This presentation due the workshop at faculty of agriculture - Suss Canal University organized by scientific research group in Egypt (SRGE) on Tuesday 8 April 214
Identification of Race/strain of Phytopathogenic Fungi through Conventional A...Sarda Konjengbam
Detection and identification of fungi has relied on a combination of microscopy and culture based techniques. Conventional methods often rely on identification of disease symptoms, isolation and culturing of environmental organisms, and laboratory identification by morphology and biochemical tests. These methods, although the cornerstone of fungal diagnostics, can lead to problems in identification, resulting in incorrect interpretation, diagnosis and ultimately treatment. The methods rely on experienced, skilled laboratory staff, the ability of the organism to be cultured, are time consuming, non quantitative, prone to contamination and error and often delay management (Atkins and Clark, 2004). During the last decades, the advent of molecular biology promised to offer radical alternatives in the detection and enumeration of fungal pathogens. Molecular technology increases understanding of the biology and population structures of plant pathogens, provides quick and accurate answers to epidemiological questions about plant diseases, and supports disease management decisions. New, rapid screening methods are being developed and increasingly used in all aspects of fungal diagnostics.
Identification of Race/strain of Phytopathogenic Fungi through Conventional A...Sarda Konjengbam
Detection and identification of fungi has relied on a combination of microscopy and culture based techniques. Conventional methods often rely on identification of disease symptoms, isolation and culturing of environmental organisms, and laboratory identification by morphology and biochemical tests. These methods, although the cornerstone of fungal diagnostics, can lead to problems in identification, resulting in incorrect interpretation, diagnosis and ultimately treatment. The methods rely on experienced, skilled laboratory staff, the ability of the organism to be cultured, are time consuming, non quantitative, prone to contamination and error and often delay management (Atkins and Clark, 2004). During the last decades, the advent of molecular biology promised to offer radical alternatives in the detection and enumeration of fungal pathogens. Molecular technology increases understanding of the biology and population structures of plant pathogens, provides quick and accurate answers to epidemiological questions about plant diseases, and supports disease management decisions. New, rapid screening methods are being developed and increasingly used in all aspects of fungal diagnostics.
This Presentation includes various tactics of IDM like Cultural control, Physical control, Chemical control, Biological control of plant disease. Useful for UG, PG Botany and Agriculture students
Integrated disease management in organic
farming combines the use of various measures. The
usefulness of certain measures depends on the specific
crop-pathogen combination. In many crops,
preventative measures can control diseases without
the need of plant protection products. However, for
certain disease problems, preventative measures are
not sufficient. For example, organic apple production
strongly depends on the multiple use plant protection
products
M.Sc. (Master's) Seminar on topic "Role of chemicals in plant disease managem...Harshvardhan Gaikwad
The importance and role of chemicals/ fungicides in plant disease management is the major objective of plant pathology. The need based, effective, ecofriendly application of chemical fungicides can leads sustainable agriculture and food production.
cotton crop needs highest pesticide application for pest management, So we came with ipm practices for reducing insecticide spray, to manage the resistance development and secondary outbreak of sucking pest
FUNGICIDES COMPATIABILITY WITH AGRO-CHEMICALSsubhashB10
In this presentation you will come to learn (or) you will learn about the different types of fungicides and its application towards plants in the Sevier infestation of the plant diseases in an particular crop. and also you will come to learn about the different AGRO-CHEMICALS used for eradication of the particular plant diseases. and also you will come to know about the different FUNGICIDES mixtures & AGRO-CHEMICAL mixtures used for curing an particular plant disease or an diseases as a whole.
Eco friendly management of fungal seed borne pathogens through bio-agentsAnkit Chaudhari
Seed borne diseases causes heavy losses in the crops at all stages of growth like seed germination, seedling and maturity of plants.
Bio-control technologies have gained momentum in disease control of crop plants, in recent times as these technologies not only minimize or replace the usage of harmful chemical pesticides, but also found to be ecofriendly, environmentally safe, cheaper and efficient in certain disease control programmes.
Fungal bio-control agents like Trichoderma spp. successfully used for the control of many seed borne diseases caused by Aspergillus spp., Alternaria spp., Curvularia spp., Colletotrichum spp., Fusarium spp., Pyricularia spp., Helminthosporium spp. etc. in several crops.
