Analysis of data is an important task in data managements systems. Many mathematical tools are used in data analysis. A new division of data management has appeared in machine learning, linear algebra, an optimal tool to analyse and manipulate the data. Data science is a multi-disciplinary subject that uses scientific methods to process the structured and unstructured data to extract the knowledge by applying suitable algorithms and systems. The strength of linear algebra is ignored by the researchers due to the poor understanding. It powers major areas of Data Science including the hot fields of Natural Language Processing and Computer Vision. The data science enthusiasts finding the programming languages for data science are easy to analyze the big data rather than using mathematical tools like linear algebra. Linear algebra is a must-know subject in data science. It will open up possibilities of working and manipulating data. In this paper, some applications of Linear Algebra in Data Science are explained.
Here is a basic Linear Algebra review for the class of Machine Learning. This is actually becoming a new class in the mathematics of Intelligent Systems, there I will be teaching stuff in
1.- Linear Algebra - From the basics to the Cayley-Hamilton Theorem with applications
2.- Mathematical Analysis - from set to the Reimann Integral
3.- Topology - Mostly in Hilbert Spaces
4.- Optimization - Convex functions, KKT conditions, Duality Theory, etc.
The stuff is going to be interesting...
3. Linear Algebra for Machine Learning: Factorization and Linear TransformationsCeni Babaoglu, PhD
The seminar series will focus on the mathematical background needed for machine learning. The first set of the seminars will be on "Linear Algebra for Machine Learning". Here are the slides of the third part which is discussing factorization and linear transformations.
Here is the link of the first part which was discussing linear systems: https://www.slideshare.net/CeniBabaogluPhDinMat/linear-algebra-for-machine-learning-linear-systems/1
Here are the slides of the second part which was discussing basis and dimension:
https://www.slideshare.net/CeniBabaogluPhDinMat/2-linear-algebra-for-machine-learning-basis-and-dimension
These Slides are very usefull interms of engineering and as well as in other fields of Study .. These are Related with linear Algebra and there Properties Methods to find out the unknowns from the equation...
Here is a basic Linear Algebra review for the class of Machine Learning. This is actually becoming a new class in the mathematics of Intelligent Systems, there I will be teaching stuff in
1.- Linear Algebra - From the basics to the Cayley-Hamilton Theorem with applications
2.- Mathematical Analysis - from set to the Reimann Integral
3.- Topology - Mostly in Hilbert Spaces
4.- Optimization - Convex functions, KKT conditions, Duality Theory, etc.
The stuff is going to be interesting...
3. Linear Algebra for Machine Learning: Factorization and Linear TransformationsCeni Babaoglu, PhD
The seminar series will focus on the mathematical background needed for machine learning. The first set of the seminars will be on "Linear Algebra for Machine Learning". Here are the slides of the third part which is discussing factorization and linear transformations.
Here is the link of the first part which was discussing linear systems: https://www.slideshare.net/CeniBabaogluPhDinMat/linear-algebra-for-machine-learning-linear-systems/1
Here are the slides of the second part which was discussing basis and dimension:
https://www.slideshare.net/CeniBabaogluPhDinMat/2-linear-algebra-for-machine-learning-basis-and-dimension
These Slides are very usefull interms of engineering and as well as in other fields of Study .. These are Related with linear Algebra and there Properties Methods to find out the unknowns from the equation...
In mathematics, graph theory is the study of graphs, which are mathematical structures used to model pairwise relations between objects.Graph theory is also important in real life.
Feature Engineering in Machine LearningKnoldus Inc.
In this Knolx we are going to explore Data Preprocessing and Feature Engineering Techniques. We will also understand what is Feature Engineering and its importance in Machine Learning. How Feature Engineering can help in getting the best results from the algorithms.
Welcome to the Supervised Machine Learning and Data Sciences.
Algorithms for building models. Support Vector Machines.
Classification algorithm explanation and code in Python ( SVM ) .
Abstract: This PDSG workshop introduces basic concepts of simple linear regression in machine learning. Concepts covered are Slope of a Line, Loss Function, and Solving Simple Linear Regression Equation, with examples.
Level: Fundamental
Requirements: No prior programming or statistics knowledge required.
Linear Regression vs Logistic Regression | EdurekaEdureka!
YouTube: https://youtu.be/OCwZyYH14uw
** Data Science Certification using R: https://www.edureka.co/data-science **
This Edureka PPT on Linear Regression Vs Logistic Regression covers the basic concepts of linear and logistic models. The following topics are covered in this session:
Types of Machine Learning
Regression Vs Classification
What is Linear Regression?
What is Logistic Regression?
Linear Regression Use Case
Logistic Regression Use Case
Linear Regression Vs Logistic Regression
Blog Series: http://bit.ly/data-science-blogs
Data Science Training Playlist: http://bit.ly/data-science-playlist
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
In mathematics, graph theory is the study of graphs, which are mathematical structures used to model pairwise relations between objects.Graph theory is also important in real life.
Feature Engineering in Machine LearningKnoldus Inc.
In this Knolx we are going to explore Data Preprocessing and Feature Engineering Techniques. We will also understand what is Feature Engineering and its importance in Machine Learning. How Feature Engineering can help in getting the best results from the algorithms.
Welcome to the Supervised Machine Learning and Data Sciences.
