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ACTIVE NETWORK EQUIPMENT AND ARCHITECTURE IMPLEMENTED AS A PART OF THE E-SCHOOLS PILOT PROJECT The Croatian Academic and Research Network (CARNet) is currently coordinating a program referred to as e-Schools, aimed to strengthen the capacities of elementary and secondary education by introducing ICT into the school system. The aim of this paper is to analyze the network infrastructure deployed in the e-Schools pilot project, focusing on one target high school in the city of Varaždin as a case study to help develop an insightful methodology in the future performance analysis of the infrastructure deployed in schools. A small-scale analysis of the school network infrastructure was carried out, with an additional examination of Quality of Experience (QoE) across three scenarios that simulate the usual behavior of students and teachers, while also observing the behavior of the network infrastructure through Meraki dashboard system. Based on our findings, we concluded that students are gen

ACTIVE NETWORK EQUIPMENT AND ARCHITECTURE IMPLEMENTED AS A PART OF THE E-SCHOOLS PILOT PROJECT The Croatian Academic and Research Network (CARNet) is currently coordinating a program referred to as e-Schools, aimed to strengthen the capacities of elementary and secondary education by introducing ICT into the school system. The aim of this paper is to analyze the network infrastructure deployed in the e-Schools pilot project, focusing on one target high school in the city of Varaždin as a case study to help develop an insightful methodology in the future performance analysis of the infrastructure deployed in schools. A small-scale analysis of the school network infrastructure was carried out, with an additional examination of Quality of Experience (QoE) across three scenarios that simulate the usual behavior of students and teachers, while also observing the behavior of the network infrastructure through Meraki dashboard system. Based on our findings, we concluded that students are gen

Collaborative Outreach to “atrisk” Middle School Students Through an ongoing collaboration among Mississippi State’s Swalm School of Chemical Engineering, the College of Education and Fifth Street Middle School in Westpoint, Mississippi, pre-service mathematics teachers and “at-risk” middle school students come together to focus on learning STEM concepts in an innovative way using LEGO robotics. A key feature of this project is the highly visual approach to teaching and studying STEM concepts. The current phase of the project is directed toward “at risk” middle school students—students whose performance on assessments indicates a strong likelihood of their failure or discontinuance from school. Pre-service teachers participate in completing lesson planning and execution coupled with service-learning by delivering the lessons to middle school students. The collaboration between the university and K-12 faculty members AND across disciplinary boundaries (i.e. engineering and education) p

School Furniture and Anthropometric Measures among Primary School Children This study is a cross-sectional study with the objective to determine mismatch between school furniture and anthropometric measurement among primary school children in Mersing. The sample consisted of 91 primary school children (46 male and 45 female) from Year 2 and Year 5 in two schools in Mersing District, Malaysia. Seven anthropometric measurement (height, weight, popliteal height, buttock-popliteal length, hip breadth, shoulder height and elbow height while sitting) as well as 5 furniture dimensions (seat height, seat depth, seat width, backrest height and seat to desk height) were taken. Instruments used were Martyn type anthropometer set, ruler, height scale and weighing scale. Differences between genders in anthropometric measurements were also investigated in this study. Findings showed 100% high mismatch for seat height, seat depth, desk height respectively while 56% match and only 44% mismatch for ba

Collaborative Outreach to “atrisk” Middle School Students Through an ongoing collaboration among Mississippi State’s Swalm School of Chemical Engineering, the College of Education and Fifth Street Middle School in Westpoint, Mississippi, pre-service mathematics teachers and “at-risk” middle school students come together to focus on learning STEM concepts in an innovative way using LEGO robotics. A key feature of this project is the highly visual approach to teaching and studying STEM concepts. The current phase of the project is directed toward “at risk” middle school students—students whose performance on assessments indicates a strong likelihood of their failure or discontinuance from school. Pre-service teachers participate in completing lesson planning and execution coupled with service-learning by delivering the lessons to middle school students. The collaboration between the university and K-12 faculty members AND across disciplinary boundaries (i.e. engineering and education) p

