Timely availability of expert support to the farmers for appropriate decision-making on ‘whether and what pest management option is required’ is imperative for effective Integrated Pest Management (IPM). For several decades Economic Threshold Level (ETL) has been the basis for decision-making but in modern IPM emphasis is given on agro-ecological situation wherein IPM decisions are based on large range of pest relevant information such as crop health, natural enemies, weather etc. beside pest incidence scientifically obtained through farmers’ field scouting. But large farming community in India can rather obtain the tentative information of this kind, consisting uncertainties. Bayesian Network (BN),anartificial intelligence approach could help in developing technique/model to deal with tentative pest relevant information which can be used in field scouting based IPM Decision Support Systems (DSSs) to automate the process of advising appropriate pest management option to the farmers on the basis of tentative agroecological situation of their fields.
“Integrated pest management (IPM) is a strategy that draws on a range of management tools with the goal of using the least ecologically disruptive techniques to manage pests within economically acceptable levels.”
IPM is based on taking preventive measures, the site for the level of the pest(s), assessing the potential for pest damage, and choosing appropriate actions. Many different tactics may be available, including cultural practices, biological control agents, pesticides, pest-resistant varieties, mechanical methods and physical barriers. In IPM, these tactics may be combined into a plan that best suits the particular situation. It is a comprehensive approach dedicated to removing causes rather than just treating symptoms.
“Integrated pest management (IPM) is a strategy that draws on a range of management tools with the goal of using the least ecologically disruptive techniques to manage pests within economically acceptable levels.”
IPM is based on taking preventive measures, the site for the level of the pest(s), assessing the potential for pest damage, and choosing appropriate actions. Many different tactics may be available, including cultural practices, biological control agents, pesticides, pest-resistant varieties, mechanical methods and physical barriers. In IPM, these tactics may be combined into a plan that best suits the particular situation. It is a comprehensive approach dedicated to removing causes rather than just treating symptoms.
Pest control refers to the regulation or management of a species defined as a pest, usually because it is perceived to be detrimental to a person's health, the ecology or the economy.
The principal objective of a pest control is to protect crops by maintaining the attack of the pests and diseases at an acceptable level.
There are various methods of pest control
they are basically non chemical methods and chemical methods
My presentation on Integrated Pest Management. I had made a try from my side to create it knowledgeful and tried to include qualitative content after studying many articals, research papers and other online websites.
Integrated Pest Management (IPM) by TS- Shiven R. TrambadiaSHIVENPATEL10
PLEASE LIKE | SHARE | FOLLOW me to get more science related presentations.
This presentation is on "Integrated Pest Management", in which I've included 1) What is IPM?, 2)History, 3)Principles and 4)Applications of IPM.
Note:- Any part (text, photo, picture, clip-art, video, images etc.) included in this presentation are mostly correct according to the author of this presentation. Moreover any part (text, photo, picture, clip-art, video, images etc.) of this presentation, if includes your / from your related resource, is just a matter of coincidence.
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.
Role of expert systems in agriculture and its
applications in efficient crop production and
protection technologies has been reviewed and
discussed in this paper. Different domains of
agriculture are highlighted where expert systems can
play an important role for an expert in transferring
expert-driven knowledge instantly at the level of
farmer’s field. This paper explores structure of an
expert system, role of expert system in agriculture
along with details of expert system developed in the
different field of agriculture and also possibilities of
designing, developing and implementation of an
expert system for agriculture would motivate
scientists and extension workers to investigate
possible applications for the benefit of entire
agricultural community.
Pest control refers to the regulation or management of a species defined as a pest, usually because it is perceived to be detrimental to a person's health, the ecology or the economy.
The principal objective of a pest control is to protect crops by maintaining the attack of the pests and diseases at an acceptable level.
There are various methods of pest control
they are basically non chemical methods and chemical methods
My presentation on Integrated Pest Management. I had made a try from my side to create it knowledgeful and tried to include qualitative content after studying many articals, research papers and other online websites.
Integrated Pest Management (IPM) by TS- Shiven R. TrambadiaSHIVENPATEL10
PLEASE LIKE | SHARE | FOLLOW me to get more science related presentations.
This presentation is on "Integrated Pest Management", in which I've included 1) What is IPM?, 2)History, 3)Principles and 4)Applications of IPM.
Note:- Any part (text, photo, picture, clip-art, video, images etc.) included in this presentation are mostly correct according to the author of this presentation. Moreover any part (text, photo, picture, clip-art, video, images etc.) of this presentation, if includes your / from your related resource, is just a matter of coincidence.
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.