Algorithms for building models. Support Vector Machines.
Classification algorithm explanation and code in Python ( SVM ) .
Abstract: This PDSG workshop introduces basic concepts of simple linear regression in machine learning. Concepts covered are Slope of a Line, Loss Function, and Solving Simple Linear Regression Equation, with examples.
Level: Fundamental
Requirements: No prior programming or statistics knowledge required.
Linear Regression vs Logistic Regression | EdurekaEdureka!
YouTube: https://youtu.be/OCwZyYH14uw
** Data Science Certification using R: https://www.edureka.co/data-science **
This Edureka PPT on Linear Regression Vs Logistic Regression covers the basic concepts of linear and logistic models. The following topics are covered in this session:
Types of Machine Learning
Regression Vs Classification
What is Linear Regression?
What is Logistic Regression?
Linear Regression Use Case
Logistic Regression Use Case
Linear Regression Vs Logistic Regression
Blog Series: http://bit.ly/data-science-blogs
Data Science Training Playlist: http://bit.ly/data-science-playlist
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Optimization is considered to be one of the pillars of statistical learning and also plays a major role in the design and development of intelligent systems such as search engines, recommender systems, and speech and image recognition software. Machine Learning is the study that gives the computers the ability to learn and also the ability to think without being explicitly programmed. A computer is said to learn from an experience with respect to a specified task and its performance related to that task. The machine learning algorithms are applied to the problems to reduce efforts. Machine learning algorithms are used for manipulating the data and predict the output for the new data with high precision and low uncertainty. The optimization algorithms are used to make rational decisions in an environment of uncertainty and imprecision. In this paper a methodology is presented to use the efficient optimization algorithm as an alternative for the gradient descent machine learning algorithm as an optimization algorithm.
In this chapter, our goal is to introduce the foundational principles of supervised learning. As we progress, we place particular emphasis on both regression and classification techniques, offering learners a more comprehensive perspective on the practical application of these methodologies in real-world scenarios. By the end of this chapter, learners will not only possess a robust understanding of the core principles but will also be armed with valuable insights into the tangible applications of supervised learning. This knowledge empowers them to skillfully navigate and leverage the full potential of this influential paradigm within the vast expanse of machine learning.
This is an elaborate presentation on how to predict employee attrition using various machine learning models. This presentation will take you through the process of statistical model building using Python.
GENETIC ALGORITHM FOR FUNCTION APPROXIMATION: AN EXPERIMENTAL INVESTIGATIONijaia
Function Approximation is a popular engineering problems used in system identification or Equation
optimization. Due to the complex search space it requires, AI techniques has been used extensively to spot
the best curves that match the real behavior of the system. Genetic algorithm is known for their fast
convergence and their ability to find an optimal structure of the solution. We propose using a genetic
algorithm as a function approximator. Our attempt will focus on using the polynomial form of the
approximation. After implementing the algorithm, we are going to report our results and compare it with
the real function output.
Performance Comparision of Machine Learning AlgorithmsDinusha Dilanka
In this paper Compare the performance of two
classification algorithm. I t is useful to differentiate
algorithms based on computational performance rather
than classification accuracy alone. As although
classification accuracy between the algorithms is similar,
computational performance can differ significantly and it
can affect to the final results. So the objective of this paper
is to perform a comparative analysis of two machine
learning algorithms namely, K Nearest neighbor,
classification and Logistic Regression. In this paper it
was considered a large dataset of 7981 data points and 112
features. Then the performance of the above mentioned
machine learning algorithms are examined. In this paper
the processing time and accuracy of the different machine
learning techniques are being estimated by considering the
collected data set, over a 60% for train and remaining
40% for testing. The paper is organized as follows. In
Section I, introduction and background analysis of the
research is included and in section II, problem statement.
In Section III, our application and data analyze Process,
the testing environment, and the Methodology of our
analysis are being described briefly. Section IV comprises
the results of two algorithms. Finally, the paper concludes
with a discussion of future directions for research by
eliminating the problems existing with the current
research methodology.
Gesture Recognition using Principle Component Analysis & Viola-Jones AlgorithmIJMER
Gesture recognition pertains to recognizing meaningful expressions of motion by a human,
involving the hands, arms, face, head, and/or body. It is of utmost importance in designing an intelligent
and efficient human–computer interface. The applications of gesture recognition are manifold, ranging
from sign language through medical rehabilitation to virtual reality. In this paper, we provide a survey on
gesture recognition with particular emphasis on hand gestures and facial expressions. Applications
involving wavelet transform and principal component analysis for face and hand gesture recognition on
digital images
Evaluation of Agro-morphological Performances of Hybrid Varieties of Chili Pe...Premier Publishers
In Benin, chilli pepper is a widely consumed as vegetable whose production requires the use of performant varieties. This work assessed, at Parakou and Malanville, the performance of six F1 hybrids of chilli including five imported (Laali, Laser, Nandi, Kranti, Nandita) and one local (De cayenne), in completely randomized block design at four replications and 15 plants per elementary plot. Agro-morphological data were collected and submitted to analysis of variance and factor analysis of mixed data. The results showed the effects of variety, location and their interactions were highly significant for most of the growth, earliness and yield traits. Imported hybrid varieties showed the best performances compared to the local one. Multivariate analysis revealed that 'De cayenne' was earlier, short in size, thin-stemmed, red fruits and less yielding (≈ 1 t.ha-1). The imported hybrids LaaliF1 and KrantiF1 were of strong vegetative vigor, more yielding (> 6 t.ha-1) by developing larger, long and hard fruits. Other hybrids showed intermediate performances. This study highlighted the importance of imported hybrids in improving yield and preservation of chili fruits. However, stability and adaptation analyses to local conditions are necessary for their adoption.
