dalam pengaturan frekuensi pada sistem tenaga listrik dapat dilakukan dengan metode-metode kontro... more dalam pengaturan frekuensi pada sistem tenaga listrik dapat dilakukan dengan metode-metode kontrol. namun dalam penelitian ini akan di coba pengendalian frekuensi dengan menggunakan logika fuzzy. dasar pemikiran ini di ambil dengan bertitik tolak kepada beberapa pertimbangan yaitu di lihat dari keunggulan logika fuzzy
International Archives of BioMedical and Clinical Research, 2017
Background: Iron deficiency anemia has emerged as a major public health issue in developed and de... more Background: Iron deficiency anemia has emerged as a major public health issue in developed and developing countries. According to WHO 29% of all women of reproductive age group are diagnosed to have anemia. Objectives:1) to determine Hemoglobin (Hb) levels among girls 20-21-year-old by Sahli’s method 2) to identify correlation between Hb levels and KAP scores among girls 20-21-year-old. Methods cross sectional study design applied with convenient sampling technique; and sample of 150 girls 20-21 year old was taken. Standardized KAP questionnaire was developed from FAO Guidelines upon iron deficiency anemia, and administered. Hb levels were determined in laboratory by Sahli’s method and classification of anemia was made according to WHO guidelines 2011. Frequency trend of anemia was noted, and Pearson product correlation was applied to Hb levels and KAP scores for risk analysis. Results19.3% had mild, 51.3% had moderate, and 13.3% had severe anemia. Only 16% girls had normal Hb level...
Abstrak Tujuan penelitian ini adalah: (1) untuk mengetahui hasil belajar siswa yang dibelajarkan ... more Abstrak Tujuan penelitian ini adalah: (1) untuk mengetahui hasil belajar siswa yang dibelajarkan menggunakan model pembelajaran langsung (2) untuk mengetahui hasil belajar siswa yang dibelajarkan mengunakan model pembelajaran berdasarkan masalah (3) untuk mengetahui perbedaan hasil belajar siswa yang dibelajarkan menggunakan model pembelajaran berdasarkan masalah dan model pembelajaran langsung. Penelitian ini dilakukan di SMK Negeri 1 Tambelangan Sampang. Metode penelitian yang digunakan adalah Quasi Eksperimental Design dengan rancangan penelitian Nonequivalent Control Group Design. Subyek penelitian ini adalah siswa kelas X/ELIND 1 sebagai kelas eksperimen yang dibelajarkan menggunakan model pembelajaran langsung dan kelas X/ELIND 2 sebagai kelas kontrol yang dibelajarkan menggunakan model pembelajaran berdasarkan masalah. Untuk analisis data digunakan statistic uji t. Berdasarkan uji hipotesis 1 didapatkan t hitung = 85,02 > t tabel = 1,70 dan =Â 83,34 > ideal = 50 sehingg...
2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), 2020
Satellites have become an important part of present-day data communication systems. They play a s... more Satellites have become an important part of present-day data communication systems. They play a significant role in the development and advancement of technologies such as navigation, telemedicine, tele-education, weather forecasting, radio and TV broadcasting, defense etc. With more and more technologies depending on satellite technology, the need of the hour is a reliable high throughput communication system that minimizes on hardware, power and bandwidth requirements. In order to meet the constraints, an IQ modulator based reconfigurable digital modulator is proposed in this paper. The modulator is designed in such a way that it can support any of the M-PSK or N-QAM modulation scheme. Higher order modulations in conjunction with proper pre-modulation filtering of baseband data is shown to minimize the bandwidth requirements for high bit rate data applications. The approach also allows for dynamic reconfiguration of the system for different modulation schemes, data rates and spectral occupancy without effecting any changes to the hardware. The proposed system is predicted to be the forerunner for all future space-based high data transmitters.
