Short Answer Grading (SAG) is the task of scoring students’ answers for applications such as examinations or e-learning. Most existing SAG systems predict scores based only on answers, and critical evaluation criteria rubrics are ignored, which plays a crucial role in evaluating real-world situations. In this paper, we propose semi-supervised method to train neural model. We extract keyphrases ...

The article presents a hierarchical framework, which supports website quality assessment. The framework is composed of a hierarchical structure of criteria and subcriteria and makes use of the Analytic Hierarchy Process to enhance criterion and subcriterion weight value assessment. To validate the framework we conducted an experiment, which involved the assessment of the websites of the three c...

Currently Hough transform and its variants are the most common methods for detecting analytic curves from a binary edge image. However, these methods do not scale well when applied to complex noisy images where correct data is very small compared to the amount of incorrect data. We propose a Genetic Algorithm in combination with the Randomized Hough Transform, along with a di erent scoring func...

A cohort of 19 international polygraph examiner trainees at the Texas Department of Public Safety Polygraph School used the Empirical Scoring System (Blalock, Cushman & Nelson, 2009; Krapohl, 2010; Nelson, Krapohl & Handler, 2008) to evaluate 100 confirmed event-specific criminal investigation polygraph examinations. Bootstrap analytic procedures were used to calculate accuracy profiles and sta...

In this paper we present a Newton scoring algorithm for the maximum likelihood separation and direction of arrival estimation of constant modulus signals, using a calibrated array. The main technical step is the inversion of the Fisher information matrix, and an analytic formula for the update step in the Newton method. We present the algorithm based on the derived update and discuss potential ...

Analysis of gene expression patterns in gastric cancer (GC) can help to identify a comprehensive panel of gene biomarkers for predicting clinical outcomes and to discover potential new therapeutic targets. Here, a multi-step bioinformatics analytic approach was developed to establish a novel prognostic scoring system for GC. We first identified 276 genes that were robustly differentially expres...

Identification of reliable predictive biomarkers and new therapeutic targets is a critical step for significant improvement in patient outcomes. Here, we developed a multi-step bioinformatics analytic strategy to mine large omics and clinical data to build a prognostic scoring system for predicting the overall survival (OS) of lung adenocarcinoma (LuADC) patients. In latter we first identified ...

Several benefits of using scoring rubrics in performance assessments have been proposed, such as increased consistency of scoring, the possibility to facilitate valid judgment of complex competencies, and promotion of learning. This paper investigates whether evidence for these claims can be found in the research literature. Several databases were searched for empirical research on rubrics, res...

Stromal tumour infiltrating lymphocytes (sTILs) are a strong prognostic marker in triple negative breast cancer (TNBC). Consistency scoring sTILs is good and was excellent when an internet-based aid developed by the TIL-WG used to score cases reproducibility study. This study aimed evaluate of assessment using this from routine practice explore potential tool overcome variability scoring. Twent...

abstract objective: to investigate the anesthesia-postoperative awakening time (at) of hepatitis- related cirrhosis patients and their relations to grading scores, portal venous pressure (pvp), prealbumin (pa), and age, to predict postoperative at and provide a basis for adjustment of anesthetic doses during operation. methods: atotal of 71 patients with hepatic cirrhosis and hypersplenism at a...