Role of expert systems in agriculture and its
applications in efficient crop production and
protection technologies has been reviewed and
discussed in this paper. Different domains of
agriculture are highlighted where expert systems can
play an important role for an expert in transferring
expert-driven knowledge instantly at the level of
farmer’s field. This paper explores structure of an
expert system, role of expert system in agriculture
along with details of expert system developed in the
different field of agriculture and also possibilities of
designing, developing and implementation of an
expert system for agriculture would motivate
scientists and extension workers to investigate
possible applications for the benefit of entire
agricultural community.
Pesticide recommendation system for cotton crop diseases due to the climatic ...IJMREMJournal
Data mining is a process of extracting knowledge from a vast database using tools and techniques. Data
mining plays an important role in decision making on issues related to many real-time problems such as
business, education, agriculture etc. Data mining in agriculture helps the farmers to decide on crop yield ratio,
water resource management, pesticides management and fertilizer management. Nowadays, climatic change is
one of the challenging problems in agriculture which has a greater impact on productivity. Many
researchers have contributed in the field of agriculture data mining i) To predict crop productivity, ii) water
management, iii) air pollution using the naïve bias and decision tree algorithms. The Proposed work is to
predict the diseases due to Climatic changes and recommended pesticide for the disease. Decision tree
algorithm is used to develop a recommendation system which helps to the farmer in the usage of pesticide for
the incidence of crop diseases.
Abstract
Cotton is the important cash crop of Pakistan and a major source of foreign earnings. However cotton crop is
facing many problems, such as disease and pest attacks. One way to reduce losses caused by disease and pest
attack is the use integrated pest management (IPM) practices. Keeping in view the importance of this technique,
the present study analyzed the adoption of IPM along with estimation of risk involved in the adoption process.
To estimate the cotton yield, two types of production functions (one for adopter and other for non-adopters) were
estimated using the regression analysis. Then estimate of regression models was used further in risk analysis.
The results of non-adopters of IPM showed that cost of urea bags, cost of nitro-phosphate bags, cost of herbicide
and rainfall were -0.038, 0.00475, 0.301 and 0.164 respectively and all of these significant at 10 percent level.
For non-adopters of IPM the coefficient values of seed expenditure, temperature, humidity and spray cost were
0.0035, 0.026,-.0.00093 and 0.00027 respectively. The results of IPM adopters showed that coefficient of
temperature, seed expenditure, spray cost, urea cost and rainfall equal to 0.0305,0.100,0.0029,-.000213 and
0.894 respectively and significant at ten percent level. Coefficient values of cost of nitro-phosphate bags,
herbicide cost, humidity were 0.00035, 0.100.-0.000671 and -0.000445 respectively.
Keywords: Cotton, IPM, herbicide, evaluation, risk, Coefficient, Hyderabad.
Adoption of crop scheduling techniques in India for sugarcane and pomegranate
production has been disappointing. The challenge is to use state of the art technology to provide
practical and useful advice to farmers and further to convince farmers of the benefits of crop
scheduling by on-farm demonstration. The purpose of this project is to describe: 1. To expose the
system to the practical aspects of farming in order to refine it if necessary. 2. To evaluate the
accuracy of the system to predict crop growth and health. 3. A high technology system to provide
practical, real time cropping advice on climate situations. The system consists of a web-based
simulation model that estimates the recent, current and future crop status and yield from field
information and real time weather data. The system automatically generates and distributes simple
advice by SMS to farmers’ cellular phones. The system is evaluated on a small-scale sugarcane and
pomegranate scheme at Pandharpur, Maharashtra. Yields are not affected significantly and
profitability is enhanced considerably.
Crops diseases detection and solution systemIJECEIAES
The technology based modern agriculture industries are today’s requirement in every part of agriculture in Bangladesh. In this technology, the disease of plants is precisely controlled. Due to the variable atmospheric circumstances these conditions sometimes the farmer doesn’t know what type of disease on the plant and which type of medicine provide them to avoid diseases. This research developed for crops diseases detection and to provide solutions by using image processing techniques. We have used Android Studio to develop the system. The crops diseases detection and solution system is compared the image of affected crops with database of CDDASS (Crops Diseases Detection and Solution system). If CDDASS detect any disease symptom, then provide suggestion so that farmers can take proper decision to provide medicine to the affected crops. The application has developed with user friendly features so that farmers can use it easily.
The technology based modern agriculture industries are today‟s requirement in every part of agriculture in Bangladesh. In this technology, the disease of plants is precisely controlled. Due to the variable atmospheric circumstances these conditions sometimes the farmer doesn‟t know what type of disease on the plant and which type of medicine provide them to avoid diseases. This research developed for crops diseases detection and to provides solution by using image processing techniques. We have used Android Studio to develop the system. The crops diseases detection and solution system is compared the image of affected crops with database of CDDASS (Crops Diseases Detection and Solution system). If CDDASS detect any disease symptom, then provide suggestion so that farmers can take proper decision to provide medicine to the affected crops. The application has developed with user friendly features so that farmers can use it easily.