International Journal for Research in Applied Science and Engineering Technology, 2020
This paper proposes Machine Learning based Methodology to assist Health staff to perform bulk rep... more This paper proposes Machine Learning based Methodology to assist Health staff to perform bulk reporting of patients on Chest X-ray images into Normal or Pneumonia diseased clusters which will be of assistance to currently overburdened health workers and possibly detect potential covid19 infected patients as pneumonia is known symptom of covid19. Also this paper demonstrates creating high accuracy models trained on existing clustered data capable of accurately predicting pneumonia in patients.
In the paper entitled "FPGA Implementation of Space Qualified Bundle Protocol for Satellite Commu... more In the paper entitled "FPGA Implementation of Space Qualified Bundle Protocol for Satellite Communication" a CCSDS proposed Bundle Protocol for delay / disruption tolerant networks in space is designed. The paper presents software coding and hardware implementation of Bundle Protocol using VHDL programming and its implementation on Xilinx Vertex 4 xc4vfx60 Field Programmable Gate Array (FPGAs). The existing TCP /IP based Internet protocols have many assumptions built into their architecture which make them not suitable for space. Compared to the present Internet architecture, delay / disruption tolerant networking (DTN) technology uses store and forward paradigm for latency as long as a year, persistent storage of protocol data units, custody transfer and self delimiting numeric values (SDNV) encoding scheme to minimize the transmission bandwidth. The proposed methodology in this paper is useful in highly stressed communications in space environments especially those with long link delay, intermittent connectivity, network partitions, frequent link disruptions and fewer node resources. The main focus of this paper is to design and demonstrate a three node test set up delay and disruption tolerant network lacking end-to-end connectivity, asymmetric data rates, variable delays, and high packet error rates.
International Journal of Advanced Science and Technology, 2020
This paper proposes a parallel architecture for a successive elimination algorithm (SEA), which i... more This paper proposes a parallel architecture for a successive elimination algorithm (SEA), which is used in block matching motion estimation. SEA effectively eliminates the search points within the search window and thus decreases the number of matching evaluation instances that require very intensive computations compared to the standard full search algorithm (FSA). The proposed architecture for SEA decreases the time to calculate the motion vector by 57 percent compared to FSA. The performance while applying the SEA to several standard video clips has been shown to be same compared to the standard FSA. The proposed architecture uses 16 processing elements accompanied with use of intelligent data arrangement and memory configuration. A technique for reducing external memory accesses has also been developed. A register-transfer level implementation as well as simulation results on benchmark video clips are presented. Comparison of design statistics on area and power between SEA and FSA implementations are also provided.
International Journal of Advanced Science and Technology, 2020
In the recent years drastic changes were occurred in the mobile communications and embedded syste... more In the recent years drastic changes were occurred in the mobile communications and embedded systems. Now we incorporate mobile technology in automation systems. We propose a mobile based home automation system that consists of a mobile phone with android capabilities and a home wi-fi connection. The home appliances are controlled by the android application through wi-fi which operates according to the user commands received from the mobile phone via the wi-fi modem. In the proposed system the home wi-fi is built upon the graphical user interface through the smart phone android application and a micro controller, allowing a user to control and monitor any variables related to the home by using any android capable cell phone. The design and implementation of modem driver, text-based command processing software and power failure resilient output of a micro controller to facilitate in sending and receiving data via the cell module together with the design of android application to enable the cell phone to send commands and receive the status of home appliances. Now we can control home appliances on our figures with long distance range. So that it provides time saving, power saving, alerts etc. And, also you can just imagine how simple would it be to implement such a system in your home that too at a very reasonable cost by using cost-effective devices.
