Jsm logistic services - PowerPoint PPT Presentation


WELCOME!.JSM 2023. Council of Chapters (COC) Business Meeting

Highlighting the key points discussed during the JSM 2023 Council of Chapters (COC) Business Meeting, including introductions, updates, and upcoming elections for COCGB positions in 2025. The meeting also touched upon the roles of current and future COCGB members, nominations committees, and opportu

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Understanding Logistic Regression Model Selection in Statistics

Statistics, as Florence Nightingale famously said, is the most important science in the world. In this chapter on logistic regression, we delve into model selection, interpretation of parameters, and methods such as forward selection, backward elimination, and stepwise selection. Guidelines for sele

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Understanding Machine Learning Concepts: Linear Classification and Logistic Regression

Explore the fundamentals of machine learning through concepts such as Deterministic Learning, Linear Classification, and Logistic Regression. Gain insights on linear hyperplanes, margin computation, and the uniqueness of functions found in logistic regression. Enhance your understanding of these key

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Logistic Strategy for Amazon: Enhancing Efficiency in Supply Chain Management

Explore the vital components of logistics, including transportation, handling, warehousing, and information flow. Understand the significance of efficient logistics in enhancing a country's export competitiveness and supporting small businesses. Discover major courier and cargo companies operating i

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Binary Logistic Regression with SPSS – A Comprehensive Guide by Karl L. Wuensch

Explore the world of Binary Logistic Regression with SPSS through an instructional document provided by Karl L. Wuensch of East Carolina University. Understand when to use this regression model, its applications in research involving dichotomous variables, and the iterative maximum likelihood proced

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Decarbonising Multimodal Logistic Chains: Best Practices Panel in Hamburg

Explore key discussions from the 13rdERA Multimodal conference Panel III in Hamburg focusing on decarbonising multimodal logistic chains. The panelists, including Nicolas Albrecht from Cargobeamer, Andr Düring from Alstom, and Matthias Knöpling from VTG, shared insights on shifting towards sustain

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Analyzing Trends in Student Placement for Autism and Intellectual Disability in California

Explore the project's goal of examining trends and factors influencing the placement of students with autism and intellectual disability in California over a 5-year period. Data obtained from the California Department of Education underwent complex data organization to build an analyzable dataset. M

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Understanding Proportional Odds Assumption in Ordinal Regression

Exploring the proportional odds assumption in ordinal regression, this article discusses testing methods, like the parallel lines test, comparing multinomial and ordinal logistic regression models, and when to use each approach. It explains how violating the assumption may lead to using the multinom

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Understanding Multivariate Binary Logistic Regression Models: A Practical Example

Exploring the application of multivariate binary logistic regression through an example on factors associated with receiving assistance during childbirth in Ghana. The analysis includes variables such as wealth quintile, number of children, residence, and education level. Results from the regression

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JSM Logistic Services - Redefining the Logistics Market with Passion and Innovation

JSM Logistic Services (JLS) is a dynamic logistics company dedicated to providing top-quality services worldwide. With a focus on service excellence and innovation, JLS offers a wide range of logistics solutions including Air & Ocean Forwarding, Multi-Modal Transport, Customs House Brokerage, Wareho

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Understanding Item Response Theory in Measurement Models

Item Response Theory (IRT) is a statistical measurement model used to describe the relationship between responses on a given item and the underlying trait being measured. It allows for indirectly measuring unobservable variables using indicators and provides advantages such as independent ability es

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Humanitarian Transformation of Logistic Firms in Emergency Situations

This research explores how logistic firms evolve into humanitarian entities in response to grand challenges like natural disasters and refugee crises. Case studies and data collection methodologies are utilized to understand the transformation process, as seen in examples such as SOS Mediterrane and

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Machine Learning Algorithms and Models Overview

This class summary covers topics such as supervised learning, unsupervised learning, classification, clustering, regression, k-NN models, linear regression, Naive Bayes, logistic regression, and SVM formulations. The content provides insights into key concepts, algorithms, cost functions, learning a

