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We explore the power of parallelism in a stochastic search for global optimum in high-dimensional optimization problems. This search, that often navigates a large solution space through a Markov-Chain Monte Carlo (MCMC) process, needs to make stochastic decisions at every step and needs to escape from local optima. Through parallelism, we are able to survey an entire neighbourhood (all states with Hamming distance of 1) to make efficient moves, use multiple replicas at different temperatures, such as in parallel tempering, or deploy a population of replicas at the same temperature. Once combined, these methods of parallelism can yield 100x to 10,000x speedups.

A handheld wireless optical reader for the detection of infectious diseases at the point of care is presented. The device is battery powered and interfaces with paper-based biosensors for the quantification of concentration in biological fluids using colorimetric analysis. The results are wirelessly transmitted to a smartphone. The device has been successfully tested with various concentrations of Influenza A nucleoprotein.

Diabetic Retinopathy (DR) is a polygenic disorder issue that affects human eyes. Bruise to the blood vessels of the photosensitive tissue of the retina causes this complication. It’s most frequent in patients who had diabetes for more than ten years. This downside is going on in several individuals worldwide. However, the number of medical practitioners and also the tools needed for the detection of DR are very less for serving the mass population. In this paper, we have proposed DRDNet (Diabetic Retinopathy Diagnosis Network), a neural network framework based on capsule networks (CapsNets) for DR diagnosis. Experiments on a dataset with 1,265 images demonstrate that CapsNet shows better accuracy and convergence behavior for the complex data than the state-ofthe-art techniques. The proposed DRDNet performs with an overall accuracy of 80.59% for five class, as compared to the closest competitor with an accuracy of 75.83%. We performed a study on a mixed dataset for two class and found that testing accuracy was 80.59%. We have also done training on a two class model and testing on other unseen datasets. Moreover, we observed that DRDNet has much higher confidence for the predicted probabilities as compared to other state-of-the-art techniques.

According to the characteristics of the online test paper composition, the genetic algorithm is preferred as the core algorithm. However, there are some problems in the traditional genetic algorithm when it is being used, such as low efficiency in the later search period and easy to fall into the local optimal solution. To solve this problem, this paper makes some optimizations for the traditional genetic algorithm's coding scheme, initial population, fitness function and genetic operator. After the improvement, the composing test paper module based on genetic algorithm was finally implemented in java language through seven parts.

Concerning intelligent paper composition, the article puts forward an improved genetic algorithm (GA) based on the multi-population division. According to the ideas of population division, the genes of individuals in the population which control the same characters are further divided into the same sub population so that they can be performed by the genetic operators. In order to avoid the local optimum, the optimal solution of each sub population is selected to be recombined global optimum. Compared with the simple genetic algorithm (SGA), this algorithm significantly reduces the search space of the problem solution and accelerates convergence speed. Finally, the algorithm is verified in the problem of intelligent paper composition and the results indicate that the algorithm has obviously improved the quality of the intelligent paper composition compared with the SGA.

Serious gaming is a novel and innovative educational strategy that has been gaining ground in nursing education in the recent years. This review explores the existing serious games in nursing education that offer the development the development of nursing competencies. A literature search was conducted in the following databases: CINAHL, PubMed, Scopus, WebofScience, ScienceDirect, PsychInfo, ProQuest and Embase from Year 2005 to 2015, to include papers that reported intervention studies on serious games in nursing education. Twenty-six papers were included in the review. Two of the reviewed articles were qualitative studies and twenty-four were quantitative studies. The findings were categorized into four main themes that relate to the core competencies of nursing: procedural skills, health assessment skills, communication skills and clinical reasoning skills. A range of core competencies can be developed through the use of serious game in nursing education.

Information connectivity and retrieval has a role in our daily lives. The most pervasive source of online information is databases. The amount of data is growing at rapid rate and database technology is improving and having a profound effect. Almost all online applications are storing and retrieving information from databases. One challenge in supplying the public with wider access to informational databases is the need for knowledge of database languages like Structured Query Language (SQL). Although the SQL language has been published in many forms, not everybody is able to write SQL queries. Another challenge is that it may not be practical to make the public aware of the structure of the database. There is a need for novice users to query relational databases using their natural language. To solve this problem, many natural language interfaces to structured databases have been developed. The goal is to provide more intuitive method for generating database queries and delivering responses. Social media makes it possible to interact with a wide section of the population. Through this medium, and with the help of Natural Language Processing (NLP) we can make the data of the Atmospheric Radiation Measurement Data Center (ADC) more accessible to the public. We propose an architecture for using Apache Lucene/Solr [1], OpenML [2,3], and Kafka [4] to generate an automated query/response system with inputs from Twitter5, our Cassandra DB, and our log database. Using the Twitter API and NLP we can give the public the ability to ask questions of our database and get automated responses.

