ASETS: A SDN Empowered Task Scheduling System for HPCaaS on the Cloud

With increasing demands for High Performance Computing (HPC), new ideas and methods are emerged to utilize computing resources more efficiently. Cloud Computing appears to provide benefits such as resource pooling, broad network access and cost efficiency for the HPC applications. However, moving the HPC applications to the cloud can face several key challenges, primarily, the virtualization overhead, multi-tenancy and network latency. Software-Defined Networking (SDN) as an emerging technology appears to pave the road and provide dynamic manipulation of cloud networking such as topology, routing, and bandwidth allocation. This paper presents a new scheme called ASETS which targets dynamic configuration and monitoring of cloud networking using SDN to improve the performance of HPC applications and in particular task scheduling for HPC as a service on the cloud (HPCaaS). Further, SETSA, (SDN-Empowered Task Scheduler Algorithm) is proposed as a novel task scheduling algorithm for the offered ASETS architecture. SETSA monitors the network bandwidth to take advantage of its changes when submitting tasks to the virtual machines. Empirical analysis of the algorithm in different case scenarios show that SETSA has significant potentials to improve the performance of HPCaaS platforms by increasing the bandwidth efficiency and decreasing task turnaround time. In addition, SETSAW, (SETSA Window) is proposed as an improvement of the SETSA algorithm

Modeling and Characterization of Lymphatic Vessels Using a Lumped Parameter Approach

The lymphatic system is responsible for several vital roles in human body, one of which is maintaining fluid and protein balance. There is no central pump in the lymphatic system and the transport of fluid against gravity and adverse pressure gradient is maintained by the extrinsic and intrinsic pumping mechanisms. Any disruption of the lymphatic system due to trauma or injury can lead to edema. There is no cure for lymphedema partly because the knowledge of the function of the lymphatic system is lacking. Thus, a well-developed model of the lymphatic system is crucial to improve our understanding of its function. Here we used a lumped parameter approach to model a chain of lymphangions in series. Equations of conservation of mass, conservation of momentum, and vessel wall force balance were solved for each lymphangion computationally. Due to the lack of knowledge of the parameters describing the system in the literature, more accurate measurements of these parameters should be pursued to advance the model. Because of the difficulty of the isolated vessel and in-situ experiments, we performed a parameter sensitivity analysis to determine the parameters that affect the system most strongly. Our results showed that more accurate estimations of active contractile force and physiologic features of lymphangions, such as length/diameter ratios, should be pursued in future experiments. Also further experiments are required to refine the valve behavior and valve parameters

Modelling of Growth Profile of Three Probiotic Single Strain Starter Cultures (L.acidophilus (La-5), Bifidobacterium (BB-12), S.thermophilus (STB-01)) through Turbidity Measurement Technique

Probiotics are one or more mixture of viable microorganisms which have beneficial effects on animals and human beings through propagation gastrointestinal microflora. Some instances for health benefits of these products are: alleviating gastrointestinal disorders, diarrehea, food allergies, infection of Helicobacter pylori, lactose intolerance, candidiasis, serum cholesterol, and improving immune system balance, mineral uptake and protecting the consumer from different cancers such as colon, bladder and gastrointestinal cancers.To achieve these neutraceutical purposes, a large population of probiotics( 107- 108 cfu/g) should remain alive during storage of these products up to expiring date.In this research production of probiotic ABT yogurt is taken into consideration. Single strains of two probiotic starter cultures, Bifidobacterium( BB-12) and L. acidophilus(La-5), and one single strain of S. thermophilus (STB-01) for reducing the fermentation time are used. In probiotic products the method of counting probiotic bacteria have a significant effect. Traditional microbiological methods require wide range of time and a lots of facilities. Modelling of growth profile of bacteria with the data obtained from turbidity measurement would be a helpful method for fast counting of microbial communities. Keywords: analyze ; Broth media ; Colony Count Unit; Direct-Vat-Set(DVS); Durbin-Watson statistic

Grouping Gestures Promote Children's Effective Counting Strategies by Adding a Layer of Meaning Through Action