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Siddhi Logistics - Unified Cold Chain & Logistic Solutions Provider

Siddhi Logistics is a unified cold chain and logistics solution provider founded by industry experts, offering quality-focused services like refrigerated transportation and value-added logistics solutions. They specialize in single-source supply chain solutions, providing refrigerated vehicles with

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What to Expect of Classifiers: Reasoning about Logistic Regression with Missing Features

This research discusses common approaches in dealing with missing features in classifiers like logistic regression. It compares generative and discriminative models, exploring the idea of training separate models for feature distribution and classification. Expected Prediction is proposed as a princ

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Exploring Resilience in Computer Science Education: A Preliminary Study

This study examines the relationship between resilience and effective learning in Computer Science education using the Grit Scale and Nicholson McBride Resilience Quotient. Research methods, findings, and implications are presented based on data from a first-year BSc/MComp cohort, with insights into

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Overview of gologit2: Generalized Logistic Regression Models for Ordinal Dependent Variables

gologit2 is an advanced program for estimating generalized logistic regression models, including proportional odds, generalized ordered logit, and partial proportional odds models. It offers features beyond traditional ologit, allowing for less restrictive and more parsimonious modeling of ordinal d

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Introduction to Binary Logistic Regression: A Comprehensive Guide

Binary logistic regression is a valuable tool for studying relationships between categorical variables, such as disease presence, voting intentions, and Likert-scale responses. Unlike linear regression, binary logistic regression ensures predicted values lie between 0 and 1, making it suitable for m

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Introduction to Multinomial Logistic Regression by Dr. Heini V. at University of Southampton

This content introduces Multinomial Logistic Regression, discussing categorical response variables, the basics of the model, interpretation of parameters, and an example study on economic activity and gender. It covers the extension of binary logistic regression to multiple categories, interpretatio

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CSEP 546 Machine Learning Course Overview

This course, led by Geoff Hulten and TAs Alon Milchgrub and Andrew Wei, delves into important machine learning algorithms and model production techniques. Topics covered include logistic regression, feature engineering, decision trees, intelligent user experiences, computer vision basics, neural net

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Understanding Binary Logistic Regression and Its Importance in Research

Binary logistic regression is an essential statistical technique used in research when the dependent variable is dichotomous, such as yes/no outcomes. It overcomes limitations of linear regression, especially when dealing with non-normally distributed variables. Logistic regression is crucial for an

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Foundations of Probabilistic Models for Classification in Machine Learning

This content delves into the principles and applications of probabilistic models for binary classification problems, focusing on algorithms and machine learning concepts. It covers topics such as generative models, conditional probabilities, Gaussian distributions, and logistic functions in the cont

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Logistics Service Discounts and Operations Overview

This document showcases the logistics services offered by Aker Custom & Logistic for various locations like Tarragona, Sete, Yalova, Trieste, Cesme, and more. It details special discounts available for DFDS and Ulusoy, with information on freight rates, trailer discounts, and service timings for cus

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Understanding Generative vs. Discriminative Models in Machine Learning

Explore the key differences between generative and discriminative models in the realm of machine learning, including their approaches, assumptions, and applications. Delve into topics such as graphical models, logistic regression, probabilistic classifiers, and classification rules to gain insights

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Understanding Overdispersed Data in SAS for Regression Analysis

Explore the concept of overdispersion in count and binary data, its causes, consequences, and how to account for it in regression analysis using SAS. Learn about Poisson and binomial distributions, along with common techniques like Poisson regression and logistic regression. Gain insights into handl

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Determinants of Growth in Micro & Small Enterprises: Empirical Evidence from Jordan

Jordanian micro and small enterprises (MSEs) play a significant role in the economy but face challenges in accessing markets and obtaining finance. A research study was conducted in Jordan to analyze the factors influencing the growth of MSEs, including formality, education level of owners, technolo

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Facilitating Preparation of District Election Management Plan: RO/ARO Learning Module

This content focuses on facilitating the preparation of the District Election Management Plan (DEMP) as part of the learning module for Returning Officers (RO) and Assistant Returning Officers (ARO). It covers essential components of the DEMP, major requisite information needed, steps in the prepara