Dirty paper coding has been shown to achieve the capacity region of a Gaussian broadcast channel. However, it is a complicated scheme and assumes knowledge of the interfering signals at the transmitter. In this paper, we compare the downlink user capacity of dirty paper coding and time-division multiple access (TDMA) in a single cell of a cellular network with single antennas at the transmitter and each of the receivers. Here we define user capacity as the expected value of the number of users/receivers to which the transmitter can simultaneously transmit at an equal rate. The system that we consider selects the users to which it will transmit from a population of mobile users. We derive closed-form expressions for the downlink user capacity using dirty paper coding and TDMA under a total transmit power constraint and a common target information rate at all the mobile users, as the user population tends to infinity. The results indicate that DPC provides a gain of at most 12% in user capacity over TDMA for the scenarios that we consider. Thus TDMA may be an attractive alternative to DPC because of the complexity of the latter.

In industry an engineer is often required to keep a logbook for recording developments within projects. In higher education, logbooks are a commonly used tool thought to be one that encourages active independent learning and reflective thinking. In School of Engineering, at University of Portsmouth, paper and more recently online logbooks have been in use for recording work for final year projects and project based learning tasks. The work presented here benefits from a unique opportunity within the School of Engineering, where online logbooks alongside traditional paper based logbooks are being used within final year projects. A recent cohort of students (N=127) on ENG600 project module was given the option, through their Supervisors, to use paper logbooks and or online logbooks for recording their work. This work aims to investigate the use of both paper and online logbooks. A mix of Qualitative Research methods and quantitative techniques will be used in this project. The use of content analysis will provide an insight into student reflections and their motivations for using their logbook. Furthermore focus groups, involving live editing of documents in an individual and collaborative fashion, will be used to gather more data for analysis. Quantitative methods (questionnaire, analytics and quantitative content analysis) will also be used in this study. When this work is completed, it will provide guidance and comparison on using the two types of logbooks, backed by knowledge of student motivations and approaches.

We conducted a field study in a non-profit resource-scarce primary care clinic to investigate its current paper-based practices. The goal is to inform the design and deployment of an impending Electronic Medical Record (EMR) system at the clinic. The clinic serves a local vulnerable, low-income population who are insured through local community health plans. We identified problems encountered by the providers in their use of the current paper-based system. We also found that providers customized their work practices so that they can serve the underserved population better. Based on the tacit knowledge that they acquired in the workplace over time, they adapted their patient care to align with the patients' prescribed health benefits. In this way, the patients were able to receive timely and proper medical care. We also propose technological recommendations for the impending EMR system to address the problems with current practices and to support the adapted practices specifically customized for the low socioeconomic patients.

Transcatheter aortic valve replacement (TAVR) has become a more utilized procedure to perform on patients deemed too frail to handle the demands of a standard open heart approach. How to determine frailty in cardiac patients, particularly TAVR candidates, has been difficult to objectively quantify. The purpose of this research was to statistically measure which outcome tool most accurately depicted frailty in patients who underwent TAVR. Our study was performed based on the comparison between two approaches: the Kansas City Cardiomyopathy Questionnaire (KCCQ), which is the current national assessment standard conducted, and the Fried scale, which tests five frailty domains: gait speed, grip strength, low physical activity, exhaustion, and weight loss. Each domain of the Fried scale was explored and compared alongside the KCCQ with those frail/not frail to the TAVR patients with complications and deaths. Low physical activity was the strongest single-frailty domain predictor. Three statistical models – Logistic Regression, Support Vector Machines (SVM), and Artificial Neural Network (ANN), were used to build classification systems to predict complication conditions. Comparing static numbers, such as Sensitivity, Specificity and Area under Curve (AUC), it is believed that composed models based on the five domains of the Fried scale were able to demonstrate more accurate results than the traditional KCCQ approach. Both SVM and ANN showed significant performance, but further research is necessary to confirm specificity for the Fried scale with the TAVR population.