An Empirical Approach for the Variation in Capital Market Price Changes Premier Publishers
The chances of an investor in the stock market depends mainly on some certain decisions in respect to equilibrium prices, which is the condition of a system competing favorably and effectively. This paper considered a stochastic model which was latter transformed to non-linear ordinary differential equation where stock volatility was used as a key parameter. The analytical solution was obtained which determined the equilibrium prices. A theorem was developed and proved to show that the proposed mathematical model follows a normal distribution since it has a symmetric property. Finally, graphical results were presented and the effects of the relevant parameters were discussed.
Influence of Nitrogen and Spacing on Growth and Yield of Chia (Salvia hispani...Premier Publishers
Chia is an emerging cash crop in Kenya and its production is inhibited by lack of agronomic management information. A field experiment was conducted in February-June and May-August 2021, to determine the influence of nitrogen and spacing on growth and yield of Chia. A randomized complete block design with a split plot arrangement was used with four nitrogen rates as the main plots (0, 40, 80, 120 kg N ha-1) and three spacing (30 cm x 15 cm (s1), 30 cm x 30 cm (s2), 50 cm x 50 cm (s3)). Application of 120 kg N ha-1 significantly increased (p≤0.05) vegetative growth and seed yield of Chia. Stem height, branches, stem diameter and leaves increased by 23-28%, 11-13%, 43-55% and 59-88% respectively. Spacing s3 significantly increased (p≤0.05) vegetative growth. An increase of 27-74%, 36-45% and 73-107% was recorded in number of leaves, stem diameter and dry weight, respectively. Chia yield per plant was significantly higher (p≤0.05) in s3. However, when expressed per unit area, s1 significantly produced higher yields. The study recommends 120 kg N ha-1 or higher nitrogen rates and a closer spacing of 15 cm x 30 cm as the best option for Chia production in Kenya.
Enhancing Social Capital During the Pandemic: A Case of the Rural Women in Bu...Premier Publishers
Social capital plays an essential role in empowering people for social and economic change even during the pandemic. A livelihood project of the government was implemented among the members of a women’s association of a disadvantaged upland community in Bukidnon province, Southern Philippines for inclusive development. This study was conducted to determine the influence of some socio-economic attributes and the change in the knowledge level on the social capital of the rural women amidst the pandemic. The activities of the project were implemented considering the health protocols imposed by the government during the health crisis. The findings revealed that the trainings conducted resulted to a positive change in the knowledge level among the rural women. This facilitated the production of vegetables for their households and generated additional income very necessary during the pandemic especially that other economic activities were hindered. Similarly, there was a significant increase in the social capital of the rural women during the last two years. The main occupation, sources of income and their ethnicity significantly influenced the social capital of the rural women. The rural development workers and policymakers must consider the social capital of the group in the implementation of poverty alleviation programs.
Impact of Provision of Litigation Supports through Forensic Investigations on...Premier Publishers
This paper presents an argument through the fraud triangle theory that the provision of litigation supports through forensic audits and investigations in relation to corporate fraud cases is adequate for effective prosecution of perpetrators as well as corporate fraud prevention. To support this argument, this study operationalized provision of litigation supports through forensic audit and investigations, data mining for trends and patterns, and fraud data collection and preparation. A sample of 500 respondents was drawn from the population of professional accountants and legal practitioners in Nigeria. Questionnaire was used as the instrument for data collection and this was mailed to the respective respondents. Resulting responses were analyzed using the OLS multiple regression techniques via the SPSS statistical software. The results reveal that the provision of litigation supports through forensic audits and investigations, fraud data mining for trends and patterns and fraud data collection and preparation for court proceedings have a positive and significant impact on corporate fraud prevention in Nigeria. This study therefore recommends that regulators should promote the provision of litigation supports through forensic audits and investigations in relation to corporate fraud cases in publicly listed firms in Nigeria, as this will help provide reports that are acceptable in court proceedings.
Improving the Efficiency of Ratio Estimators by Calibration WeightingsPremier Publishers
It is observed that the performances of most improved ratio estimators depend on some optimality conditions that need to be satisfied to guarantee better estimator. This paper develops a new approach to ratio estimation that produces a more efficient class of ratio estimators that do not depend on any optimality conditions for optimum performance using calibration weightings. The relative performances of the proposed calibration ratio estimators are compared with a corresponding global [Generalized Regression (GREG)] estimator. Results of analysis showed that the proposed calibration ratio estimators are substantially superior to the traditional GREG-estimator with relatively small bias, mean square error, average length of confidence interval and coverage probability. In general, the proposed calibration ratio estimators are more efficient than all existing estimators considered in the study.
