana, India reported 5 t ha -1 fresh fodder and 1 t DM ha -1 for the two top varieties. Khan and Stoffella evaluated nine cultivars of cowpea in 1985 and ten in 1989 in Florida and Oklahoma, USA. Forage yields were high in Florida due to high nitrogen fertilization and seed yield and size was higher in Oklahoma. Generally 50 % of the seed came from main stem and 50 % form the branches with variable proportion in cultivars

Rapeseed oil spray development of diesel idi spray nozzle under air movement influence

Rapeseed oil (RO) spray has very slow atomization due to its high viscosity nature. Although high injection pressure, high ambient temperature and combination of nozzle can promote faster atomization of rapeseed oil spray, another factor that was not discussed is the effect air movement that could positively influence RO spray development. To study the effect of air movement, in particular to generate the swirl (air movement inside the chamber), a swirler was used. Images were captured using a nano-spark shadowgraph photography technique and also high speed video imaging. Macrostructures of diesel sprays such as spray tip penetration length, spray shape, spraycone angle were obtained. Microstructures, such as droplet distribution and size were also studied. Result shows that IDI nozzle rapeseed oil spray has a narrow spray cone angle. The average droplet size is around 20~25µm. The large size of rapeseed oil droplet require assistant to improve atomization and results shows rapid air movement in chamber successfully improve atomizatio

Study on Mist Nozzle Spray Characteristics for Cooling Application

Evaporative cooling mist spray is a cost effective solution for many cooling applications. Selection of misting spray nozzle play a major role in order to provide the suitable spraying condition in regards to the application. One of the most widely use mist spray application is evaporative cooling of outdoor open area. This study was carried out to characterized the spray formation, size of droplet, velocity of the droplet and the angle of the spray formation from a commercial mist spray nozzle namely 1/8 SF-CE SM nozzle with 1 mm and 2 mm diameter hole. Water was supplied with different pressure of 1, 2 and 4 bar. High speed video camera and still digital camera using short burst of flash were used to produce the video and image for analysis. The results show that increase in water pressure affect the spray angle, increase droplet speed and decrease droplet size of the mist spray

Numerical study of variable length exhaust pipe in small engine

Small engines, with capacity not exceeding 150 cc, can be divided into two types: two-stroke and four-stroke engines. The exhaust pipe has significant influences on the performance of the engine. Thus, it is necessary to study factors that affect the exhaust in order to improve the performance of the engine. For this early stage, it would be appropriate to conduct the research by using simulations since they only require minimal resources and can be conducted in a short period. The objective of this study is to conduct the simulation for determining the required velocity and pressure in the exhaust pipe. The comparison is done between parameter values from different configuration of exhaust pipes; the most appropriate configuration is then proposed. Three types of exhaust pipe is proposed using computer software and simulations are carried out using ANSYS Workbench 15.0. Results show that the velocity and pressure fluctuate according to the diameter and length of the exhaust pipe. Model 3 exhaust pipe configurations have been selected as the most suitable exhaust pipe for obtaining the maximum pressure and velocity

Numerical simulation of aerofoil with flow injection at the upper surface

Separation of the boundary layer over an airfoil causes a significant increase in the adverse pressure gradients and the losses of energy resulting in the reduction of the lift force and the increment of drag force. Therefore, delaying and eliminating flow separation is necessary to improve its aerodynamic characteristics. In this study, an injection of flow was introduced at the upper surface/suction side of the aerofoil to control the boundary layer separation effectively. Flow around the NACA0012 airfoil was examined, with the position of flow injection jet at 90° relative to the tangential surface of the airfoil at 20%, 50% and 80% of its chord length. The flow injection velocity was varied from 0%, 10%, 30% and 50% of the free stream velocity, which corresponds to 0, 2.5 x 10-4, 2.25 x 10-3 and 6.25 x 10-3 of the momentum coefficient. The results showed that the most suitable condition was at 10% of the blowing amplitude (2.5 x 10-4 of the momentum coefficient) of flow injection at the trailing edge, which was around 80% of the chord length at the upper surface/suction side. This configuration can successfully increase the lift force and decrease the drag force of the aerofoil at the angle equal to or larger than a stall angle of 16° compared to the baseline aerofoil