Journal of
Systemics, Cybernetics and Informatics
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ABSTRACTS


   





Behavior of Cell in Uniform Shear Flow Field between Rotating Cone and Stationary Plate
Shigehiro Hashimoto, Hiromi Sugimoto, Haruka Hino
(Pages: 1-7)

The behavior of a biological cell in a uniform shear flow between the rotating cone and the stationary plate has been observed in vitro. The cone and plate apparatus is mounted on a stage of an inverted phase contrast microscope to observe cells adhered to the plate under the shear flow. Deformation and migration of cells during exposure to the shear flow for 24 hours were traced with the time lapse images. Two kinds of cells were used in the test: C2C12 (mouse myoblast cell line), and HUVEC (human umbilical vein endothelial cell). The experimental results show that HUVEC tends to migrate downstream at the shear stress of 1 Pa. C2C12 tends to tilt vertically in the flow for 18 hours between 1 Pa and 2 Pa. HUVEC tends to be rounded at the shear stress of 2 Pa. The behavior of each isolated cell in the shear flow field has been able to be quantitatively observed by the cone and plate apparatus in vitro.




Teachers Continuing Professional Development: Trends in European Countries. Towards Teachers' Professionalism
Liliana Budkowska, Pawel Poszytek
(Pages: 8-12)

The article focuses on description of different approaches of European countries to the Continuing Professional Development of teachers that leads to certain recommendations on that matter.

The main division assumes the presence of centralised and decentralised systems for such development. However, it is neither clear nor easy to define, which system is used in the particular country. That is why the article covers more categories, even if some of them may overlap in certain conditions.

Having defined the system, the emphasis is put on its correlation with whether Continuing Professional Development is compulsory and to what extent or not.

That leads to the following point that concentrates on considering time during which trainings are conducted and the replacement needed.

The article describes also institutions that provide Continuing Professional Development. Among them, there is the Foundation for Development of the Education System1, which is presented more precisely.

Having established all the data from these parts of the article, it was possible to make recommendations that should contribute to improvement of Continuing Professional Development programmes.




Play, Connect and Learn: Using Mobile Phones to Improve Early Grade Reading Skills at Home
Ira Joshi
(Pages: 13-16)

Mobile technologies offer great scope and potential for learning in countries with moderate income rates, low literacy levels, poor educational opportunities and high ownership of mobile phones. The paper discusses the efforts made by Sesame Workshop in India to support children’s grade l and 2 reading skills, specifically foundational literacy and reading comprehension, using mobile phones at home. It provides the findings from a quasi-experimental design research conducted to evaluate the effectiveness of a mobile phone based reading application on the reading levels of children. A total of 627 children participated in the research, which used an adapted version of Early Grade Reading Assessment (EGRA) to measure children’s early grade reading skills, in their mother tongue. The findings indicate statistically significant gains for children in the intervention group on four of the six subtasks: letter name identification, syllable identification, familiar word reading and oral reading fluency. These findings support the growing literature on the effectiveness of engaging and developmentally appropriate content delivered through mobile phones to improve children’s reading skills.




May Parental Reading Behavior Explain the Gender Differences in Subteeners’ Reading Attitude?
Aniko Joó, Erzsébet Dani
(Pages: 17-22)

This paper presents the results of a research project which analyzed the impact of parental reading behavior on the gender differences in subteeners’ reading attitude. The applied theoretical approach is based on the tri-component view of reading attitude. A sample of 1633 (815 male and 786 female) students and their parents filled in a questionnaire on reading preferences and habits, and the students completed a reading attitude scale. Variance analyses (ANOVA) are used to determine the statistically significant differences. Independent variables of the measurement are materialized dimensions of reading, and parents’ paper-based/online reading habits, purpose and frequency. As assumed, girls are generally more influenced by parental reading habits and exhibit more favorable reading attitude if either parent has positive reading behavior. Boys’ reading attitude is far less influenced by behavioral patterns; nevertheless, the father’s impact is significantly stronger than that of the mother. In the light of the results, this paper will also give some thought, briefly, to what can be done; thereby, indicating some directions of further research.