Urban Liveability in the Context of Sustainable Development: A Perspective fr...Premier Publishers
Urbanization and quality of urban life are mutually related and however it varies geographically and regionally. With unprecedented growth of urban centres, challenge against urban development is more in terms of how to enhance quality of urban life and liveability. Making sense of and measuring urban liveability of urban places has become a crucial step in the context of sustainable development paradigm. Geographical regions depict variations in nature of urban development and consequently level of urban liveability. The coastal regain of West Bengal faces unusual challenges caused by increasing urbanization, uncontrolled growth, and expansion of economic activities like tourism and changing environmental quality. The present study offers a perspective on urban liveability of urban places located in coastal region comprising of Purba Medinipur and South 24 Parganas districts. The study uses the liveability standards covering four major pillars- institutional, social, economic and physical and their indicators. This leads to develop a City Liveability Index to rank urban places of the region, higher the index values better the urban liveability. The data for the purpose is collected from various secondary sources. Study finds that the eastern coastal region of the country covering state of West Bengal depicts variations in index of liveability determined by physical, economic, social and institutional indicators.
Transcript Level of Genes Involved in “Rebaudioside A” Biosynthesis Pathway u...Premier Publishers
Stevia rebaudiana Bertoni is a plant which has recently been used widely as a sweetener. This medicinal plant has some components such as diterpenoid glycosides called steviol glycosides [SGs]. Rebaudioside A is a diterpenoid steviol glycoside which is 300 times sweeter than table sugar. This study was done to investigate the effect of GA3 (50 mg/L) on the expression of 14 genes involved in Rebaudioside A biosynthesis pathway in Stevia rebaudiana under in vitro conditions. The expression of DXS remarkably decreased by day 3. Also, probably because of the negative feedback of GA3 on MEP-drived isoprenes, GGDS transcript level reached its lowest amount after GA3 treatment. The abundance of DXR, CMS, CMK, MCS, and CDPS transcripts showed a significant increase at various days after this treatment. A significant drop in the expression levels of KS and UGT85C2 is detected during the first day. However, expression changes of HDR and KD were not remarkable. Results revealed that the level of transcript of UGT74G1 and UGT76G1 up regulated significantly 4 and 2 times higher than control, respectively. However, more research needs to shed more light on the mechanism of GA3 on gene expression of MEP pathway.
Multivariate Analysis of Tea (Camellia sinensis (L.) O. Kuntze) Clones on Mor...Premier Publishers
Information on genetic variability for biochemical characters is a prerequisite for improvement of tea quality. Thirteen introduced tea clones characterized with objective; assessing tea clones based on morphological characters at Melko and Gera research stations. The study was conducted during 2017/18 cropping season on experimental plots in RCBD with three replications. Data recorded on morphological traits like days from pruning to harvest, height to first branch, stem diameter, leaf serration density, leaf length, leaf width, leaf size, petiole length, leaf ratio, internode length, shoot length, number of shoot, canopy diameter, hundred shoot weight, fresh leaf yield per tree. Cluster analysis of morphological trait grouped into four clusters indicated, the existence of divergence among the tested clones. The maximum inter-cluster distance was between clusters I and IV (35.27) while the minimum inter cluster distance was observed between clusters I and II (7.8).Principal components analysis showed that the first five principal components with eigenvalues greater than one accounted 86.45% for 15 morphological traits. Generally, the study indicated presence of variability for several morphological traits. However, high morphological variation between clones is not a guarantee for a high genetic variation; therefore, molecular studies need to be considered as complementary to biochemical studies.
Causes, Consequences and Remedies of Juvenile Delinquency in the Context of S...Premier Publishers
This research work was designed to examine nature of juvenile offences committed by juveniles, causes of juvenile delinquency, consequences of juvenile delinquency and remedies for juvenile delinquency in the context of Sub-Saharan Africa with specific reference to Eritrea. Left unchecked, juvenile delinquents on the streets engage in petty theft, take alcohol or drugs, rape women, rob people at night involve themselves in criminal gangs and threaten the public at night. To shed light on the problem of juvenile delinquency in the Sub-Saharan region data was collected through primary and secondary sources. A sample size of 70 juvenile delinquents was selected from among 112 juvenile delinquents in remand at the Asmara Juvenile Rehabilitation Center in the Eritrean capital. The study was carried out through coded self-administered questionnaires administered to a sample of 70 juvenile delinquents. The survey evidence indicates that the majority of the juvenile respondents come either from families constructed by unmarried couples or separated or divorced parents where largely the father is missing in the home or dead. The findings also indicate that children born out of wedlock, families led by single mothers, lack of fatherly role models, poor parental-child relationships and negative peer group influence as dominant causes of juvenile infractions. The implication is that broken and stressed families are highly likely to be the breeding grounds for juvenile delinquency. The survey evidence indicates that stealing, truancy or absenteeism from school, rowdy or unruly behavior at school, free-riding in public transportation, damaging the book of fellow students and beating other young persons are the most common forms of juvenile offenses. It is therefore, recommended that parents and guardians should exercise proper parental supervision and give adequate care to transmit positive societal values to children. In addition, the government, the police, prosecution and courts, non-government organizations, parents, teachers, religious leaders, education administrators and other stakeholders should develop a child justice system that strives to prevent children from entering deeper into the criminal justice process.