Melanoma is the most serious type of skin cancer, with a very low chance of survival, out of the ... more Melanoma is the most serious type of skin cancer, with a very low chance of survival, out of the three primary types: basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and melanoma. Melanoma early identification may increase survival rates. The four fundamental parts of skin cancer detection technology are, in general, image preprocessing, which includes hair removal, de-noise, sharpening, and resizing of the skin picture, segmentation, which is used to segment out the region of interest from the given image, and resizing. Segmentation can be done in a variety of ways. K-means, threshold in histograms, etc., as well as feature extraction from the segmented picture and classification of the image from the features set retrieved from segmented image, are some examples of segmentation techniques that are frequently employed. For this, a variety of classification techniques can be applied. Recent advances in skin cancer detection technology classify data using machine learning and deep learning-based algorithms. Support vector machine (SVM), feed forward artificial neural network, and deep convolutional neural network are the most widely used classification techniques. This essay offers research and analysis on skin cancer detection, including a thorough review of the literature on the subject and a precise comparison of cutting-edge algorithms.
Early plant leaf disease detection is a major challenge in agriculture field. The easiest way, to... more Early plant leaf disease detection is a major challenge in agriculture field. The easiest way, to control the plant leaf disease infection is an Challenging task But the excessisive use of plant leaf disease are harmful to plants, animals as well as human beings. Integrated plant leaf disease management combines biological and physical methods to prevent plant leaf disease infection. The techniques of machine vision and digital image Processing are extensively applied to agricultural science and it have great perspective especially in the plant protection field, which ultimately leads to plant leafs management. This paper deals with a new type of early detection of plant leaf diseases system. Images of the leaves affected by plant leaf diseases are acquired by using a digital camera. The leaves with plant leaf disease images are processed for getting a gray colored image and then using feature extraction, image classification techniques to detect plant leaf diseases on leaves. The images are acquired by using a digital camera. The images are then transferred to a PC and represented in python software. The RGB image is then converted into gray scale image and the feature extraction techniques are applied on that image. The Support Vector Machine classifier is used to classify the plant leaf disease types. Here in this paper we implement the deep learning and machine learning approach for identification of plat leaf disease and we found that deep learning apporch using Bidrectional CNN gives the better performace in term of accuracy Index Term:-svm,cnn,opencv,plant leaf disease,image processing
The digital world continues to witness an unprecedented growth in view of the technological advan... more The digital world continues to witness an unprecedented growth in view of the technological advancements in the field of Digital Signal Processing (DSP). The increased usage of digital applications along with the tremendous evolution of Very Large Scale Integration (VLSI) technology over a few epochs has led to the development of enhanced algorithms and architectures for DSP systems that augur to meet the demands of a wide variety of applications in this expanding horizon of the signal processing sector. Finite Impulse Response (FIR) digital filter is the most potent and frequently used component in various signal processing and image processing applications. Since the intricacy of implementation grows with the filter order and the precision of computation, real-time realization of these filters with desired level of accuracy and less area-delay-power complexity is a challenging task. consumption is low. FPGA is a semiconductor device containing programmable logic components and programmable interconnects.
Early plant leaf disease detection is a major challenge in agriculture field. The easiest way, to... more Early plant leaf disease detection is a major challenge in agriculture field. The easiest way, to control the plant leaf disease infection is an Challenging task. But the excessive use of plant leaf disease are harmful to plants, animals as well as human beings. Integrated plant leaf disease management combines biological and physical methods to prevent plant leaf disease infection. The techniques of machine vision and digital image Processing are extensively applied to agricultural science and it have great perspective especially in the plant protection field, which ultimately leads to plant leaf management. This paper deals with a new type of early detection of plant leaf diseases system. Images of the leaves affected by plant leaf diseases are acquired by using a digital camera. The leaves with plant leaf disease images are processed for getting a gray colored image and then using feature extraction, image classification techniques to detect plant leaf diseases on leaves. The images are acquired by using a digital camera. The images are then transferred to a PC and represented in python software. The RGB image is then converted into gray scale image and the feature extraction techniques are applied on that image. The Support Vector Machine classifier is used to classify the plant leaf disease types. Here in this paper we implement the deep learning and machine learning approach for identification of plat leaf disease and we found that deep learning approach using Bi-directional CNN gives the better performance in terms of accuracy.