Leadership and Literacy Processes in School Improvement Creating and Supporting a Community of Success: A Case Study Examining the Principal’s Role in the Reconstitution of a Campus to Transform Literacy and Learning
W. Todd Duncan, Lisa E. Colvin
(Pages: 23-28)

Any number of school districts in the U.S. are having to improve schools that have been underperforming by state and federal measures. Research has indicated that one of the ways to effectively improve school performance is by reconstituting the school (i.e. change the principal and the teachers in the particular school organization). This case study investigates the improvement effort of an urban elementary school in the greater Houston, Texas area. A principal with a track record of improving student achievement was brought in to change the performance of an elementary school that had spent several years on the federal improvement needed list and the state list of schools that had not met standard. The study investigates the actions of leadership taken by the new principal, the organizational vision cast by the principal, and the instructional support provided to the teachers toward improved student achievement. The study also investigates the perceptions of the teachers regarding the leadership and support provided by the principal, and the instructional expectations that school leadership and the teaching faculty have for literacy development.

The study notes the improvements made by the school in the two years after the school was reconstituted, especially the growth for the Hispanic and English Language Learner subgroups. Also noted is the additional work that still needs to be done for other subgroups particularly the African American subgroup. The results of the efforts of the school in this case study support over 30 years of research that demonstrates the importance of school leadership in improving teacher efficacy and leading the instructional direction of the school.




Rwandan Collaborative Model for Educator Capacity Building
Andrew Moore, Vincentie Nyangoma, Jaco Du Toit, Peter Wallet, Pascal Rukundo
(Pages: 29-35)

Collaboration between the Rwandan government, the University of Rwanda, and local industry to develop and deploy educator technology-integration professional development initiatives neatly follows the Triple Helix Model[1]. However, in this Rwandan initiative a fourth collaborative partner proved significant, the regional/global education community coordinated by UNESCO’s Regional Office for Eastern Africa. The ICT Essentials for Teachers’ Course was designed to exploit a blended-learning methodology, developed using Open Educational Resources and deployed by locally trained online facilitators. This paper presents a model of how effective collaboration between stakeholders can result in the quick and cost-effective development and deployment of educator training initiatives that are scalable.




Do You Know Where Your Students Are? Digital Supervision and Digital Privacy in Schools
Lorayne Robertson, Laurie Corrigan
(Pages: 36-42)

More students are now online at school because of several factors such as the increasing affordability of mobile devices; the rapid proliferation of low-cost or free educational applications; and because internet access is more widely available. When students are learning online, however, their personal information needs to be protected. Student supervision in the past focused on physical presence, but it must evolve now to include students in digital settings. Updated legislative policy alone cannot eliminate risks to digital privacy. Students, teachers, and parents need to become more aware of the privacy risks and all should build digital citizenship skills. The research presented in this paper is policy analysis that examines the availability and direction of digital supervision policies in Canada and the U.S. and then compares the findings to international policies and directions. The authors find key differences in policy approaches designed to supervise students online and protect their digital privacy. Based on this policy analysis, the authors recommend that more collaborative efforts are needed to protect students’ digital privacy and manage their online risks.




A General Case Study of Complexity Science: Analytical and Logical Interconnection Between Soft and Hard Sciences (Invited Paper)
Jack Jia-Sheng Huang, Yu-Heng Jan
(Pages: 43-48)

Complexity science is gaining popularity due to its unique approach to address convoluted and multi-dimentional problems. In this work, we present a general case study of complexity science by means of analytical and logical interconnection between soft and hard sciences. Hard sciences such as semiconductor technology and biology may branch out and offer useful analogous thinking for the study of soft sciences such as health care and social science.