A study on real time plant disease diagonsis systemIJARIIT
We aim to develop a real time application to the farmers for managing crop diseases. However, disease detection requires
continuous monitoring of experts which might be prohibitively expensive in large farms area. Automatic detection of plant diseases
is an essential research topic as it may prove benefits in monitoring large fields of crops and thus automatically detect the symptoms
of diseases as soon as they appear on plant leaves. Regarding plant disease diagnosis methodologies to detect diseases on crops,
image processing in disease diagnosis and eAGROBOT was studied. This paper is aiming to all are collectively used and formed
semi real time system for a disease diagnosis which uses image processing and data mining concepts to give pesticide
recommendation and pesticide cost estimation system. Thus the android application makes a good foundation for following effective
characteristic parameters for the disease diagnoses and setting up recommender system. The system is to be designed and developed
using Android studio as front-end software and SQLite as back-end software. The pictures and remedial measures of the diseases
were stored in the database and can be retrieved whenever necessary. The challenge is to make the farmers listen to the crop disease
diagnosis system and to get the advice related to the crop diseases. The constraint here is to develop the expert in local languages so
that farmers can operate the ES by themselves and get expert advice from the system.
This Presentation includes various tactics of IDM like Cultural control, Physical control, Chemical control, Biological control of plant disease. Useful for UG, PG Botany and Agriculture students
Integrated disease management in organic
farming combines the use of various measures. The
usefulness of certain measures depends on the specific
crop-pathogen combination. In many crops,
preventative measures can control diseases without
the need of plant protection products. However, for
certain disease problems, preventative measures are
not sufficient. For example, organic apple production
strongly depends on the multiple use plant protection
products
M.Sc. (Master's) Seminar on topic "Role of chemicals in plant disease managem...Harshvardhan Gaikwad
The importance and role of chemicals/ fungicides in plant disease management is the major objective of plant pathology. The need based, effective, ecofriendly application of chemical fungicides can leads sustainable agriculture and food production.
cotton crop needs highest pesticide application for pest management, So we came with ipm practices for reducing insecticide spray, to manage the resistance development and secondary outbreak of sucking pest
FUNGICIDES COMPATIABILITY WITH AGRO-CHEMICALSsubhashB10
In this presentation you will come to learn (or) you will learn about the different types of fungicides and its application towards plants in the Sevier infestation of the plant diseases in an particular crop. and also you will come to learn about the different AGRO-CHEMICALS used for eradication of the particular plant diseases. and also you will come to know about the different FUNGICIDES mixtures & AGRO-CHEMICAL mixtures used for curing an particular plant disease or an diseases as a whole.
Eco friendly management of fungal seed borne pathogens through bio-agentsAnkit Chaudhari
Seed borne diseases causes heavy losses in the crops at all stages of growth like seed germination, seedling and maturity of plants.
Bio-control technologies have gained momentum in disease control of crop plants, in recent times as these technologies not only minimize or replace the usage of harmful chemical pesticides, but also found to be ecofriendly, environmentally safe, cheaper and efficient in certain disease control programmes.
Fungal bio-control agents like Trichoderma spp. successfully used for the control of many seed borne diseases caused by Aspergillus spp., Alternaria spp., Curvularia spp., Colletotrichum spp., Fusarium spp., Pyricularia spp., Helminthosporium spp. etc. in several crops.
A study on real time plant disease diagonsis systemIJARIIT
We aim to develop a real time application to the farmers for managing crop diseases. However, disease detection requires
continuous monitoring of experts which might be prohibitively expensive in large farms area. Automatic detection of plant diseases
is an essential research topic as it may prove benefits in monitoring large fields of crops and thus automatically detect the symptoms
of diseases as soon as they appear on plant leaves. Regarding plant disease diagnosis methodologies to detect diseases on crops,
image processing in disease diagnosis and eAGROBOT was studied. This paper is aiming to all are collectively used and formed
semi real time system for a disease diagnosis which uses image processing and data mining concepts to give pesticide
recommendation and pesticide cost estimation system. Thus the android application makes a good foundation for following effective
characteristic parameters for the disease diagnoses and setting up recommender system. The system is to be designed and developed
using Android studio as front-end software and SQLite as back-end software. The pictures and remedial measures of the diseases
were stored in the database and can be retrieved whenever necessary. The challenge is to make the farmers listen to the crop disease
diagnosis system and to get the advice related to the crop diseases. The constraint here is to develop the expert in local languages so
that farmers can operate the ES by themselves and get expert advice from the system.