dalam pengaturan frekuensi pada sistem tenaga listrik dapat dilakukan dengan metode-metode kontro... more dalam pengaturan frekuensi pada sistem tenaga listrik dapat dilakukan dengan metode-metode kontrol. namun dalam penelitian ini akan di coba pengendalian frekuensi dengan menggunakan logika fuzzy. dasar pemikiran ini di ambil dengan bertitik tolak kepada beberapa pertimbangan yaitu di lihat dari keunggulan logika fuzzy
International Archives of BioMedical and Clinical Research, 2017
Background: Iron deficiency anemia has emerged as a major public health issue in developed and de... more Background: Iron deficiency anemia has emerged as a major public health issue in developed and developing countries. According to WHO 29% of all women of reproductive age group are diagnosed to have anemia. Objectives:1) to determine Hemoglobin (Hb) levels among girls 20-21-year-old by Sahli’s method 2) to identify correlation between Hb levels and KAP scores among girls 20-21-year-old. Methods cross sectional study design applied with convenient sampling technique; and sample of 150 girls 20-21 year old was taken. Standardized KAP questionnaire was developed from FAO Guidelines upon iron deficiency anemia, and administered. Hb levels were determined in laboratory by Sahli’s method and classification of anemia was made according to WHO guidelines 2011. Frequency trend of anemia was noted, and Pearson product correlation was applied to Hb levels and KAP scores for risk analysis. Results19.3% had mild, 51.3% had moderate, and 13.3% had severe anemia. Only 16% girls had normal Hb level...
Abstrak Tujuan penelitian ini adalah: (1) untuk mengetahui hasil belajar siswa yang dibelajarkan ... more Abstrak Tujuan penelitian ini adalah: (1) untuk mengetahui hasil belajar siswa yang dibelajarkan menggunakan model pembelajaran langsung (2) untuk mengetahui hasil belajar siswa yang dibelajarkan mengunakan model pembelajaran berdasarkan masalah (3) untuk mengetahui perbedaan hasil belajar siswa yang dibelajarkan menggunakan model pembelajaran berdasarkan masalah dan model pembelajaran langsung. Penelitian ini dilakukan di SMK Negeri 1 Tambelangan Sampang. Metode penelitian yang digunakan adalah Quasi Eksperimental Design dengan rancangan penelitian Nonequivalent Control Group Design. Subyek penelitian ini adalah siswa kelas X/ELIND 1 sebagai kelas eksperimen yang dibelajarkan menggunakan model pembelajaran langsung dan kelas X/ELIND 2 sebagai kelas kontrol yang dibelajarkan menggunakan model pembelajaran berdasarkan masalah. Untuk analisis data digunakan statistic uji t. Berdasarkan uji hipotesis 1 didapatkan t hitung = 85,02 > t tabel = 1,70 dan =Â 83,34 > ideal = 50 sehingg...
2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), 2020
Satellites have become an important part of present-day data communication systems. They play a s... more Satellites have become an important part of present-day data communication systems. They play a significant role in the development and advancement of technologies such as navigation, telemedicine, tele-education, weather forecasting, radio and TV broadcasting, defense etc. With more and more technologies depending on satellite technology, the need of the hour is a reliable high throughput communication system that minimizes on hardware, power and bandwidth requirements. In order to meet the constraints, an IQ modulator based reconfigurable digital modulator is proposed in this paper. The modulator is designed in such a way that it can support any of the M-PSK or N-QAM modulation scheme. Higher order modulations in conjunction with proper pre-modulation filtering of baseband data is shown to minimize the bandwidth requirements for high bit rate data applications. The approach also allows for dynamic reconfiguration of the system for different modulation schemes, data rates and spectral occupancy without effecting any changes to the hardware. The proposed system is predicted to be the forerunner for all future space-based high data transmitters.