In the era of data-driven warfare, the integration of big data and machine learning (ML) techniques has
become paramount for enhancing defence capabilities. This research report delves into the applications of
big data and ML in the defence sector, exploring their potential to revolutionize intelligence gathering,
strategic decision-making, and operational efficiency. By leveraging vast amounts of data and advanced
algorithms, these technologies offer unprecedented opportunities for threat detection, predictive analysis,
and optimized resource allocation. However, their adoption also raises critical concerns regarding data
privacy, ethical implications, and the potential for misuse. This report aims to provide a comprehensive
understanding of the current state of big data and ML in defence, while examining the challenges and
ethical considerations that must be addressed to ensure responsible and effective implementation.
Cloud Computing, being one of the most recent innovative developments of the IT world, has been
instrumental not just to the success of SMEs but, through their productivity and innovative contribution to
the economy, has even made a remarkable contribution to the economic growth of the United States. To
this end, the study focuses on how cloud computing technology has impacted economic growth through
SMEs in the United States. Relevant literature connected to the variables of interest in this study was
reviewed, and secondary data was generated and utilized in the analysis section of this paper. The findings
of this paper revealed that there have been meaningful contributions that the usage of virtualization has
made in the commercial dealings of small firms in the United States, and this has also been reflected in the
economic growth of the country. This paper further revealed that as important as cloud-based software is,
some SMEs are still skeptical about how it can help improve their business and increase their bottom line
and hence have failed to adopt it. Apart from the SMEs, some notable large firms in different industries,
including information and educational services, have adopted cloud computing technology and hence
contributed to the economic growth of the United States. Lastly, findings from our inferential statistics
revealed that no discernible change has occurred in innovation between small and big businesses in the
adoption of cloud computing. Both categories of businesses adopt cloud computing in the same way, and
their contribution to the American economy has no significant difference in the usage of virtualization.
Energy-constrained Wireless Sensor Networks (WSNs) have garnered significant research interest in
recent years. Multiple-Input Multiple-Output (MIMO), or Cooperative MIMO, represents a specialized
application of MIMO technology within WSNs. This approach operates effectively, especially in
challenging and resource-constrained environments. By facilitating collaboration among sensor nodes,
Cooperative MIMO enhances reliability, coverage, and energy efficiency in WSN deployments.
Consequently, MIMO finds application in diverse WSN scenarios, spanning environmental monitoring,
industrial automation, and healthcare applications.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication. IJCSIT publishes original research papers and review papers, as well as auxiliary material such as: research papers, case studies, technical reports etc.
With growing, Car parking increases with the number of car users. With the increased use of smartphones
and their applications, users prefer mobile phone-based solutions. This paper proposes the Smart Parking
Management System (SPMS) that depends on Arduino parts, Android applications, and based on IoT. This
gave the client the ability to check available parking spaces and reserve a parking spot. IR sensors are
utilized to know if a car park space is allowed. Its area data are transmitted using the WI-FI module to the
server and are recovered by the mobile application which offers many options attractively and with no cost
to users and lets the user check reservation details. With IoT technology, the smart parking system can be
connected wirelessly to easily track available locations.
Welcome to AIRCC's International Journal of Computer Science and Information Technology (IJCSIT), your gateway to the latest advancements in the dynamic fields of Computer Science and Information Systems.
Computer-Assisted Language Learning (CALL) are computer-based tutoring systems that deal with
linguistic skills. Adding intelligence in such systems is mainly based on using Natural Language
Processing (NLP) tools to diagnose student errors, especially in language grammar. However, most such
systems do not consider the modeling of student competence in linguistic skills, especially for the Arabic
language. In this paper, we will deal with basic grammar concepts of the Arabic language taught for the
fourth grade of the elementary school in Egypt. This is through Arabic Grammar Trainer (AGTrainer)
which is an Intelligent CALL. The implemented system (AGTrainer) trains the students through different
questions that deal with the different concepts and have different difficulty levels. Constraint-based student
modeling (CBSM) technique is used as a short-term student model. CBSM is used to define in small grain
level the different grammar skills through the defined skill structures. The main contribution of this paper
is the hierarchal representation of the system's basic grammar skills as domain knowledge. That
representation is used as a mechanism for efficiently checking constraints to model the student knowledge
and diagnose the student errors and identify their cause. In addition, satisfying constraints and the number
of trails the student takes for answering each question and fuzzy logic decision system are used to
determine the student learning level for each lesson as a long-term model. The results of the evaluation
showed the system's effectiveness in learning in addition to the satisfaction of students and teachers with its
features and abilities.