School Furniture and Anthropometric Measures among Primary School Children This study is a cross-sectional study with the objective to determine mismatch between school furniture and anthropometric measurement among primary school children in Mersing. The sample consisted of 91 primary school children (46 male and 45 female) from Year 2 and Year 5 in two schools in Mersing District, Malaysia. Seven anthropometric measurement (height, weight, popliteal height, buttock-popliteal length, hip breadth, shoulder height and elbow height while sitting) as well as 5 furniture dimensions (seat height, seat depth, seat width, backrest height and seat to desk height) were taken. Instruments used were Martyn type anthropometer set, ruler, height scale and weighing scale. Differences between genders in anthropometric measurements were also investigated in this study. Findings showed 100% high mismatch for seat height, seat depth, desk height respectively while 56% match and only 44% mismatch for ba

Fashion Learning adapts to Attributes’ Data The ancient Greek philosopher said that it is much easier to recognize the attributes of the concept than to understand it directly. Nowadays, his descendants employ this philosophy to improve objects understanding in each image at fine-grained level. This research direction is developed widely. These finegrained details are often called attributes. While local features are supposed to be better than global features, many handcrafted features like as SIFT, HOG, … are used to extracted visual features. However, the features are not appropriate to all attributes. In addition, to narrow semantic gap in fashion recognition and retrieval, local features are replaced by attribute vectors for each fashion image. Hence, attribute learning become a hot topic in many researches. http://www.aleeshainstitute.com/ In Computer Vision, attributes are used in face retrieval [3], fashion retrieval [2], violent’s attributes detection [17], crowd attributes

Fashion Learning adapts to Attributes’ Data The ancient Greek philosopher said that it is much easier to recognize the attributes of the concept than to understand it directly. Nowadays, his descendants employ this philosophy to improve objects understanding in each image at fine-grained level. This research direction is developed widely. These finegrained details are often called attributes. While local features are supposed to be better than global features, many handcrafted features like as SIFT, HOG, … are used to extracted visual features. However, the features are not appropriate to all attributes. In addition, to narrow semantic gap in fashion recognition and retrieval, local features are replaced by attribute vectors for each fashion image. Hence, attribute learning become a hot topic in many researches. http://www.aleeshainstitute.com/ In Computer Vision, attributes are used in face retrieval [3], fashion retrieval [2], violent’s attributes detection [17], crowd attributes

ANNOTATED ONLINE RESOURCES FOR FASHION FEATURE EXTRACTION We propose a method to extract representative features for fashion analysis by utilizing weakly annotated online fashion images in this work. The proposed system consists of two stages. In the first stage, we attempt to detect clothing items in a fashion image: the top clothes (t), bottom clothes (b) and one-pieces (o). In the second stage, we extract discriminative features from detected regions for various applications of interest. Unlike previous work that heavily relies on well-annotated fashion data, we propose a way to collect fashion images from online resources and conduct automatic annotation on them. Aleesha Intitute Fashion Designing Based on this methodology, we create a new fashion dataset, called the Web Attributes, to train our feature extractor. It is shown by experiments that extracted regional features can capture local characteristics of fashion images well and offer better performance than previous works.

ANNOTATED ONLINE RESOURCES FOR FASHION FEATURE EXTRACTION We propose a method to extract representative features for fashion analysis by utilizing weakly annotated online fashion images in this work. The proposed system consists of two stages. In the first stage, we attempt to detect clothing items in a fashion image: the top clothes (t), bottom clothes (b) and one-pieces (o). In the second stage, we extract discriminative features from detected regions for various applications of interest. Unlike previous work that heavily relies on well-annotated fashion data, we propose a way to collect fashion images from online resources and conduct automatic annotation on them. Aleesha Intitute Fashion Designing Based on this methodology, we create a new fashion dataset, called the Web Attributes, to train our feature extractor. It is shown by experiments that extracted regional features can capture local characteristics of fashion images well and offer better performance than previous works.

Learning and forecasting fashion style We propose an approach to predict the future of fashion styles based on images and consumers’ purchase data. Our approach 1) learns a representation of fashion images that captures the garments’ visual attributes; then 2) discovers a set of fine-grained styles that are shared across images in an unsupervised manner; finally, 3) based on statistics of past consumer purchases, constructs the styles’ temporal trajectories and predicts their future trends. Elements of fashion In some fashion-related tasks, one might rely solely on meta information provided by product vendors, e.g., to analyze customer preferences. Aleesha Institute Fashion Designing Meta data such as tags and textual descriptions are often easy to obtain and interpret. However, they are usually noisy and incomplete. For example, some vendors may provide inaccurate tags or descriptions in order to improve the retrieval rank of their products, and even extensive textual descriptions