International Journal for Research in Applied Science and Engineering Technology, 2020
This paper proposes Machine Learning based Methodology to assist Health staff to perform bulk rep... more This paper proposes Machine Learning based Methodology to assist Health staff to perform bulk reporting of patients on Chest X-ray images into Normal or Pneumonia diseased clusters which will be of assistance to currently overburdened health workers and possibly detect potential covid19 infected patients as pneumonia is known symptom of covid19. Also this paper demonstrates creating high accuracy models trained on existing clustered data capable of accurately predicting pneumonia in patients.
In the paper entitled "FPGA Implementation of Space Qualified Bundle Protocol for Satellite Commu... more In the paper entitled "FPGA Implementation of Space Qualified Bundle Protocol for Satellite Communication" a CCSDS proposed Bundle Protocol for delay / disruption tolerant networks in space is designed. The paper presents software coding and hardware implementation of Bundle Protocol using VHDL programming and its implementation on Xilinx Vertex 4 xc4vfx60 Field Programmable Gate Array (FPGAs). The existing TCP /IP based Internet protocols have many assumptions built into their architecture which make them not suitable for space. Compared to the present Internet architecture, delay / disruption tolerant networking (DTN) technology uses store and forward paradigm for latency as long as a year, persistent storage of protocol data units, custody transfer and self delimiting numeric values (SDNV) encoding scheme to minimize the transmission bandwidth. The proposed methodology in this paper is useful in highly stressed communications in space environments especially those with long link delay, intermittent connectivity, network partitions, frequent link disruptions and fewer node resources. The main focus of this paper is to design and demonstrate a three node test set up delay and disruption tolerant network lacking end-to-end connectivity, asymmetric data rates, variable delays, and high packet error rates.
International Journal of Advanced Science and Technology, 2020
This paper proposes a parallel architecture for a successive elimination algorithm (SEA), which i... more This paper proposes a parallel architecture for a successive elimination algorithm (SEA), which is used in block matching motion estimation. SEA effectively eliminates the search points within the search window and thus decreases the number of matching evaluation instances that require very intensive computations compared to the standard full search algorithm (FSA). The proposed architecture for SEA decreases the time to calculate the motion vector by 57 percent compared to FSA. The performance while applying the SEA to several standard video clips has been shown to be same compared to the standard FSA. The proposed architecture uses 16 processing elements accompanied with use of intelligent data arrangement and memory configuration. A technique for reducing external memory accesses has also been developed. A register-transfer level implementation as well as simulation results on benchmark video clips are presented. Comparison of design statistics on area and power between SEA and FSA implementations are also provided.
International Journal of Advanced Science and Technology, 2020
In the recent years drastic changes were occurred in the mobile communications and embedded syste... more In the recent years drastic changes were occurred in the mobile communications and embedded systems. Now we incorporate mobile technology in automation systems. We propose a mobile based home automation system that consists of a mobile phone with android capabilities and a home wi-fi connection. The home appliances are controlled by the android application through wi-fi which operates according to the user commands received from the mobile phone via the wi-fi modem. In the proposed system the home wi-fi is built upon the graphical user interface through the smart phone android application and a micro controller, allowing a user to control and monitor any variables related to the home by using any android capable cell phone. The design and implementation of modem driver, text-based command processing software and power failure resilient output of a micro controller to facilitate in sending and receiving data via the cell module together with the design of android application to enable the cell phone to send commands and receive the status of home appliances. Now we can control home appliances on our figures with long distance range. So that it provides time saving, power saving, alerts etc. And, also you can just imagine how simple would it be to implement such a system in your home that too at a very reasonable cost by using cost-effective devices.