This paper mainly discussed the implementation of genetic algorithm on generating test paper for English class. The existing genetic algorithm is optimized through the analysis on principles and key technologies of standard genetic algorithms. We use matrix encoding to improve the coding method. It can storage various properties of indicators and fitness of individual papers and improve computing speed. By the improvement of genetic operators, we propose a sectional multi-point strategy for mutation operator. A large proportion of hybridization and mutation are adopted to maintain the diversity of population, which avoid the knowledge conflict in generating paper and rapid shrinking when searching space. It also raises the speed of approximating to the global optimum and improves the comprehensive performance. Simultaneously, to ensure the best individual parent enter the offspring, we adopt the selection method based on fitness sorting during copy, to make the selection on the generation be the best strategy. The experiments results verify the effectiveness and practicality of our algorithm.

Government documents such as welfare applications or accounting records are often considered mundane artifacts that signify shared practice and routine. In this paper we examine cases where these "everyday documents" are sites of creation and contestation of the dominant information order. We argue that the circulation of everyday government documents opens up the possibility for a population to gaze back and "see" the state. In three cases, we show how the materiality of everyday documents in welfare schemes takes center-stage in mediating public participation in India and in the US.

With the widespread use of the Tablet computer in school and at home, there is an ongoing transition of reading from print to screen. This study examines the reading comprehension of linear text passages with three media platforms. 23 university students take part in this research. Results indicate that both scores of multiple choice and summarization of reading on Computer screen are significantly better than on Tablet computer. Suggesting that ICT familiarity might be an important factor to the reading performance.

Vehicle to Infrastructure (V2I) networks can help managing different on-the-road applications and services, especially where the vehicles population is low and Internet access is needed for messaging, alerts, entertainment. Accessing a network through a proper technology requires the possibility of establishing connections with a minimum quality level; besides, a mechanism for switching from a network with poor performance to a better one by means of a so-called Vertical HandOver (VHO) may result of paramount importance. In this work we propose a switching mechanism based on sensing and processing of some physical/access/networking parameters in order to choose the technologies allowing the minimization of outages.

The purpose of this study was to compare data collected via online surveys to via paper-and-pencil ones in mental health fields. Two groups of participants completed the Adult Adaptation Inventory (AAI) and Self-rating depression scale (SDS) either in online format or in paper-and-pencil format independently. Data collected via paper-and-pencil surveys had more missing data than Internet-based ones. As for internal consistency, there were no significant differences in AAI between both two groups, while internal consistency of SDS in the online format was much higher than in the paper-and-pencil format. There was measurement invariance of both two scales across the two conditions. Finally, there were no significant differences in mean scores of both two scales between both two formats. The basic similarity of the properties across the two conditions suggests the viability of the Internet-based surveys for assessing mental health status of adults.

Traditional test paper generating algorithms have some shortcomings, such as slow generating speed, low success probability and low generating quality. The population search strategy in Genetic Algorithm (GA) provides a very suitable solution for multi-objective optimization, so applying it to the issue of test paper auto-generating can achieve good results. In this paper, we study the issue of test paper generation and propose the mathematical model and object function. Then some improvements are made in Simple GA for test paper generation. Based on the algorithm, a system is designed and implemented.

This paper presents the idea of exam script analysis and the design to provide it as well as the support for examiners to mark exams written using pen and paper devices. It also describes partial implementation going on. Pen and paper devices capture the traces of pen movement (called digital ink), allowing the answers to be reorganized independent from paper format, analyzed and marked semi-automatically under the examiner's supervision. Furthermore, digital ink carries time stamp for each stroke so that we can use this information to analyze the question answering process of the examinees such as revisions in the answer given for a question, the time taken in answering a question and so on. This information also allows us to consider the appropriateness of the exam design and improve it.

This paper proposes an intelligent algorithm to generating test paper based on genetic algorithm, and provides a set of schemes of making papers of different degree of difficulties display in normal distribution. The algorithm adopts a new decimal system of subsection code, improves the traditional method of initializing the population and optimizes course of search. The experiment proves that this algorithm has better performance thus is more practical.

A high quality test paper auto-generating is generally at the cost of considerable time. In order to handle the contradiction between quality and speed of combination, an improved subsection-single-point crossover and mutation GA based on real segment coding and condition matrix is proposed in the thesis. In the design of genetic operators roulette wheel selection, subsection-single-point crossover and mutation policy are synthetically used. And the population can be evolved continuously by the optimal-store policy. The algorithm has been proved feasible and effective through test and comparison between other algorithms. At last the validating system enhances the users' condition constraints for test paper through manual inching, thus the system is more simple and practical.