Novel Application of Immobilized Bacillus Cells for Biotreatment of Furfural-Laden Wastewater
Haneen A. Khudhair, Zainab Z. Ismail
(Pages: 49-54)

Immobilization of growing bacterial cells was considered as an innovative technique and very effective in dealing with major environmental challenges for bioremediation of organics-loaded wastewater. This study was undertaken to investigate the aerobic biodegradation of furfural in aqueous solution by using immobilized Bacillus cells in spouted bed bioreactor. Bacillus cells were individually immobilized in the matrices of sodium alginate, guar-gum, and agar-agar; each was cross linked in polyvinyl alcohol. Immobilized cells exhibited efficient furfural degradation in several successive reuse batches up to 3 cycles without losing their degradation activity which could provide economic advantages when used in industrial-scale applications. Results of batch experiments in fluidized spouted bed bioreactor demonstrated that complete removal of furfural using immobilized Bacillus cells in the first and second cycles was achieved after 450 and 480 min, respectively. The removal efficiency of furfural was 100%, 100%, and 95% for the 1st, 2nd, and 3rd, cycles, respectively. Unlike the free cells, the potentiality of the immobilized cells is that they could be reused without reduction in their ability to degrade hazardous furfural. Additional advantage of immobilized cells compared to free cells, is their ability to tolerate high concentrations of furfural.




Reliable Sub-Nanosecond Switching of a Perpendicular SOT-MRAM Cell without External Magnetic Field
Viktor Sverdlov, Alexander Makarov, Siegfried Selberherr
(Pages: 55-59)

The steady increase in performance and speed of modern integrated circuits is continuously supported by constant miniaturization of complementary metal-oxide semiconductor (CMOS) devices. However, a rapid growth of the dynamic and stand-by power due to transistor leakages becomes a pressing issue.

A promising way to stop this trend is to introduce non-volatility. The development of an electrically addressable non-volatile memory combining high speed and high endurance is essential to achieve these goals. It is particularly promising to employ non-volatility in the main computer memory as a replacement of conventional volatile CMOS-based DRAM.

To further reduce the energy consumption, it is essential to replace caches (SRAM) in modern hierarchical multi-level processor memory structures with a non-volatile memory technology. The spin-orbit torque magnetic random access memory (SOT-MRAM) combines non-volatility, high speed, high endurance, and is thus suitable for applications in caches. However, its development is still impeded by the necessity of a static in-plane magnetic field.

We propose a magnetic field-free perpendicular SOT-MRAM, based on a cross-bar architecture and the use of two consecutive orthogonal sub-nanosecond current pulses. In this way small layout footprint and high integration density are guaranteed.




The Methodology and Implementation of Unique Technology Focused Entrepreneurship/Intrepreneurship Programs
Stephen A. Szygenda, Diana M. Easton
(Pages: 60-66)

This paper describes a unique methodology for technical entrepreneurship education and it’s application to real world situations. The methodology provides a general domain independent approach, which has evolved over a number of years, and been adopted in universities and technology start-ups. We believe that this approach can have additional domain specibic imact and one such case is presented herein.




Intelligent Fault Pattern Recognition of Aerial Photovoltaic Module Images Based on Deep Learning Technique
Xiaoxia Li, Qiang Yang, Wenjun Yan, Zhebo Chen
(Pages: 67-71)

The rise of photovoltaic industry has raised the difficulty of the operation and maintenance. Nowadays, the growing interest in the application of unmanned aerial vehicles (UAV) in civil monitoring and diagnostic applications has been observed. Such UAV-based inspection system can significantly improve the efficiency of system monitoring and fault detections. This paper presents an intelligent UAV-based inspection system for asset assessment and defect classification for large-scale PV systems. The aerial imagery data of PV modules increase the complexity of the detection by traditional pattern recognition, a novel method based on the deep learning and supervision is proposed, which could solve the low quality and distortion flexibly and reliably. A convolutional neural network (CNN) is adopted to address the defects classification. Extracting features by the pre-trained architecture Vgg16, the suggested solution added a full-connected layer and a SVM decision layer to classify the defects. Such pre-trained learning-based algorithm can meet the demand of the small datasets, and carry out a variety of deep features and condition classification in PV system, which can supervise with significantly promoted efficiency in comparison with the conventional methods. The proposed solution is evaluated through numerical experiments and the result confirms its improved performance.