Melanoma is the most serious type of skin cancer, with a very low chance of survival, out of the ... more Melanoma is the most serious type of skin cancer, with a very low chance of survival, out of the three primary types: basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and melanoma. Melanoma early identification may increase survival rates. The four fundamental parts of skin cancer detection technology are, in general, image preprocessing, which includes hair removal, de-noise, sharpening, and resizing of the skin picture, segmentation, which is used to segment out the region of interest from the given image, and resizing. Segmentation can be done in a variety of ways. K-means, threshold in histograms, etc., as well as feature extraction from the segmented picture and classification of the image from the features set retrieved from segmented image, are some examples of segmentation techniques that are frequently employed. For this, a variety of classification techniques can be applied. Recent advances in skin cancer detection technology classify data using machine learning and deep learning-based algorithms. Support vector machine (SVM), feed forward artificial neural network, and deep convolutional neural network are the most widely used classification techniques. This essay offers research and analysis on skin cancer detection, including a thorough review of the literature on the subject and a precise comparison of cutting-edge algorithms.
Early plant leaf disease detection is a major challenge in agriculture field. The easiest way, to... more Early plant leaf disease detection is a major challenge in agriculture field. The easiest way, to control the plant leaf disease infection is an Challenging task But the excessisive use of plant leaf disease are harmful to plants, animals as well as human beings. Integrated plant leaf disease management combines biological and physical methods to prevent plant leaf disease infection. The techniques of machine vision and digital image Processing are extensively applied to agricultural science and it have great perspective especially in the plant protection field, which ultimately leads to plant leafs management. This paper deals with a new type of early detection of plant leaf diseases system. Images of the leaves affected by plant leaf diseases are acquired by using a digital camera. The leaves with plant leaf disease images are processed for getting a gray colored image and then using feature extraction, image classification techniques to detect plant leaf diseases on leaves. The images are acquired by using a digital camera. The images are then transferred to a PC and represented in python software. The RGB image is then converted into gray scale image and the feature extraction techniques are applied on that image. The Support Vector Machine classifier is used to classify the plant leaf disease types. Here in this paper we implement the deep learning and machine learning approach for identification of plat leaf disease and we found that deep learning apporch using Bidrectional CNN gives the better performace in term of accuracy Index Term:-svm,cnn,opencv,plant leaf disease,image processing
The digital world continues to witness an unprecedented growth in view of the technological advan... more The digital world continues to witness an unprecedented growth in view of the technological advancements in the field of Digital Signal Processing (DSP). The increased usage of digital applications along with the tremendous evolution of Very Large Scale Integration (VLSI) technology over a few epochs has led to the development of enhanced algorithms and architectures for DSP systems that augur to meet the demands of a wide variety of applications in this expanding horizon of the signal processing sector. Finite Impulse Response (FIR) digital filter is the most potent and frequently used component in various signal processing and image processing applications. Since the intricacy of implementation grows with the filter order and the precision of computation, real-time realization of these filters with desired level of accuracy and less area-delay-power complexity is a challenging task. consumption is low. FPGA is a semiconductor device containing programmable logic components and programmable interconnects.
Early plant leaf disease detection is a major challenge in agriculture field. The easiest way, to... more Early plant leaf disease detection is a major challenge in agriculture field. The easiest way, to control the plant leaf disease infection is an Challenging task. But the excessive use of plant leaf disease are harmful to plants, animals as well as human beings. Integrated plant leaf disease management combines biological and physical methods to prevent plant leaf disease infection. The techniques of machine vision and digital image Processing are extensively applied to agricultural science and it have great perspective especially in the plant protection field, which ultimately leads to plant leaf management. This paper deals with a new type of early detection of plant leaf diseases system. Images of the leaves affected by plant leaf diseases are acquired by using a digital camera. The leaves with plant leaf disease images are processed for getting a gray colored image and then using feature extraction, image classification techniques to detect plant leaf diseases on leaves. The images are acquired by using a digital camera. The images are then transferred to a PC and represented in python software. The RGB image is then converted into gray scale image and the feature extraction techniques are applied on that image. The Support Vector Machine classifier is used to classify the plant leaf disease types. Here in this paper we implement the deep learning and machine learning approach for identification of plat leaf disease and we found that deep learning approach using Bi-directional CNN gives the better performance in terms of accuracy.
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