Agent-oriented design is one of the most active areas in the field of deployment of web-based distance education, and test is a popular measurement tool of learnerspsila knowledge in order to verify the learnerpsilas level of understanding and select corresponding educational strategy. In this paper, an innovative approach to seamless integration of the particle swarm optimization (PSO) and multi-agent system (MAS) is proposed. In order to generate a test paper automatically, a modified genetic particle swarm optimization (GPSO) is presented, in which the values of parameters will be decreased linearly with the number of iterations for improving the late convergence rate. For the implementation of GPSO based on multi-agent system, a core agents TPAgent (TPA) is provided to undertake the operations of GPSO and will control the evolution operations of each generation of population. To keep communication between different nodes at a minimum cost, fitness evaluation tasks are implemented by the TPAgents at local nodes, only the local minimum fitness and the corresponding best particle are sent to center node so as to get the global best particle in the parallel computing environment. For avoiding the prematurity, the global best particle will be dispatched to remote node randomly. Based on the JADE, a prototype system is setup , and the simulation results show that the proposed approach is feasible and robust.

In an ecosystem, coexistence of competing species is always transient due to unavoidable fluctuations of their population and interactions. In this letter, we use stochastic simulation method to investigate the variation of each species' population and the relation between the lifetime and its reaction rate of the specie. The simulation shows that the predator of the weakest specie always goes extinct firstly. Our finding provides a new evidence for the law of the “weakest” specy survival.

This paper describes a strategy to follow whilst playing the Rock-Paper-Scissors game. Instead of making a biased decision, a rule is adopted where the outcomes of the game from the last few turns are observed and then a deterministic decision is made. Such a strategy is encoded into a genetic string and a genetic algorithm works on a population of such strings. Good strings are produced in later generations. Such a strategy is found to be successful, and its efficiency is demonstrated by testing the strategy against both systematic and human strategies.

According to the feature that Genetic Algorithm (GA) is adapted to requirement of Culture Algorithms (CA) framework, GA is as the population space of CA and these

The paper deals with the phosphorus removal in a wastewater treatment plant in accordance with the legislation. The treatment plant in question is one that supplies a city with a population of 250,000–300,000 inhabitants. At the same time, the phosphorus removal must also keep the other components of the wastewater (ammonium, organic substances) within legal limits. The treatment plant was modeled with the ASM2d. The authors make an analysis of methods of reducing the total phosphorus concentration below the limit required by law, considering the two components: inorganic phosphorus and organic phosphorus. The first strategy proposed in the paper is the control of the inorganic phosphorus concentration by addition of ferric chloride. In the second strategy, a control loop of suspended solids concentration (TSS) measured at the output of biological reactors is added. The third strategy introduces in addition a control loop of ammonium concentration in the effluent. The results are obtained in numerical simulation.

A new family of B-staged, epoxy mica paper tapes has been developed. These tapes have been in commercial use for several years and have proved themselves to have low cost, excellent electrical properties and have been free from dermatitis problems.

For a number of years, various games have been used as an educational tool at different academic levels, especially in primary education. However, only recently games that teach coding and algorithmic thinking or even broader, computational thinking, emerged. Initiatives like Hour of Code and similar online activities or block-based programming games popularized the field, while at the same time, projects like CSUnplugged showed that the “idea of programming” can be learned even without using the computer. In this paper, we present our experience so far in creating and implementing different unplugged activities that teach students of different age levels, from early primary school to the university students, the simple programming concepts and algorithms. As a part of Science, Technology, Engineering, Mathematics and Computer Science (STEM- C) outreach program named SUZA - From school to science and the academic community at University of Zagreb Faculty of Electrical Engineering and Computing, Croatia, we conducted a number of game-like activities based on graph paper programming, block-based programming and using the existing board games. Although this is a work in progress project, the participant reactions so far, collected through interviews and questionnaires, indicated that the conducted activities were well accepted by students and their teachers. We also received a number of useful feedback comments and proposals, such as to expand the activities to include the homework part, or to make them more physical and relocate them outdoors.