Preschoolers can often rattle off a long sequence of numbers in order, but have problems in reporting the exact number of objects even in a small set, and have trouble in comparing numerical relation of two sets that differ by exactly 1 item. The present study showed that representing and highlighting sets by showing a circular, enclosed diagram around them with or without a grouping gesture helps children to enhance their understanding of cardinality and to improve their overall math competence. Nighty-three preschool students, ages ranging from 3years-10 months to 4 years-9months (M= 51.82 months, SD= 3.56 months), from three public schools in Harlem, New York participated in this study. Children from each school were ranked based on their pre-test score on the Test of Early Mathematics Ability (TEMA-3), and were then assigned randomly to one of the three math comparison groups or the reading control group. Children in diagram-plus-gesture math group, were asked to draw a bubble by making a grouping gesture around each of the two sets on a touch screen device, indicate the number of fish in each bubble, and judge whether there were the same number of fish in each bubble, and in case the number was not the same, indicate which set had more fish. Children in the diagram only condition simply saw bubbles around sets without the need to do a grouping gesture around them. Children in the no diagram- no gesture condition neither saw a bubble nor did a grouping gesture. All participants played on the software for 4 sessions within a two-week time period and the data were examined microgenetically. Results showed that all children in the math comparison groups improved in their math scores during the game-play and improved in their overall math competence from pre- to post-test, unlike the children in the reading control group. More importantly, children who saw the circular diagram (bubbles) around sets with or without the grouping gesture outperformed children who never saw bubbles nor made a grouping gesture in their accuracy, understanding of cardinality, and overall math competence from pre to post. Further, children with lower executive functioning skills benefitted from performing the grouping gesture in addition to seeing the circular diagram. Gestures can have the same form as diagrams, and hence, they may carry information that is redundant with diagrams. Such redundancy reinforces the message by presenting information in two modalities-- a redundancy that may not be necessary for some, but beneficial to others (i.e. children with low executive functioning skills). Finally, over the course of game-play children who did the grouping gesture never counted the two sets together as one set when asked to compare their numerical relation-- a mistake many preschoolers make; children in the other groups made that mistake occasionally. Because gestures are actions and dynamic by nature, they appear to be especially suited for changing actions and promoting early counting skills

A Hybrid Data Mining Method for Customer Churn Prediction

The expenses for attracting new customers are much higher compared to the ones needed to maintain old customers due to the increasing competition and business saturation. So customer retention is one of the leading factors in companies’ marketing. Customer retention requires a churn management, and an effective management requires an exact and effective model for churn prediction. A variety of techniques and methodologies have been used for churn prediction, such as logistic regression, neural networks, genetic algorithm, decision tree etc.. In this article, a hybrid method is presented that predicts customers churn more accurately, using data fusion and feature extraction techniques. After data preparation and feature selection, two algorithms, LOLIMOT and C5.0, were trained with different size of features and performed on test data. Then the outputs of the individual classifiers were combined with weighted voting. The results of applying this method on real data of a telecommunication company proved the effectiveness of the method

Modeling the Number of Attacks in Multiple Sclerosis Patients Using Zero-Inflated Negative Binomial Model

Background and aims: Multiple sclerosis (MS) is an inflammatory disease of the central nervous system. The impact of the number of attacks on the disease is undeniable. The aim of this study was to analyze the number of attacks in these patients. Methods: In this descriptive-analytical study, the registered data of 1840 MS patients referred to the MS clinic of Ayatollah Kashani hospital in Isfahan were used. The number of attacks during the treatment period was defined as the response variable, age at diagnosis, sex, employment, level of education, marital status, family history, course of disease, and expanded disability as the explanatory variables. The analysis was performed using zero-inflated negative binomial model via Bayesian framework in OpenBUGS software. Results: Age at diagnosis (CI: -0.04, -0.20), marital status (CI: -0.56, 0.002), level of education (CI: -0.81, -0.26), Job (CIHousewives vs Employee=[0.04, 0.64], CIUnemployee vs Employee=[-1.10,0.008])), and course of disease (CI: -0.51, -0.08) had a significant effect on the number of attacks. In relapsing-remitting patients, the number of attacks was partial significantly affected by expanded disability status scale (EDSS) (CI: -0.019, 0.16). Conclusion: Aging, being single (never married), high education, and not having a job decrease the number of attacks; therefore, lower age, being married, primary education, and being a housewife increase the number of attacks. An interventional or educational program is suggested in order to prevent the occurrence of further attacks in high-risk groups of patients and to increase their chances of recovery. Keywords: Multiple sclerosis Attack Negative binomial Zero-inflated Markov chain Monte Carl