The Knowledge of and Attitude to and Beliefs about Causes and Treatments of M...Premier Publishers
Stigma and discrimination associated with mental illness are a common occurrence in the Sub-Saharan region including Eritrea. Numerous studies from Sub-Saharan Africa suggest that stigma and discrimination are major problems in the community, with negative attitudes and behavior towards people with mental illness being widespread. In order to assess the whether such negative attitudes persist in the context of Eritrea this study explored the knowledge and perceptions of 90 Eritrean university students at the College of Business and Economics, the University of Asmara regarding the causes and remedies of mental illness A qualitative method involving coded self-administered questionnaires administered to a sample of 90 university students to collecting data at the end of 2019. The survey evidence points that almost 50% of the respondents had contact with a mentally ill person suggesting that the significant number of the respondents experienced a first-hand encounter and knowledge of mental illness in their family and community. The findings show an overall greater science-based understanding of the causes of mental illness to be followed by recommended psychiatric treatments. The survey evidence indicates that the top three leading causes of mental illness in the context of Eritrea according to the respondents are brain disease (76%), bad events in the life of the mentally ill person (66%) and substance abuse or alcohol taking, smoking, taking drugs like hashish. (54%). The majority of the respondents have a very sympathetic and positive outlook towards mentally ill persons suggesting that mentally illness does not simply affect a chosen individual rather it can happen to anybody regardless of economic class, social status, ethnicity race and religion. Medical interventions cited by the majority of the respondents as being effective treatments for mental illness centered on the idea that hospitals and clinics for treatment and even cures for psychiatric disease. Changing perceptions of mental illnesses in Eritrea that paralleled the very caring and sympathetic attitudes of the sample university students would require raising public awareness regarding mental illness through education, using the mass media to raise public awareness, integrating mental health into the primary health care system, decentralizing mental health care services to increase access to treatment and providing affordable service to maintain positive treatment outcomes.
Effect of Phosphorus and Zinc on the Growth, Nodulation and Yield of Soybean ...Premier Publishers
An investigation was carried out at Kogi State University Student Research and Demonstration farm Anyigba during the 2019 wet season to observe the effect of phosphorus and zinc on the growth, nodulation and yield of soybean. The treatments comprised three levels: phosphorus and zinc (0, 30 and 60 kg P2O5/ha; 0, 5 and 10kg Zn/ha) and two varieties TGX 536 – 02D and Samsoy 2. The investigation revealed that application of phosphorus affected growth, nodulation, yield and some yield components of soybean while zinc application, apart from the plant height, which is reduced significantly, had no significant effect on other growth characters, nodulation, yield and yield components. However, it was generally found to decrease most of the characters. Application of 60 kg P2O5/ha gave the highest growth and yield, while 30 kg P2O5/ha gave the highest nodulation. Application of 60 kg P2O5/ha significantly increased yield to 1.9t/ha, which was significantly higher over the control plots, which gave 1.7t/ha. Crude protein and oil contents of the seeds were not significantly affected by phosphorus application but were significantly affected by zinc application, which significantly decreased protein content as its amount an increase from 0 to 10 kg/ha, and significantly increased oil content from 0 to 5kg/ha and decreased it below 5kg/ha. It was also revealed that the two varieties responded similarly to phosphorus and zinc in terms of growth, grain yield and crude protein content of the seeds.
Influence of Harvest Stage on Yield and Yield Components of Orange Fleshed Sw...Premier Publishers
A field experiment was conducted at Adami Tullu Agricultural Research Center in 2018 under rainfed condition with supplementary irrigation to determine the influence of harvest stage on vine yield and tuberous root yield of orange fleshed sweet potato varieties. The experiment consisted of four harvest stages (105, 120, 135 and 150 days after planting) and Kulfo, Tulla and Guntute varieties. A 4 X 3 factorial experiment arranged in randomized complete block design with three replications was used. Interaction of harvest stage and variety significantly influenced above ground fresh biomass, vine length, marketable tuberous root weight per hectare, commercial harvest index and harvest index. The highest mean values of above ground fresh biomass (66.12 t/ha) and marketable tuberous root weight (56.39 t/ha) were produced by Guntute variety harvested at 135 days after planting. Based on the results, it can be recommended that, farmers of the study area can grow Guntute variety by harvesting at 135 days after planting to obtain optimum vine and tuberous root yields.
Performance evaluation of upland rice (Oryza sativa L.) and variability study...Premier Publishers
This study aimed at assessing genetic variability and to evaluate the performance of 13 improved upland rice varieties for yield and its components based on morphological traits. The field experiment was conducted using a randomized block design at Guraferda and Gimbo districts in the 2019 main cropping season. The analysis of variance (ANOVA) over the two locations revealed significant differences (p≤ 0.05) among varieties for days to 50% heading, days to 85% maturity, panicle length, thousand-grain weight, and grain yield. Similarly, the ANOVA for variety by location interactions depicted significant differences among the tested varieties for days to 50% heading, days to 85% maturity, and thousand-grain weight. High heritability was obtained from days to heading (88.5%), panicle length (85.0%), and grain yield (85.2%), which indicates these traits can be easily improved through selection. High to medium broad sense heritability and genetic advance as percentage of the mean for days to heading, thousand-grain weight, and grain yield indicates a good opportunity for improvement through selection using their phenotypic performance. This is mainly due to the high role of additive gene action in the expression of such traits. This study confirmed the presence of variability among varieties for most of the studied traits, which will create an opportunity for breeders to improve rice yield and other attributes.