This Research Full Paper presents the results of a longitudinal study about confidence and academic performance conducted at a large, R1, university over the course of a semester. We surveyed male (N = 226) and female (N = 67) students six times throughout the course of the semester and once after final grades were released. Each time, we asked students four questions designed to gauge students’ overall confidence. Using a modified latent growth curve analysis, we found distinctively different patterns in confidence trajectories between students in CS-1, CS-2, CS-3, and CS-4; the four consecutive introductory courses. We found that students’ confidence tended to show a significant decrease across all confidence variables for all four courses, though some courses showed a stronger decrease than others. We found a similar decline pattern for gender such that males initially reported higher confidence than females, but also showed a steeper decrease in confidence after receiving final grades. This declining trend was also predicted by grades, such that individuals who earned higher grades at the end of the semester initially began the semester with higher confidence, but these individuals also showed a steeper decrease in confidence after receiving their final grades. This work has implications for researchers interested in developing interventions designed to help students gain confidence when they need it most and for those interested in the relationship between confidence and retention.

This short paper summarizes the content of a practical training dedicated to the susceptibility of operational amplifiers to electromagnetic disturbances. The typical failure mechanisms of this type of device are characterized and compared on two commercial components. An analog behavioral model is then derived to predict the susceptibility of this device in various configuration. The extent version of this summary can be found in [1].

Activity sequencing is one of the deficits that autism children encounter. One of the essential skills that involve activity sequencing is toilet training which is difficult, cumbersome and sometimes never achieved for autistic children. This paper presents the requirement elicitation of Toilet Training Sequencing (TTS) wearable watch to provide customized support for autism children in toilet training. The presented prototype will help autistic children to dispense the paper based activity sequencing and thus increase the adaptation of the child with any place. The requirement elicitation techniques were conducted in collaboration with non-profit specialized centers in serving children with autism in Riyadh, Saudi Arabia "Mother of Faisal Autism Center (MFAC)". The results of the semi-structured interview, field observation and focus group are provided. The TTS prototype is demonstrated to show its applicability and effectiveness, it also includes the use of visual supports to diminish effort and time.

Nowadays the smart pen either write on a digital pad or they write on the standard Anoto dot pattern paper. The digital pen is lacking to convert the written text into editable document. These pens are mostly concentrating on taking the image of the written text. Few pens are written on any type of paper and converts into document. They were able to correct the spelling mistakes of the user but the grammatical mistakes were unknown by the pen. This paper proposes an idea to correct the grammatical errors and correct the spelling mistakes by parsing and having a training data set stored in the in the database which ultimately make the pen smarter and intelligent. This pen will learn by itself as to what kind of mistake the user is doing frequently and this ultimately will lead to efficient and faster results.

The purpose of this Research Full Paper is to investigate the role of pre-college characteristics, resources, and experiences in shaping engineering students’ experiences in college. Previous research has shown that students’ pre-college characteristics (e.g., socioeconomic indicators, race/ethnicity, gender) inform their experiences in college, as well as their academic and social outcomes. For example, research suggests that students from low-socioeconomic status (SES) backgrounds participate in co-curricular activities at lower rates than their high-SES counterparts. In this study, we hypothesize that precollege characteristics (e.g., race, gender, legacy status), resources (e.g., access to college counselors or private tutors), and experiences (e.g., participation in pre-college engineering programs) combine to inform how students are socialized into college broadly, and into engineering specifically. Using survey data collected from 998 undergraduate engineering students, we conducted a set of nested multiple regression models to investigate the relationships between students’ pre-college characteristics and both their college experiences and outcomes. Results offer some support for our hypotheses that some precollege characteristics, resources, and experiences, such as gender and college course taking in high school, are significant predictors of undergraduate engineering students’ college experiences, such as students’ general socializing experiences and feedback seeking behaviors. However counterintuitive findings suggest a need to further investigate how some characteristics, resources, and experiences inform students’ experiences and outcomes in college.

In this Research to Practice Full Paper, we analyzed 60,427 student-semester entries from 12,053 engineering students, enrolled at a Hispanic Serving Institution (HSI) over 8 years, to investigate contextually relevant factors of student academic success. We examined the relation of student semester Grade Point Average (GPA) with the following factors: living on campus or off campus, being enrolled part-time or fulltime, Hispanic citizen vs. undocumented, being first-generation college student, financial need, and transfer status. When appropriate, we also considered the role of race and ethnicity within each of the factors. In addition to the t-test to compare the average semester GPAs, we also calculated the effect size in the cases were the difference in GPA was significant. The results indicated the difference between the average semester GPA was significant, with the exception living on or off campus for Asian students. However, in all cases but being enrolled part-time or fulltime, the effect size was small. Interestingly, undocumented Hispanic students had a higher GPA than Hispanic citizens.