The Effects of Hand Tracking on User Performance: an experimental study of an object selection based memory game

Until recently, Virtual Reality (VR) applications relied on controllers to enable user interaction in virtual environments. With advances in tracking technology, HMDs are now able to track the movements of users’ hands in real-time with significantly greater accuracy, allowing us to interact with the digital world directly with our hands. However, it is not entirely clear how hand tracking affects users’ performance. In this study, we investigate user performance using an in-game analytics-based assessment methodology for a VR memory puzzle task. We conducted a within-subjects experiment with 30 participants in three conditions: 1- Hand-tracking, 2- Controller Without Haptics, and 3- Controller With Haptics. In all our measurements (correct order and pattern, correct pattern only, and trial completion) except for the initial selection time, participants performed best with hand tracking. The use of controllers with haptics did not outperform controllers without haptics in most measures, possibly because other feedback cues compensated for the lack of haptics. This study helps us better understand the three selected interactivity methods when used in VR, as well as the importance of naturalistic experience in interaction design

Our Nudges, Our Selves: Tailoring Mobile User Engagement Using Personality

To increase mobile user engagement, current apps employ a variety of behavioral nudges, but these engagement techniques are applied in a one-size-fits-all approach. Yet the very same techniques may be perceived differently by different individuals. To test this, we developed HarrySpotter, a location-based AR app that embedded six engagement techniques. We deployed it in a 2-week study involving 29 users who also took the Big-Five personality test. Preferences for specific engagement techniques are not only descriptive but also predictive of personality traits. The Adj. $R^2$ ranges from 0.16 for conscientious users (encouraged by competition) to 0.32 for neurotic users (self-centered and focused on their own achievements), and even up to 0.61 for extroverts (motivated by both exploration of objects and places). These findings suggest that these techniques need to be personalized in the future.Comment: 10 pages, 1 figure, 2 table

Analyzing the Effect of COVID-19 on Education by Processing Users’ Sentiments

COVID-19 infection has been a major topic of discussion on social media platforms since its pandemic outbreak in the year 2020. From daily activities to direct health consequences, COVID-19 has undeniably affected lives significantly. In this paper, we especially analyze the effect of COVID-19 on education by examining social media statements made via Twitter. We first propose a lexicon related to education. Then, based on the proposed dictionary, we automatically extract the education-related tweets and also the educational parameters of learning and assessment. Afterwards, by analyzing the content of the tweets, we determine the location of each tweet. Then the sentiments of the tweets are analyzed and examined to extract the frequency trends of positive and negative tweets for the whole world, and especially for countries with a significant share of COVID-19 cases. According to the analysis of the trends, individuals were globally concerned about education after the COVID-19 outbreak. By comparing between the years 2020 and 2021, we discovered that due to the sudden shift from traditional to electronic education, people were significantly more concerned about education within the first year of the pandemic. However, these concerns decreased in 2021. The proposed methodology was evaluated using quantitative performance metrics, such as the F1-score, precision, and recall

Quality of Randomization in Clinical Trials Published in Persian Journals of Medical Sciences Indexed in Scopus During 2013-2017

Background and Objectives Randomization is one of the principles of correct clinical trial. The aim of this study was to determine the quality of randomization in the published articles of clinical trials in the Persian-language journals indexed in Scopus. Methods In this cross-sectional study, all clinical trials published in Persian journals indexed in Scopus during 2013-2017 were evaluated in terms of randomization using the Jadad scale. The score of the randomization item of this scale ranges from 0 to 2, with 0, 1, and 2 indicating poor, moderate, and good quality. Results A total of 452 articles were evaluated. Random allocation was indicated in 423 articles (93.6%). Simple random assignment and blocked methods were used in 42.8% and 22% of randomizations, respectively. The randomization method was unknown in 34% and an incorrect method was used for randomization in 5.3% of the articles. According to the Jadad scale, 56.4% of the articles had good, 36.9% had moderate, and 6.6% had poor quality in terms of randomization. Methodologists were consulted in 40.7% of the articles, and their contributions led to increased transparency in the randomization report (P = 0.007). Conclusion The randomization method and its report are missing in many clinical trials. Therefore, considering the importance of randomization in validating the results of these studies, journals editors and researchers should pay attention to the quality of randomization and its report. Keywords: Clinical trial , Randomization , Scopus , Persian journals , Jadad scal