Analysis and prediction of seed quality using machine learning IJECEIAES
The mainstay of the economy has always been agriculture, and the majority of tasks are still carried out without the use of modern technology. Currently, the ability of human intelligence to forecast seed quality is used. Because it lacks a validation method, the existing seed prediction analysis is ineffective. Here, we have tried to create a prediction model that uses machine learning algorithms to forecast seed quality, leading to high crop yield and high-quality harvests. For precise seed categorization, this model was created using convolutional neural networks and trained using the seed dataset. Using data that can be used to forecast the future, this model is used to learn about whether the seeds are of premium quality, standard quality, or regular quality. While testing data are employed in the algorithm’s predictive analytics, training data and validation data are used for categorization reasons. Thus, by examining the training accuracy of the convolution neural network (CNN) model and the prediction accuracy of the algorithm, the project’s primary goal is to develop the best method for the more accurate prediction of seed quality.
Livestock are farm animals who are raised to generate profit. They are used for the commodities such as meat, eggs, milk, fur, leather and wool. Livestock animals usually distribute in remote areas, with relatively poor condition of disease diagnosis. Generally, it is difficult to carry out disease diagnosis rapidly and accurately.
Livestock diseases often pose a risk to public health and even affects the economy at large extent as we are quite dependent on the essential commodities we procure from the livestock. It is necessary to detect the disease outcome in the livestock to take the precautionary measures in order to avoid spread amongst them. So, there is a need for a system which can help in predicting the diseases among livestock on the basis of symptoms and suggest the precautionary measures to be taken with respect to the disease predicted. Our proposed system will predict the livestock (Cow, Sheep and Goat) disease using SVC (Support Vector Classifier) multi-class classification algorithm based on the symptoms and also provide the precautionary measures on the basis of disease predicted. There are some diseases which can prove to be fatal. So, our system will also alert the livestock owner if the predicted disease may cause a sudden death.
This research paper introduces a novel application for predicting plant diseases in cotton and potato plants using Convolutional Neural Networks (CNNs).
Separate CNN models were trained on labeled datasets of cotton and potato leaves, each associated with their respective diseases. The primary goal is to employ a fusion of two standard CNN systems to detect various diseases in cotton and potato plants.
Given India's heavy reliance on agriculture, this innovation is crucial to address challenges faced by the sector, including technological limitations, limited access to credit and markets, and the impact of climate change.
Cotton and potatoes are significant crops; this research paper are susceptible to various diseases that can impede their growth and result in substantial yield losses.
The conventional disease detection methods involve manual inspection and disease prognosis, which are time consuming and less accurate. The research showcases the effectiveness of the automated plant disease detection system, with two best models achieving impressive accuracies of 97.10% and 96.94% for cotton and potato plants, respectively.
These results offer promising insights for potential applications in crop management, benefiting the agricultural sector and contributing to increased productivity and profitability.