In the realm of computer security, the importance of efficient and reliable user authentication methods has
become increasingly critical. This paper examines the potential of mouse movement dynamics as a
consistent metric for continuous authentication. By analysing user mouse movement patterns in two
contrasting gaming scenarios, "Team Fortress" and "Poly Bridge," we investigate the distinctive
behavioral patterns inherent in high-intensity and low-intensity UI interactions. The study extends beyond
conventional methodologies by employing a range of machine learning models. These models are carefully
selected to assess their effectiveness in capturing and interpreting the subtleties of user behavior as
reflected in their mouse movements. This multifaceted approach allows for a more nuanced and
comprehensive understanding of user interaction patterns. Our findings reveal that mouse movement
dynamics can serve as a reliable indicator for continuous user authentication. The diverse machine
learning models employed in this study demonstrate competent performance in user verification, marking
an improvement over previous methods used in this field. This research contributes to the ongoing efforts to
enhance computer security and highlights the potential of leveraging user behavior, specifically mouse
dynamics, in developing robust authentication systems.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Image segmentation and classification tasks in computer vision have proven to be highly effective using neural networks, specifically Convolutional Neural Networks (CNNs). These tasks have numerous
practical applications, such as in medical imaging, autonomous driving, and surveillance. CNNs are capable
of learning complex features directly from images and achieving outstanding performance across several
datasets. In this work, we have utilized three different datasets to investigate the efficacy of various preprocessing and classification techniques in accurssedately segmenting and classifying different structures
within the MRI and natural images. We have utilized both sample gradient and Canny Edge Detection
methods for pre-processing, and K-means clustering have been applied to segment the images. Image
augmentation improves the size and diversity of datasets for training the models for image classification
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
This research aims to further understanding in the field of continuous authentication using behavioural
biometrics. We are contributing a novel dataset that encompasses the gesture data of 15 users playing
Minecraft with a Samsung Tablet, each for a duration of 15 minutes. Utilizing this dataset, we employed
machine learning (ML) binary classifiers, being Random Forest (RF), K-Nearest Neighbors (KNN), and
Support Vector Classifier (SVC), to determine the authenticity of specific user actions. Our most robust
model was SVC, which achieved an average accuracy of approximately 90%, demonstrating that touch
dynamics can effectively distinguish users. However, further studies are needed to make it viable option
for authentication systems. You can access our dataset at the following
link:https://github.com/AuthenTech2023/authentech-repo
This paper discusses the capabilities and limitations of GPT-3 (0), a state-of-the-art language model, in the
context of text understanding. We begin by describing the architecture and training process of GPT-3, and
provide an overview of its impressive performance across a wide range of natural language processing
tasks, such as language translation, question-answering, and text completion. Throughout this research
project, a summarizing tool was also created to help us retrieve content from any types of document,
specifically IELTS (0) Reading Test data in this project. We also aimed to improve the accuracy of the
summarizing, as well as question-answering capabilities of GPT-3 (0) via long text
In the realm of computer security, the importance of efficient and reliable user authentication methods has
become increasingly critical. This paper examines the potential of mouse movement dynamics as a
consistent metric for continuous authentication. By analysing user mouse movement patterns in two
contrasting gaming scenarios, "Team Fortress" and "Poly Bridge," we investigate the distinctive
behavioral patterns inherent in high-intensity and low-intensity UI interactions. The study extends beyond
conventional methodologies by employing a range of machine learning models. These models are carefully
selected to assess their effectiveness in capturing and interpreting the subtleties of user behavior as
reflected in their mouse movements. This multifaceted approach allows for a more nuanced and
comprehensive understanding of user interaction patterns. Our findings reveal that mouse movement
dynamics can serve as a reliable indicator for continuous user authentication. The diverse machine
learning models employed in this study demonstrate competent performance in user verification, marking
an improvement over previous methods used in this field. This research contributes to the ongoing efforts to
enhance computer security and highlights the potential of leveraging user behavior, specifically mouse
dynamics, in developing robust authentication systems.
Image segmentation and classification tasks in computer vision have proven to be highly effective using neural networks, specifically Convolutional Neural Networks (CNNs). These tasks have numerous
practical applications, such as in medical imaging, autonomous driving, and surveillance. CNNs are capable
of learning complex features directly from images and achieving outstanding performance across several
datasets. In this work, we have utilized three different datasets to investigate the efficacy of various preprocessing and classification techniques in accurssedately segmenting and classifying different structures
within the MRI and natural images. We have utilized both sample gradient and Canny Edge Detection
methods for pre-processing, and K-means clustering have been applied to segment the images. Image
augmentation improves the size and diversity of datasets for training the models for image classification.