Response of Hot Pepper (Capsicum Annuum L.) to Deficit Irrigation in Bennatse...Premier Publishers
This study was conducted at Enchete kebele in Benna-Tsemay Woreda, South Omo Zone to evaluate the response of hot pepper to deficit irrigation on yield and water productivity under furrow irrigation system. The experiment comprised four treatments (100 % of ETc, 85% of ETc, 70 % of ETc and 50% of ETc), respectively. The experiment was laid out in RCBD and replicated four times. The two years combined yield results indicated that, the maximum total yield (20.38 t/ha) was obtained from 100% ETc while minimum yield (12.92 t/ha) was obtained from 50% of ETc deficit irrigation level. The highest WUE 5.22 kg/ha mm-1 was obtained from 50% of ETc. Treatment of 100% ETc irrigation application had highest benefit cost ratio (4.5) than all others treatments. Applying 50% of ETc reduce the yield by 37% when compared to 100 % ETc. Accordingly, to achieve maximum hot pepper yield in areas where water is not scarce, applying 100% ETc irrigation water application level throughout whole growing season under furrow irrigation system is recommended. But, in the study area water scarcity is the major limiting factor for crop production. So, it is possible to get better yield and water productivity of hot pepper when we apply 85% ETc irrigation water throughout growing season under furrow irrigation system.
Harnessing the Power of Agricultural Waste: A Study of Sabo Market, Ikorodu, ...Premier Publishers
Nigeria is still burdened with huge responsibilities of waste disposal because the potential for benefits of proper waste management is yet to be harnessed. The paper evaluates the capacity of the Sabo Cattle market in producing the required quantities of waste from animal dung alongside decomposed fruits with a view to generating renewable energy possibilities for lighting, security and other business activities of the market. It is estimated that about 998 million tons of agricultural waste is produced yearly in the country with organic wastes amounting to 80 percent of the total solid wastes. This can be categorized into biodegradable and non-biodegradable wastes. The paper evaluates the capacity of the Sabo Cattle market in producing the required quantities of waste from animal dung alongside decomposed fruits with a view to generating renewable energy possibilities for lighting, security and other business activities of the market. The Sabo market was treated as a study case with the adoption of in-depth examinations of the facility, animals and products for sale and waste generated. A combination of experimental, interviews (qualitative) and design simulation (for final phase) was adopted to extract, verify and analyse the data generated from the study. Animal waste samples were subjected to compositional and fibre analysis with results showing that the sample has high potency for biogas production. Biodegradable Wastes are human and animal excreta, agricultural and all degradable wastes. Availability of high quantity of waste generated being organic in Sabo market allows the use of anaerobic digestion to be proposed as a waste to energy technology due to its feasibility for conversion of moist biodegradable wastes into biogas. The study found that at peak supply period during the Islamic festivities, a conservative 300tonnes of animal waste is generated during the week which translates to over 800kilowatts of electricity.
Influence of Conferences and Job Rotation on Job Productivity of Library Staf...Premier Publishers
The general purpose of this study is to investigate the influence of conferences and job rotation on job productivity of library staff in tertiary institutions in Imo State, Nigeria. The survey research design was used for this study using questionnaire as an instrument for data collection. This study covered the entire population of 661. Out of these, 501 copies of the questionnaire representing 75.8% were duly completed and returned for analysis. Student’s t-test was used to analyze the research questions. The finding showed that conferences had no significant influence on the job productivity of library staff in tertiary institutions in Imo State, Nigeria (F cal= 7.86; t-vale =6.177; p >0.005). Finding also showed that job rotation significantly influences job productivity of library staff in tertiary institutions in Imo State, Nigeria (F-cal value= 18.65; t-value = 16.225; P<0.05). This study recommended that, government should ensure that library staff participate in conferences with themes and topics that are relevant to the job they perform and also ensure that there should be proper evaluation and feedback mechanism which aimed to ensuring control and minimize abuse of their development opportunities. Again, there should be written statement of objectives in order to sustain job rotation programmes. Also, that training and development needs of library staff must be identified and analyzed before embarking on job rotation processes as this would help to build skills, competences, specialization and high job productivity.
Scanning Electron Microscopic Structure and Composition of Urinary Calculi of...Premier Publishers
Microscopic examination of urine samples collected from geriatric dogs revealed increased numbers of erythrocytes, leucocytes, epithelial cells and pus cells along with casts, bacteria, spermatozoa and crystals of various shapes. Among the different crystals, triple phosphate or struvite were predominant, followed by calcium oxalate dihydrate, calcium oxalate monohydrate and ammonium urate or biurate. The struvite crystals were, coffin-lid shape and while calcium oxalate dihydrate were octahedron or envelope and monohydrate crystals demonstrated “picket fence” and “dumbbell” and “hemp seed” appearance. Brown or yellow-brown spherical bodies with irregular borders with thorn-apple appearance were shown by ammonium urate or biurate crystals. SEM aspects of magnesium ammonium phosphate crystals revealed perpendicular columnar strata, few with scattered hexa or octa-hedral coffin-lid shaped crystals and calcium phosphate crystals were like cracked eggshells. Presence of wavy phases with sundry areas (uric acid), picket fence (calcium oxalate monohydrate) and typical envelope (calcium oxalate dehydrate) were electron microscopic appearance of various crystals.