Similar to Applications of information technology in agriculture ws ns for environmental monitoring-y. m. awad 2014-408 (20)
هذة المحاضرة تناقش العوالم الافتراضية فى التعليم واهمية الذكاء الاصطناعى والتوأم الرقمى والإستفادة من العلوم المختلفة فى بيئة الميتافيرس وتقنيات عالم الميتافيرس فى التعليم وتم القائها فى المؤتمر الدولى للتعليم الابداعى والتحول الرقمى فى التعليم بجامعة الكويت الدولية يوم 13 نوفمبر 2022
الذكاء الأصطناعى المسؤول ومستقبل الأمن المناخى وانعكاساته الاجتماعية والأمنيةAboul Ella Hassanien
تحت رعاية الاستاذ الدكتور / محمود صقر رئيس اكاديمية البحث العلمي و إشراف الأستاذ الدكتور/ أحمد جبر المشرف علي المجالس النوعية ورئاسة الاستاذ الدكتور / احمد الشربيني مقرر مجلس بحوث الاتصالات وتكنولوجيا المعلومات تم تنظيم ورشة عمل اليوم 7 نوفمبر بمقر اكاديمية البحث العلمي عن " دور الذكاء الاصطناعي وانترنت الاشياء في مكافحة التغيرات المناخية" وذلك بمناسبة انعقاد مؤتمر الاطراف للتغيرات المناخية COP27 والمنعقد بمدينة شرم الشيخ. وقد عرض المتحدثون وهم الاستاذ الدكتو. / ابو العلا حسانين عضو المجلس والاستاذ الدكتور / اشرف درويش عضو المجلس والدكتورة لبني ابو المجد دور وتطبيقات الذكاء الاصطناعي وانترنت الاشياء في مجالات متعددة ومرتبطة بالتغيرات المناخية منها الزراعة ، الطاقة، الصحة , الاقتصاد الاخضر ، النقل والمواصلات والتخطيط العمراني من اجل الحد من التاثيرات المناخية والتي تهدف الي تقليل نسب انبعاث غازات الاحتباس الحراري والتكيف مع التغيرات المناخية. امتدت ورشة العمل لاكثر من ثلاث ساعات. وشارك عدد كبير من الحضور من الجامعات والمراكز البحثية المختلفة ووسائل الاعلام. كما شارك بالحضور معالي الاستاذ الدكتور / عصام شرف رئيس وزراء مصر الاسبق. وفي نهاية ورشة العمل استعرض الاستاذ الدكتور الشربيني النتائج والتوصيات العامة لورشة العمل والتي بدورها تدعو الي تعزيز دور التكنولوجيا البازغة في مكافحة التغيرات المناخية.
الذكاء الأصطناعى المسؤول ومستقبل الأمن المناخى وانعكاساته الاجتماعية والأمنيةAboul Ella Hassanien
تحت رعاية الاستاذ الدكتور محمود صقر رئيس اكاديمية البحث العلمى والتكنولوجيا وإشراف الاستاذ الدكتور احمد جبر المشرف على المجالس النوعية ينظم مجلس تكنولوجيا المعلومات والاتصالات بالاكاديمية ندوة بعنوان "الذكاء الأصطناعى ومستقبل الأمن المناخى" يوم الاثنين الموافق 7 نوفمبر 2022 باكاديمية البحث العلمى بشارع القصر العينى وتناقش الندوة عدد من المحاور اهمها المخاطر الأمنية المتعلقة بالمناخ وتاثيرات التغير المناخى على الأمن العام و التهديدات المتصاعدة للأمن القومي والعلاقة بين التغير المناخى والموارد الطبيعية والامن الانسانى والتاثيرات المجتمعية بالاضافة الى الاثار المتتالية لتأثيرات تغير المناخ على الأمن الغذائي وأمن الطاقة والامن الإجتماعى والانسانى والذكاء الأصطناعى المسؤول ومستقبل الأمن المناخى وانعكاساته الاجتماعية والانسانية والأمنية ومحور الذكاء الاصطناعي وتعزيزإستراتيجية العمل المناخي.
تحت رعاية
الأستاذ الدكتور محمد الخشت رئيس جامعة القاهرة
كلية التجارة-جامعة القاهرة
دور الذكاء الاصطناعي فى دعم الإقتصاد الأخضر لمواجهة التغيرات المناخية
الإستخدام المسؤول للذكاء الإصطناعى فى سياق تغيرالمناخ خارطة طريق فى عال...Aboul Ella Hassanien
تحت رعاية
الأستاذ الدكتور محمد الخشت رئيس جامعة القاهرة
الأستاذ الدكتور محمد سامي - نائب رئيس الجامعة لشئون خدمة المجتمع والبيئة - جامعة القاهرة
الاستاذ الدكتور رضا عبد الوهاب – عميد كلية الحاسبات والذكاء الإصطناعى – جامعة القاهرة
ويبينار بعنوان
الإستخدام المسؤول للذكاء الإصطناعى
فى سياق تغيرالمناخ
خارطة طريق فى عالم شديد التحديات والإضطرابات
الذكاء الإصطناعي والتغيرات المناخية والبيئية:الفرص والتحديات والأدوات السياسيةAboul Ella Hassanien
تحت رعاية الأستاذ الدكتور محمد الخشت رئيس جامعة القاهرة و الأستاذ الدكتور محمد سامي - نائب رئيس الجامعة لشئون خدمة المجتمع والبيئة - جامعة القاهرة ويبينار بعنزان الذكاء الإصطناعي والتغيرات المناخية والبيئية:الفرص والتحديات والأدوات السياسية