This work highlights transfer learning’s effectiveness in image classification using CNNs and VGG 16 that
provides insights into the selection of pre-trained models and hyper parameters for optimal performance.
We have proposed a comprehensive approach for image segmentation and classification, incorporating preprocessing techniques, the K-means algorithm for segmentation, and employing deep learning models such
as CNN and VGG 16 for classification.
The security of Electric Vehicle (EV) charging has gained momentum after the increase in the EV adoption
in the past few years. Mobile applications have been integrated into EV charging systems that mainly use a
cloud-based platform to host their services and data. Like many complex systems, cloud systems are
susceptible to cyberattacks if proper measures are not taken by the organization to secure them. In this
paper, we explore the security of key components in the EV charging infrastructure, including the mobile
application and its cloud service. We conducted an experiment that initiated a Man in the Middle attack
between an EV app and its cloud services. Our results showed that it is possible to launch attacks against
the connected infrastructure by taking advantage of vulnerabilities that may have substantial economic and
operational ramifications on the EV charging ecosystem. We conclude by providing mitigation suggestions
and future research directions.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
This paper describes the outcome of an attempt to implement the same transitive closure (TC) algorithm
for Apache MapReduce running on different Apache Hadoop distributions. Apache MapReduce is a
software framework used with Apache Hadoop, which has become the de facto standard platform for
processing and storing large amounts of data in a distributed computing environment. The research
presented here focuses on the variations observed among the results of an efficient iterative transitive
closure algorithm when run against different distributed environments. The results from these comparisons
were validated against the benchmark results from OYSTER, an open source Entity Resolution system. The
experiment results highlighted the inconsistencies that can occur when using the same codebase with
different implementations of Map Reduce.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Chapter 3 - Islamic Banking Products and Services.pptx
Decision Making in Integrated Pest Management and Bayesian Network
1. International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 2, April 2017
DOI:10.5121/ijcsit.2017.9203 31
DECISION MAKING IN INTEGRATED PEST
MANAGEMENT AND BAYESIAN NETWORK
Niranjan Singh and Neha Gupta
Faculty of Computer Application,ManavRachna International University,
Faridabad-121004, India
ABSTRACT
Timely availability of expert support to the farmers for appropriate decision-making on ‘whether and what
pest management option is required’ is imperative for effective Integrated Pest Management (IPM). For
several decades Economic Threshold Level (ETL) has been the basis for decision-making but in modern
IPM emphasis is given on agro-ecological situation wherein IPM decisions are based on large range of
pest relevant information such as crop health, natural enemies, weather etc. beside pest incidence
scientifically obtained through farmers’ field scouting. But large farming community in India can rather
obtain the tentative information of this kind, consisting uncertainties. Bayesian Network (BN),anartificial
intelligence approach could help in developing technique/model to deal with tentative pest relevant
information which can be used in field scouting based IPM Decision Support Systems (DSSs) to automate
the process of advising appropriate pest management option to the farmers on the basis of tentative agro-
ecological situation of their fields.
KEYWORDS
IPM, field scouting, decision-making, ETL, agro-ecological situation
1. INTRODUCTION
Excessive, injudicious and irrational use of chemical pesticide by the farmers for pest control
causes significant damage to the environment, human health and also negatively impacts the crop
production. There is a growing awareness world over on the need for promoting environmentally
sustainable agriculture practices. Integrated Pest Management is a globally accepted strategy for
promoting sustainable agriculture [10]. The IPM has been evolving over the decades to address
the negative impact of chemical pesticides on environment ultimately affecting the interests of the
farmers. The major goal of IPM is not to eradicate all pest populations but rather to accept a
tolerable pest density above the Economic Threshold Level[6]. For several decades ETL has been
the basis for IPM decision-making but in modern IPM emphasis is being given on field agro-
ecological situation where pest management decisions are based on larger range of field
observations such as crop health, natural enemies’ population, and weather etc. beside pest
information. Easy and timely availability of expert support on IPM decision-making is the biggest
problem faced by the farmers in India. ‘Whether and what pest management option is required’ is
the most important decision concern of the farmers. Many ICT based DSSs as web-based
applications are available in the country but most of them provide information about for pest
identification and management. Some initiatives have also been taken to provide ETL based
decision support to the farmers on ‘weather and what pest management option is required’ which
2. International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 2, April 2017
32
capture quantitative pest information scientifically obtained by trained pest scouts through regular
field scouting. But there are no DSSs to provide decision support to the farmers on ‘weather and
what pest management option is required’ on the basis of farmer’s field agro-ecological situation
neither there are techniques which can be used in these DSSs for selecting appropriate pest
management option on the basis of tentative agro-ecological information obtained by the farmers.