Gentrification and its Effects on Minority Communities – A Comparative Case S...Premier Publishers
This paper does a comparative analysis of four global cities and their minority districts which have been experiencing the same structural pressure of gentrification. The main contribution of this paper is providing a detailed comparison of four micro geographies worldwide and the impacts of gentrification on them: Barrio Logan in San Diego, Bo-Kaap in Cape Town, the Mission District in San Francisco, and the Rudolfsheim-Fünfhaus District in Vienna. All four cities have been experiencing the displacement of minority communities due to increases in property values. These cities were chosen because their governments enacted different policies to temper the gentrification process. It was found that cities which implemented social housing and cultural inclusionary policies were more successful in maintaining the cultural and demographic make-up of the districts.
Oil and Fatty Acid Composition Analysis of Ethiopian Mustard (Brasicacarinata...Premier Publishers
The experiments was conducted at Holetta Agricultural Research Center, to analyze forty nine Ethiopian Mustard land races for oil and fatty acid composition traits The experiment was carried out in a simple lattice design. The analysis of variance showed that there were highly significant differences among genotypes for all oil and fatty acid traits compared. The significant difference indicates the existence of genetic variability among the land races which is important for improvement
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
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 French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
We all have good and bad thoughts from time to time and situation to situation. We are bombarded daily with spiraling thoughts(both negative and positive) creating all-consuming feel , making us difficult to manage with associated suffering. Good thoughts are like our Mob Signal (Positive thought) amidst noise(negative thought) in the atmosphere. Negative thoughts like noise outweigh positive thoughts. These thoughts often create unwanted confusion, trouble, stress and frustration in our mind as well as chaos in our physical world. Negative thoughts are also known as “distorted thinking”.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
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.
2. Linear Algebra – A Powerful Tool for Data Science
Ishchi H. 138
APPLICATIONS OF LINEAR ALGEBRA IN DATA
SCIENCES
Fig. 2: Applications of linear algebra in data sciences
Linear Algebra in Machine Learning
The following are the some application areas of linear
algebra in machine learning.
1. Loss functions
2. Regularization
3. Covariance Matrix
4. Support Vector Machine Classification
Loss functions
Consider how good a model is, say a Linear Regression
model, and fits a given data:
• Some arbitrary prediction function (a linear function for
a Linear Regression Model)
• Use it on the independent features of the data to
predict the output
• Calculate how far-off the predicted output is from the
actual output
• Use these calculated values to optimize prediction
function using some strategy like Gradient Descent
It is difficult to calculate how different prediction is from the
expected output. This issue can be resolved using loss
function. A loss function is an application of the Vector
Norm in Linear Algebra. The norm of a vector can simply
be its magnitude. There are many types of vector norms.
Here, discussed two types.
L1 Norm: Also known as the Manhattan Distance or
Taxicab Norm. The L1 Norm is the distance travelled from
the origin to the vector if the only permitted directions are
parallel to the axes of the space.
In this 2D space, consider the vector (3, 4) by traveling 3
units along the x-axis and then 4 units parallel to the y-axis
(as shown). Or travelled 4 units along the y-axis first and
then 3 units parallel to the x-axis. In either case, travelled
a total of 7 units.
L2 Norm: Also known as the Euclidean Distance. L2
Norm is the shortest distance of the vector from the origin
as shown by the red path in the figure below:
Fig. 3: Euclidean Distance
This distance is calculated using the Pythagoras Theorem.
It is the square root of (3^2 + 4^2), which is equal to 5. The
predicted values are stored in a vector P and the expected
values are stored in a vector E. Then P-E is the difference
vector. And the norm of P-E is the total loss for the
prediction.
Regularization
Regularization is a very important concept in data science.
It’s a technique we use to prevent models from overfitting.
Regularization is actually another application of the Norm.
A model is said to overfit when it fits the training data too
well. Such a model does not perform well with new data
because it has learned even the noise in the training data.
It will not be able to generalize on data that it has not seen
before. The below illustration sums up this idea really well:
Regularization penalizes overly complex models by adding
the norm of the weight vector to the cost function. Since
we want to minimize the cost function, we will need to
minimize this norm. This causes unrequired components
of the weight vector to reduce to zero and prevents the
prediction function from being overly complex.
3. Linear Algebra – A Powerful Tool for Data Science
Int. J. Stat. Math. 139
Fig 4: Regularization
The L1 and L2 norms we discussed above are used in two
types of regularization:
• L1 regularization used with Lasso Regression
• L2 regularization used with Ridge Regression
Covariance Matrix
Bivariate analysis is an important step in data exploration
to study the relationship between pairs of variables.
Covariance or Correlation is measures used to study
relationships between two continuous variables.
Covariance indicates the direction of the linear relationship
between the variables. A positive covariance indicates that
an increase or decrease in one variable is accompanied
by the same in another. A negative covariance indicates
that an increase or decrease in one is accompanied by the
opposite in the other.
Fig 5: Co-variance
On the other hand, correlation is the standardized value of
Covariance. A correlation value tells us both the strength
and direction of the linear relationship and has the range
from -1 to 1. Using the concepts of transpose and matrix
multiplication in Linear Algebra, there is another
expression for the covariance matrix:
𝑐𝑜𝑣 = 𝑋 𝑇
𝑋
Here, X is the standardized data matrix containing all
numerical features.