Learning and forecasting fashion style We propose an approach to predict the future of fashion styles based on images and consumers’ purchase data. Our approach 1) learns a representation of fashion images that captures the garments’ visual attributes; then 2) discovers a set of fine-grained styles that are shared across images in an unsupervised manner; finally, 3) based on statistics of past consumer purchases, constructs the styles’ temporal trajectories and predicts their future trends. Elements of fashion In some fashion-related tasks, one might rely solely on meta information provided by product vendors, e.g., to analyze customer preferences. Aleesha Institute Fashion Designing Meta data such as tags and textual descriptions are often easy to obtain and interpret. However, they are usually noisy and incomplete. For example, some vendors may provide inaccurate tags or descriptions in order to improve the retrieval rank of their products, and even extensive textual descriptions

School Bus Based on Kana Model Karthi VIdhyalaya ICSE School Kumbakonam Generally, customers’ ideas about quality are often confused and difficult to see clearly. So, when facing how to plan a product or service, manufacturers have to spare no effort to satisty the customer needs. A precise list of customers’ need is a determining factor. Many methods are available for investigating the characteristics of customer requirements. For instance, it is important for producers to ask customers to rank-order them. The particular method we will discuss here is based on the work of Professor Noriaki Kano of Tokyo Rika University. The ideas which the Professor Kano and his colleagues developed are as follows. A. Making abstract ideas about quality into concrete It is really difficult for customers to express their needs or convey their needs to manufacturers clearly. https://karthividhyalayaicse.com/ As all customers’ ideas made, many requirements emerge, and they finally fall into several g

School Bus Based on Kana Model Karthi VIdhyalaya ICSE School Kumbakonam Generally, customers’ ideas about quality are often confused and difficult to see clearly. So, when facing how to plan a product or service, manufacturers have to spare no effort to satisty the customer needs. A precise list of customers’ need is a determining factor. Many methods are available for investigating the characteristics of customer requirements. For instance, it is important for producers to ask customers to rank-order them. The particular method we will discuss here is based on the work of Professor Noriaki Kano of Tokyo Rika University. The ideas which the Professor Kano and his colleagues developed are as follows. A. Making abstract ideas about quality into concrete It is really difficult for customers to express their needs or convey their needs to manufacturers clearly. https://karthividhyalayaicse.com/ As all customers’ ideas made, many requirements emerge, and they finally fall into several g

Reorganization by Combining with Traffic Congestion Data of The School District In recent years, traffic congestion has become increasingly serious, and typical tidal mode of transportation is particularly prominent in urban traffic. This brings some troubles to people’s daily travel. There is no doubt that the increasing number of private cars is the main cause of traffic congestion. Therefore, some measures were taken in [1] to reduce traffic congestion, like limiting the number of trips through the license plate tail number. However, there are also hidden factors that can cause traffic congestion, such as the way of school district plan. In Beijing, the school that the children can choose mainly depends on where their parents live. In addition, due to the attention of children’s education and travel safety, parents pick up their children by private car at the time of upper and lower school [2], [3]. The centralized division by residential areas is easy to cause local traffic conges

Telephone Calls from Faculty on the Matriculation of High School Students Two characteristics of the University of San Diego present challenges in identify those students who might be interested in pursuing a USD engineering degree. First, as a Catholic, predominantly undergraduate university, USD is known for its liberal arts programs. Most students looking for an engineering degree don’t think of USD, and most students attracted by USD’s reputation aren’t thinking of majoring in engineering. So the first challenge was identifying those students who might be interested in our offering and providing them with information about our programs. Most activities related to identifying prospects were executed by USD Undergraduate Admissions. Among the things they did to identify engineering candidates are: Karthi Vidhyalaya Matriculation School Kumbakonam • Send mailings to our top 100 feeder high schools and to high tech and magnet high schools. • Place advertisements featuring engineering

A Dynamic Learning Model for Matriculation Mathematics Accelerated pre-matriculation mathematics remediation programs are a popular strategy for improving the placement levels of underprepared students. Although limited assessments of such programs have been reported in the literature, most work is focused either on immediate placement level improvement or longitudinal indicators of student success. While valuable, both techniques offer no insight regarding the learning progression of students while participating in the program, which is of tremendous value in optimizing program policy, such as determining the ideal number of contact hours. Best Matriculation School The research described herein proposes a first-order dynamic learning model for describing students’ content acquisition process within accelerated remediation programs. Details regarding model formulation are presented within this work-in-progress paper. A brief evaluation of model efficacy is also conducted using data g