Large Indian farming community cannot scientifically observe such certain information rather
they may obtain tentative information. Hence, Bayesian Network is widely used in ecological
decision-making could be the suitable approach to develop expert technique/model for selecting
appropriate pest management option on the basis of tentative agro-ecological information
obtained from farmer fields. The technique thus developed can be used in field scouting based
DSSs to automate the process of providing field agro-ecological situation based pest management
advisories to the farmers.
2. DECISION-MAKING IN IPM
Decision-making is a mental process resulting in the selection of an action among several
alternative solutions. Every decision-making process produces a final choice [4].Decision-making
starts with the identification of a problem, which requires the collection of all relevant
information for critical analysis of the problem. This analysis leads to development of a set of
available alternative courses of actions to solve the problem; only realistic solutions should be
selected considering multiple criteria e.g. effectiveness, benefits, costs and the constraints e.g.
ease of implementation and technical or legislative constraints. Based on this analysis, the best
solution is selected, and the decision is converted into an action [9].
Decision-making in IPM is a dynamic and complex process (Fig. 1) which requires much more
knowledge and support than the conventional agriculture. The core of IPM framework is the
decision-making process. The first decision concerns pest identification and second decision
concerns ‘whether and what pest management option is required’. Regular field scouting is the
corner stone of the IPM. Whenever the decision maker notices any pest activity while scouting
the field, he needs to identify the pest and scientifically observe the exact pest and other relevant
information necessary for IPM decision-making. After the analyzing the information observed,
first decision to be made is whether pest management action is required and if so, what is the
most appropriate option; physical, biological or chemical, their doses, application methods,
Fig: 1 IPM Decision making
3. International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 2, April 2017
33
frequency etc. In IPM, sustainable biological, physical, and other non-chemical methods which
are safer to environment and human health are preferred to chemical methods [9].
ETL VS. AGRO-ECOLOGICAL SITUATION, BASIS FOR IPM DECISION-MAKING
ETL is an important concept for IPM which integrates biology and economics and uses
pesticides, or other management actions, only when economic loss in anticipated [6]. ETL is the
best known and widely used concept in making IPM decisions but here are many reasons for not
to use this method. One of the problems of the ETL is that it is based on parameters that are
changing all the time, and that are often not known. ETL is defined as the population density at
which control measures should be initiated against an increasing pest population to prevent
economic damage. It is expressed as insect numbers. It is calculated on the basis of management
cost per hectare, price of the farm produce/ kilogram and expected damage (kilogram/pest). So, it
is possible to estimate the pest management cost but is very difficult to know the farm produce
while crop is still growing. Similarly, pest damage too cannot be predicted as it depends upon
many factors: crop health, weather, presence of pest natural enemies etc.
Analysis of field agro-ecological situation considers large rage of pest relevant information such
as crop health, weather conditions and natural enemies’ population beside pest incidence thus is
more holistic approach than ETL. In agro-ecological situation based IPM, understanding the
intricate interactions in an ecosystem can play a critical role in pest management. Agro-ecological
situation based IPM results in more reduction of chemical pesticide usage and conserves the agro-
ecosystems in comparison to ETL based IPM. Farmers cannot base decisions on only a simple
pest count but have to consider many other aspects such as crop health, natural enemies and
weather condition etc. Hence, IPM specialists have realized the limitations of the ETL and
gradually shifted towards agro-ecological situation based IPM decision-making.
3. LIMITATIONS OF EXISTING FIELD SCOUTING BASED IPM DECISION
SUPPORT SYSTEMS
In spite of development and wide spread of ICT, still there are limitations to the use of DSSs in
IPM. One of the major limitation is that pest management DSSs do not adequately consider all
aspects of IPM. Most of the available DSSs address only specific aspect of IPM. Several DSSs
require too much time to use because of delays in data processing or tedious and input
requirements whereas pest is very dynamic specie and can cause significant crop losses if not
managed timely. For effective and successful IPM, farmer need easy and timely access to the
knowledge or expertise so as to make appropriate decision as per his field situation.