تنظم كلية الحاسبات والذكاء الاصطناعى - جامعة دمياط ويبينار بعنون الذكاء الاصطناعى:أسلحة لاتنام وأفاق لاتنتهى يحاضر فيها الاستاذ الدكتور ابوالعلا عطيفى حسنين الاستاذ بكلية الحاسبات والذكاء الاصطناعى - جامعة القاهرة ومؤسس ورئيس المدرسة العلمية البحثية المصرية وذلك يوم الثلاثاء الموافق 26 ابريل الساعة العاشرة مساء على منصة زووم ويناقش فيها مفهوم الطائرات بدون طيار وتطبيقاتها التجارية والمدنية والعسكرية والامن السيبرانى المعزز بالذكاء الاصطناعى ومفهوم الجيوش الالكترونية وعرض بعض النقاط البحثية فى علوم الطيارات بدون طيار المعزز بتقنيات الذكاء الاصطناعى و التؤمة الرقمية ---
ويبينا بالتعاون مع كلية العلوم الادارية - جامعة الكويت بعنوان اقتصاد ميتافيرس - يوم الاربعاء الموافق 20 ابريل 2022 وتناقش العوالم الافتراضية والاقتصاد الافتراضى
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
3. Agenda
Introduction
Plant Diseases
The cost
The solution
Computer-based Detection
Machine Learning Tech.
Expert System
Remote Sensing
WSN
Conclusions
4. Introduction
UN’s Food and Agriculture Organization (FAO)
admitted that food insecurity continues to be a major
development problem across the globe*. This problem
usually affects to developing countries.
*http://www.libelium.com/es/food_sustainability_monitoring_sensor_network/
6. Plant Diseases
Plant diseases have turned into a
dilemma as it can cause significant
reduction in both quality and quantity of
agricultural products.
The naked eye observation of experts is
the main approach adopted in practice
for detection and identification of plant
diseases
11. Computer-based Detection
Machine Learning Tech.
Usually, Machine learning techniques are the first
choice. The recent researches provide clues on their
ability to detect and to identify the plant diseases
in its early stages
12. Machine Learning Tech.
Al-Hiary, H., et al. "Fast and Accurate Detection and Classification of Plant Diseases." International Journal of Computer
Applications 17
13. Machine Learning Tech.
Al-Hiary, H., et al. "Fast and Accurate Detection and Classification of Plant Diseases." International Journal of Computer
Applications 17
14. Computer-based Detection
Machine Learning Tech.
An Indian researcher
used ML to establish
weather-based
prediction models of
plant diseases.
Kaundal, Rakesh, Amar S. Kapoor, and Gajendra PS Raghava. "Machine learning techniques in disease forecasting: a case study on rice blast
prediction." BMC bioinformatics 7.1 (2006): 485.
15. Computer-based Detection
Expert Systems
Expert systems have applications in many domains. They are mostly
suited in situations where the expert is not available.
In order to develop an expert system the knowledge has to be
extracted from domain expert.
16. Computer-based Detection
Expert Systems
An Indian researcher had
developed an Expert System for
diagnosis of diseases in Rice Plant
Sarma, Shikhar Kr, Kh Robindro Singh, and Abhijeet Singh. "An Expert System for diagnosis of diseases in Rice Plant." International Journal of Artificial
Intelligence 1.1 (2010): 26-31.
17. Computer-based Detection
Expert Systems
The rapid development of World Wide Web has
provided another way of using expert systems.
A Palestinian Researcher developed Dr. Wheat.
20. Computer-based Detection
Remote Sensing
Hyperspectral sensors onboard of satellites or on
AutoCopter to allow to continuously monitor the spatial
and temporal physiological and structural changes in a
plant production system
Remote sensing provides indications of the growth rate
at important development stages. This includes
detection of stress due to drought and nutrient
deficiency as well as a result of plant diseases or
animal pests.
24. Conclusion
Information systems and their related applications
give a new paradigm in the Agriculture field.
This helps in the early detection of common plant
diseases.