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Understanding Robustness to Adversarial Examples in Machine Learning

Explore the vulnerability of machine learning models to adversarial examples, including speculative explanations and the importance of linear behavior. Learn about fast gradient sign methods, adversarial training of deep networks, and overcoming vulnerabilities. Discover how linear perturbations imp

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Predictive Model for Protection Risks Using Logistic Regression

Utilizing logistic regression, a statistical modeling technique, to predict protection risks on freedom of movement in Afghanistan. The analysis involves exploratory data examination, correlation matrices, and predictor variable assessment to identify factors influencing the outcome variable. Insigh

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Understanding Logistic Regression in Multi-level Hierarchies

Explore the intricacies of logistic regression in cross-level hierarchies through helpful project advice, model graphs, and leftover considerations. Learn about transforming binary responses, interpreting log-odds, and conducting multilevel logistic regression with random intercepts. Dive into real-

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Comprehensive Guide to Multiple Multinomial Logistic Regression with Dr. Heini V.

Learn about multinomial logistic regression models with multiple explanatory variables, including model selection, likelihood ratio tests, and Wald tests. Explore an example on the association between economic activity, gender, age, and marital status. Understand the distribution of variables like e

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Population Management and Sustainable Harvesting Strategies

Actual population numbers exhibit complex fluctuations influenced by predation and other factors. Understanding concepts like Maximum Sustainable Yield (MSY) and Minimum Viable Population (MVP) can help in managing populations effectively. The concept of MSY ensures the maximum harvest of a renewabl

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Development of Satellite Passive Microwave Snowfall Detection Algorithm

This study focuses on the development of a satellite passive microwave snowfall detection algorithm, highlighting the challenges in accurately determining snowfall using satellite instruments. The algorithm uses data from AMSU/MHS, ATMS, and SSMIS sensors to generate snowfall rate estimates, overcom

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Premorbid Temperament as a Predictor for Remission in Depression Study

Personality traits, specifically premorbid temperament, play a crucial role in predicting remission from depressive disorders. This study, led by Professor Jouko Miettunen, examines how premorbid personality can be a significant factor in assessing the risk and outcome of depressive disorders. By an

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AI Solutions for Direct-to-Customer Sales Innovation Briefing

Explore the latest in AI technologies enabling direct customer sales and marketing strategies. The proposal focuses on market access, customer experience enhancement, logistics organization, business ecosystem requirements, and cost-effective tools. Partners like Upseller Oy, GreenPeak Oy, ETM Ltd.,

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Machine Learning in Commodity Flow Survey: Improving Data Quality

Exploring the application of machine learning in the Commodity Flow Survey (CFS), this report discusses the use of logistic regression models to correct and impute shipment data. The upcoming shift to eliminate manual SCTG product code provision aims to enhance respondent experience and response rat

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Understanding Nearest Neighbor Classification in Data Mining

Classification methods in data mining, like k-nearest neighbor, Naive Bayes, Logistic Regression, and Support Vector Machines, rely on analyzing stored cases to predict the class label of unseen instances. Nearest Neighbor Classifiers use the concept of proximity to categorize data points, making de

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Understanding Linear Regression and Gradient Descent

Linear regression is about predicting continuous values, while logistic regression deals with discrete predictions. Gradient descent is a widely used optimization technique in machine learning. To predict commute times for new individuals based on data, we can use linear regression assuming a linear

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Understanding Multiclass Logistic Regression in Data Science

Multiclass logistic regression extends standard logistic regression to predict outcomes with more than two categories. It includes ordinal logistic regression for hierarchical categories and multinomial logistic regression for non-ordered categories. By fitting separate models for each category, suc

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Introduction to Advanced Topics in Data Analysis and Machine Learning

This content delves into advanced topics in data analysis and machine learning, covering supervised and unsupervised learning, classification, logistic regression, modeling class probabilities, and prediction using logistic functions. It discusses foundational concepts, training data, classification

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