Most of the IPM DSSs have been built to provide support on pest identification and their
management. Only few DSSs are available andthese too provide real-time decision support to the
farmers on the basis of pest situation in their fields ‘whether pest incidence level has reached near
ETL or crossed ETL’. These DSS scapture the quantitative pest incidence information
scientifically obtained by trained pest scouts through regular scouting of farmer fields and
produce ETL based pest reports to the experts so as to select appropriate pest management option
to be advised to the farmers. Whereas in modern IPM the basis of IPM decision making has
changed to field agro-ecological situation instead of pest ETL which requires large range of
certain pest relevant information scientifically obtained from farmer fields through regular field
4. International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 2, April 2017
34
scouting. But regular scientific observation of such information form farmer fields require large
number of trained manpower which is a difficult and costly proposition for state plant protection
agencies. So, can the farmers themselves do the filed scouting? They can, but large farming
community is not able to scientifically observe such information rather they can obtain tentative
information which consists lot of uncertainty. But there are no techniques available which can be
used in field scouting based DSSs to select appropriate pest management option on the basis of
tentative pest relevant information to be advised to the farmers.
4. BAYESIAN NETWORK
Bayesian Network is a key computer technology for dealing with probabilities in Artificial
Intelligence. BN is one of the most effective theoretical models for uncertain knowledge
expression and reasoning [1]. Probabilistic reasoning approaches such as Bayesian network [7]
can be useful to develop technique for selecting appropriate pest management option on the basis
of uncertain or inexact pest and other relevant information obtained through scouting of farmer
fields. It was found through the literature review, that there have been very little efforts to use BN
for pest management decision-making specifically for “whether and what pest management
option is required’ on the basis of tentative agro ecological situation of farmer fields. BN can be
of great use in developing technique to better deal with this kind of tentative information obtained
by farmers from their fields for selecting appropriate pest management option.
BN graphical model that represents a set of random variables and their conditional dependencies
via anAcyclic Directed Graph (ADG). Because a Bayesian network is a complete model for the
variables and their relationships, it can be used to answer probabilistic queries about them.
Formally, a BN is a pair (G; P) where
G = (V; E) is a directed acyclic graph whose set of nodes V = {X1, X2, ………Xn} represents
the system variables and whose set of arcs E represents direct dependence relationships among
the variables, and
P is a set of conditional probability distributions containing a conditional probability distribution
P (Xi/pa (Xi)) for each variable X given the set of parents pa (Xi) in the graph.
The joint probability distribution over V can be recovered from this set P of conditional
probability distributions applying the chain rule as:
n
P(X1, ……,Xn)=∏P (Xi/pa (Xi))
i
The process of obtaining the graph and the probabilities of a BN can be done either manually,
from experts’ knowledge on the domain, or automatically, from databases [3].
BN that can represent and solve decision problems under uncertainty are called BDN. It is a
generalization of a Bayesian network, in which not only probabilistic inference problems but
also decision making problems can be modeled and solved. BN only contain chance nodes, each
representing a random variable, while BDN also contain decision nodes representing the options
available to decision makers and utility nodes representing the decision makers’ preferences. Arcs
5. International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 2, April 2017
coming into decision nodes represent the information that will be available when the decision is
made. Arcs coming into chance nodes represents probabilistic dependence.
BN has been effectively used in ecological decision making
and techniques keep increasing BN’S abilities and range of practical applications
Nevertheless, there are very few experiences of its usage in pest management
5. CONCEPTUAL BAYESIAN
5.1 Problem Description
So the major decision concern of the farmers related to IPM is
management option to apply on the basis of
Whenever he notices any pest activity,
information about crop condition, level of pest incidence, natural enemies and weather
from his field.
Crop condition is measured in terms of its phenology. The level of pest incidence, presence of
natural enemies and weather condition are important to estimate the intensity of the attack
crop condition, along with the intensi
plant health treatment or not and if yes then what is the correct IPM option.
conditional relationship among these agro ecological factors, a
built for selection of appropriate pest management option.
5.2 Model Structure& Parameterization
The construction of BN model structure included: identifying the important variables and
establishing the links between variables.
experts, BN model for agro ecological situation based IPM decision making was constructed.
prominent variables (nodes) of interest
presence of natural enemies, weather conditions,
Level of pest incidence, natural enemies and weather are the parent nodes of pest intensity and
pest intensity and crop health are the parent nodes for IPM option.
model for field agro ecological situation based
model represent the variables, with their causal relations depicted by black arrows.
.
International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 2, April 2017
coming into decision nodes represent the information that will be available when the decision is
nodes represents probabilistic dependence.
BN has been effectively used in ecological decision making [8]. New computational methods
and techniques keep increasing BN’S abilities and range of practical applications
are very few experiences of its usage in pest management [2].