Support Vector Machine Classification
Support vector machine is the most common classification
algorithms that regularly produces remarkable results. It is
an application of the concept of Vector Spaces in Linear
Algebra. Support Vector Machine, or SVM, is a
discriminative classifier that works by finding a decision
surface. It is a supervised machine learning algorithm. In
this algorithm, we plot each data item as a point in an n-
dimensional space (where n is the number of features) with
the value of each feature being the value of a particular
coordinate. Then, perform classification by finding the
hyperplane that differentiates the two classes very well i.e.
with the maximum margin, which is C is this case.
Fig 6: Support Vector Machine
A hyperplane is a subspace whose dimensions are one
less than its corresponding vector space, so it would be a
straight line for a 2D vector space, a 2D plane for a 3D
vector space and so on. Again, Vector Norm is used to
calculate the margin.
Linear Algebra in Dimensionality Reduction
1. Principal Component Analysis
2. Singular Value Decomposition
1. Principal Component Analysis
Principal Component Analysis, or PCA, is an unsupervised
dimensionality reduction technique. PCA finds the
directions of maximum variance and projects the data
along them to reduce the dimensions. Without going into
the math, these directions are the eigenvectors of the
covariance matrix of the data (Gupta et al., 2010; Slavkovic
and Jevtic, 2012)
4. Linear Algebra – A Powerful Tool for Data Science
Ishchi H. 140
Eigenvectors for a square matrix are special non-zero
vectors whose direction does not change even after
applying linear transformation (which means multiplying)
with the matrix. They are shown as the red-colored vectors
in the figure below:
Fig 7: Eigen Vectors
2. Singular Value Decomposition
Singular Value Decomposition (SVD) is underrated and
not discussed enough. It is an amazing technique of matrix
decomposition with diverse applications. Here focused
about SVD in Dimensionality Reduction. Specifically, this
is known as Truncated SVD.
• Start with the large m x n numerical data matrix A,
where m is the number of rows and n is the number of
features
Decompose it into 3 matrices as shown here:
Choose k singular values based on the diagonal matrix
and truncate (trim) the 3 matrices accordingly:
Finally, multiply the truncated matrices to obtain the
transformed matrix A_k. It has the dimensions m x k. So,
it has k features with k < n. On applying truncated SVD to
the Digits data, the below plot was obtained.
Linear Algebra in Natural Language Processing
1. Word Embeddings
2. Latent Semantic Analysis
Word Embeddings
Machine learning algorithms cannot work with raw textual
data. The raw data needs to be converted to some
numerical and statistical features to create model inputs.
There are many ways for extracting features from text
data, such as:
• Meta attributes of a text, like word count, special
character count, etc.
• NLP attributes of text using Parts-of-Speech tags and
Grammar Relations like the number of proper nouns
• Word Vector Notations or Word Embeddings
Word Embeddings is a way of representing words as low
dimensional vectors of numbers while preserving their
context in the document. These representations are
obtained by training different neural networks on a large
amount of text which is called a corpus. They also help in
analyzing syntactic similarity among words:
5. Linear Algebra – A Powerful Tool for Data Science
Int. J. Stat. Math. 141
Word2Vec and GloVe are two popular models to create Word Embeddings.
Latent Semantic Analysis
Latent Semantic Analysis (LSA), or Latent Semantic
Indexing, is one of the techniques of Topic Modeling. It is
another application of Singular Value Decomposition.
Latent means ‘hidden’. True to its name, LSA attempts to
capture the hidden themes or topics from the documents
by leveraging the context around the words.
• First, generate the Document-Term matrix for the data
Use SVD to decompose the matrix into 3 matrices:
• Document-Topic matrix
• Topic Importance Diagonal Matrix
• Topic-term matrix
• Truncate the matrices based on the importance of
topics
Linear Algebra in Computer Vision
Deep learning methods can achieve state – of – the – art
results on challenging computer vision problems such as
image classification, object detection and face recognition.
• Image representation as Tensors
• Convolution and Image Processing
Image representation as Tensors
A computer does not process images as humans do.
Machine learning algorithms need numerical features to
work with. A digital image is made up of small indivisible
units called pixels. Consider the figure below:
This grayscale image of the digit zero is made of 8 x 8 =
64 pixels. Each pixel has a value in the range 0 to 255. A
value of 0 represents a black pixel and 255 represent a
white pixel. Conveniently, an m x n grayscale image can
be represented as a 2D matrix with m rows and n columns
with the cells containing the respective pixel values:
A colored image is generally stored in the RGB system.
Each image can be thought of as being represented by
three 2D matrices, one for each R, G and B channel. A
pixel value of 0 in the R channel represents zero intensity
of the Red color and of 255 represents the full intensity of
the Red color. Each pixel value is then a combination of
the corresponding values in the three channels: In reality,
instead of using 3 matrices to represent an image, a tensor
is used. A tensor is a generalized n-dimensional matrix.
For an RGB image, a 3rd ordered tensor is used. Imagine
it as three 2D matrices stacked one behind another:
Convolution and Image Processing
2D Convolution is a very important operation in image
processing. It consists of the below steps:
• Start with a small matrix of weights, called a kernel or
a filter