Real-Time Implementation of Model Predictive Control in a Low-Cost Embedded Device
John Espinoza, Jorge Buele, Esteban X. Castellanos, Marco Pilatásig, Paulina Ayala, Marcelo V. García
(Pages: 72-77)

This document presents a general description of the implementation of a low-cost system for flow control. A preconditioning of the signal coming from the process to be controlled is carried out and, through Arduino UNO, data is acquired. Using this data in the embedded board Raspberry Pi 3, a predictive control by model (MPC) has been implemented in real time. The plant model is obtained using the identification tool of the MATLAB software. The design of the controller which are in the latest version of this software, has been developed in Simulink using the new complements made for this board. The experimental results show that despite the technical limitations and the high computational cost that this controller represents, both devices can work together and present high performance, robustness and good response in the presence of disturbances.




Real-Time Sentimental Polarity Classification on Live Social-Media
Khalid N. Alhayyan, Imran Ahmad
(Pages: 78-84)

In recent years, the popularity of social media networks has attracted the attention of researchers, government agencies, politicians and business world alike, as a powerful platform to explore real-time trends. The data generated by these networks offers an opportunity to investigate people's behaviors and activities, but the high velocity and low quality of this data poses some unique challenges. Twitter, an example of social media networks, is particularly popular for this purpose due to its easily accessible API that is open to use for research purposes. Different techniques can be used to analyze patterns from available data. One of such techniques for extracting subjective information from any text such as opinions on various topics is Sentiment Polarity Classification, which quantifies emotions embedded in texts and classifies them as positive, negative or neutral. The focus of this paper is on preparing and analyzing real-time twitter streams to detect real-time trends on a particular topic using Sentiment Polarity Classification. We have used StreamSensing approach and have performed a supervised machine learning on real-time high velocity data using Apache Spark micro-batching technology to classify the opinions and feelings of people in real-time. Appropriate experiments for processing high rate of incoming streams have been carefully designed and conducted on live twitter data. The outcomes of these experiments were analyzed and presented. The findings of this paper fell into two perspectives: theoretical and practical. The theoretical perspective is seen in testing and confirming the validity of StreamSensing approach as well as the introduction of a sentimental polarity algorithm, while practically; this approach can be employed to perform trend analyses on any real-time streams related to live events.




Information Modeling and Information Retrieval for the Internet of things (IoT) in Buildings
Renata Baracho, Izabella Cunha, Mário Lúcio Pereira Junior
(Pages: 85-91)

The ability to monitor and analyze real-time information generated by sensors and devices is a vitalto maximize employee effectiveness and productivity in organizations, reduce unscheduled downtime, increase production quality and minimize the risk of accidents. The implementation of aneffective smart building requires deep study of information systems, monitoring with data collection and analysis and reflection on concepts, representation, goals and occupations of buildings. This research is focused on the application of technologies within the domain of Architecture, Engineering and Construction (AEC), with the following objectives: to identify the current state of literature on the topics Information Modeling, Information Retrieval and Internet of Things (IoT) in buildings in the context of Information Science; discuss concepts and advances Smart Building, Building Automation, Intelligent Building and Information Modeling Building (BIM); and prepare a proposal for the implementation of IoT in a research laboratory of UFMG. The smart lab experiment is a proof of concept proposal that through practice makes simulations for real solutions like validation. The results demonstrate that the implementation of IoT provides new insights into the behavior of people and the environment, supporting the identification of standards and setting precedents for optimization.