AYESIAN NETWORK MODEL FOR IPM DECISION
major decision concern of the farmers related to IPM is to decide whether and what pest
on the basis of tentative agro ecological situation of his field
ever he notices any pest activity, he needs to notes down the date of obser
crop condition, level of pest incidence, natural enemies and weather
Crop condition is measured in terms of its phenology. The level of pest incidence, presence of
natural enemies and weather condition are important to estimate the intensity of the attack
crop condition, along with the intensity of pest attack, determines whether there is need to apply
plant health treatment or not and if yes then what is the correct IPM option. So
conditional relationship among these agro ecological factors, a conceptual BN model
appropriate pest management option.
Model Structure& Parameterization
The construction of BN model structure included: identifying the important variables and
establishing the links between variables. Based on knowledge elicited from literature and domain
BN model for agro ecological situation based IPM decision making was constructed.
prominent variables (nodes) of interest were identified in this case; level of pest incidence,
presence of natural enemies, weather conditions, crop health, pest intensity and IPM options.
Level of pest incidence, natural enemies and weather are the parent nodes of pest intensity and
pest intensity and crop health are the parent nodes for IPM option. Figure 2 shows the Bayesian
for field agro ecological situation based IPM decision making. The nodes in the BN
model represent the variables, with their causal relations depicted by black arrows.
International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 2, April 2017
35
coming into decision nodes represent the information that will be available when the decision is
. New computational methods
and techniques keep increasing BN’S abilities and range of practical applications [5].
ECISION-MAKING
to decide whether and what pest
agro ecological situation of his field.
notes down the date of observation,
crop condition, level of pest incidence, natural enemies and weather condition
Crop condition is measured in terms of its phenology. The level of pest incidence, presence of
natural enemies and weather condition are important to estimate the intensity of the attack The
whether there is need to apply
So by using the
BN model has been
The construction of BN model structure included: identifying the important variables and
ature and domain
BN model for agro ecological situation based IPM decision making was constructed. Six
level of pest incidence,
crop health, pest intensity and IPM options.
Level of pest incidence, natural enemies and weather are the parent nodes of pest intensity and
shows the Bayesian
The nodes in the BN
model represent the variables, with their causal relations depicted by black arrows.
6. International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 2, April 2017
36
To keep the BN model for IPM decision making as simple as possible, each node was
discretized into necessary states only. The definition of these states was performed
through literature review and expert consultation. In the model—Crop Health (CH) and
Natural Enemies (NE) nodes are binary and other are ordered value. The conditional probabilities
of these nodes are estimated basedon the data records available with public research institution, to
keep the size of the CPs manageable, each node have been assigned the fewest number of states
necessary.
6. IMPLEMENTATION OF BAYESIAN NETWORK MODEL FOR IPM DECISION
SUPPORT
CPTs for conceptual BN model were approximated. Actual CPTs could be defined based on data
analysis of the records available for agro ecological regions or on the basis of expert knowledge
and subsequently the model is evaluated. Model evaluation helps ensure the model’s interactions
and outcomes are feasible. The model can be tested by applying different agro ecological
scenarios (i.e. combinations of inputs) and examining whether the resulting probabilities are
reasonable and logical. Ideally, the accuracy of the model should be tested with empirical data,
but in many studies that use BNs these data are not available, at least not voluminously[11].
Once model is evaluated, input obtained from farmers for level of pest incidence, natural
enemies, and weather and crop health be propagated to the model for PA, NE, weather and CH
nodes, which changes the CP of PM node. CP of PM node would be deciding the pest
management option to be applied in the farmers filed. Higher CP for PM node will lead to
selection of stronger IPM option application and for moderate CP, milder IPM option be selected.
If CP for PM node is very low than, there is no need for application of any pest treatment. The
model thus validated could be used in IPM DSSs for selecting appropriate pest management
option to be advised to the farmers on the basis of tentative agro ecological information provided
by as model input.
7. CONCLUSION
Many DDSs have been developed for IPM by private and public organizations in the country but
for extension workers only few for farmers. Most of these DSSs are either web database or
information systems which provides information particularly on pest identification and
management. Little efforts have been made to develop field scouting based DSSs to provide real-
time decision support to the farmers. Even those few available field scouting based DSSs use pest
ETL as the basis for decision-making capturing quantitative pest incidence information only
instead of field agro-ecological situation, more holistic approach. But agro ecological information
obtained by the farmers form their field is tentative and contains uncertainties. Bayesian network
has unique advantage in dealing with uncerta in information. In following study, we found that
use of Bayesian networks will be perfect approach to develop technique/model for selecting
appropriate pest management option on the basis of tentative agro-ecological information
obtained by the farmers through field scouting. Subsequently the technique thus developed can be
used in field scouting based IPM DSSs to automate the process of decision support to the farmers.
7. International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 2, April 2017
37
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