Scholarly

Predictive Maintenance of Industrial Shredders: Efficient Operation through Real-Time Monitoring Using Statistical Machine Learning

Year: 2021 Volume: 15 Issue: 12 401 - 405 Pages

Abstract: The shredding of waste materials is a key step in the recycling process towards circular economy. Industrial shredders for waste processing operate in very harsh operating conditions, leading to the need of frequent maintenance of critical components. The maintenance optimization is particularly important also to increase the machine’s efficiency, thereby reducing the operational costs. In this work, a monitoring system has been developed and deployed on an industrial shredder located at a waste recycling plant in Austria. The machine has been monitored for several months and methods for predictive maintenance have been developed for two key components: the cutting knives and the drive belt. The large amount of collected data is leveraged by statistical machine learning techniques, thereby not requiring a very detailed knowledge of the machine or its live operating conditions. The results show that, despite the wide range of operating conditions, a reliable estimate of the optimal time for maintenance can be derived. Moreover, the trade-off between the cost of maintenance and the increase in power consumption due to the wear state of the monitored components of the machine is investigated. This work proves the benefits of real-time monitoring system for efficient operation of industrial shredders.

Impact on Course Registration and SGPA of the Students of BSc in EEE Programme due to Online Teaching during the COVID-19 Pandemic

Year: 2021 Volume: 15 Issue: 12 839 - 848 Pages

Authors:
Muhibul Haque Bhuyan

Abstract: Most educational institutions were compelled to switch over to the online mode of teaching, learning, and assessment due to the lockdown when the corona pandemic started around the globe in the early part of the year 2020. However, they faced a unique set of challenges in delivering knowledge and skills to their students as well as formulating a proper assessment policy. This paper investigates whether there is an impact on the student Semester Grade Point Average (SGPA) due to the online mode of teaching and learning assessment at the Department of Electrical and Electronic Engineering (EEE) of Southeast University (SEU). Details of student assessments are discussed. Then students’ grades were analyzed to find out the impact on SGPA based on the z-test by finding the standard deviation (). It also pointed out the challenges associated with the online classes and assessment strategies to be adopted during the online assessment. The student admission, course advising, and registration statistics were also presented in several tables and analyzed based on the change in percentage to observe the impact on it due to the pandemic. In summary, it was observed that the students’ SGPAs are not affected but student course advising and registration were affected slightly by the pandemic. Finally, the paper provides some recommendations to improve the online teaching, learning, assessment, and evaluation system.

Implication of Taliban’s Recent Relationship with Neighboring Countries and Its Impact on the Current Peace Process

Year: 2021 Volume: 15 Issue: 12 835 - 838 Pages

Authors:
Lutfurahman Aftab

Abstract: The Taliban’s relationships with the neighboring countries are a complex political issue that local people interpret one way, and politicians have different perceptions; therefore, it is a current issue that needs to be analyzed broadly and impartially. In this article, we investigate the Taliban’s current relationships with the neighboring countries, as well as look at the effects these relationships have on the current peace negotiations in Doha, which began on September 12, 2020. The issue of Taliban and the current peace process has turned to be the center-of-attention for most of the neighboring countries, and every country has opened new pages in their foreign policies because after the Taliban-US peace agreement, the neighboring countries are meticulously and closely observing the situation and they believe that the Taliban is on the verge to tighten their grips on the future political power of Afghanistan. Every neighboring country of Afghanistan has political, economic, and social interests in this land-locked country. The Taliban’s current role within the peace talks and anticipated future position within the Afghan government will have great political, economic, and social implications on countries in the region as they assess their foreign policies. As these countries move to form closer ties with the Taliban, the government of Afghanistan is worried that this may hinder the peace process. Afghanistan has long blamed Pakistan for sheltering the Taliban and providing safe havens for the terrorist groups, including Al Qaeda, and the recent visits of Taliban’s delegations to Islamabad, Pakistan, have raised concern among government officials in Afghanistan who believe that the Taliban is not independent in their decisions, and for every step they take, are consulting with Pakistan’s political leadership.

Thermosensitive Hydrogel Development for Its Possible Application in Cardiac Cell Therapy

Year: 2021 Volume: 15 Issue: 12 140 - 145 Pages

Abstract: Ischemic events can culminate in acute myocardial infarction with irreversible cardiac lesions that cannot be restored due to the limited regenerative capacity of the heart. Tissue engineering proposes therapeutic alternatives by using biomaterials to resemble the native extracellular medium combined with healthy and functional cells. This research focused on developing a natural thermosensitive hydrogel, its physical-chemical characterization and in vitro biocompatibility determination. Hydrogels’ morphological characterization was carried out through scanning electron microscopy and its chemical characterization by employing Infrared Spectroscopy technic. In addition, the biocompatibility was determined using fetal human ventricular cardiomyocytes cell line RL-14 and the MTT cytotoxicity test according to the ISO 10993-5 standard. Four biocompatible and thermosensitive hydrogels were obtained with a three-dimensional internal structure and two gelation times. The results show the potential of the hydrogel to increase the cell survival rate to the cardiac cell therapies under investigation and lay the foundations to continue with its characterization and biological evaluation both in vitro and in vivo models.

Hardware Error Analysis and Severity Characterization in Linux-Based Server Systems

Year: 2021 Volume: 15 Issue: 12 479 - 485 Pages

Abstract: Current server systems are responsible for critical applications that run in different infrastructures, such as the cloud, physical machines, and virtual machines. A common challenge that these systems face are the various hardware faults that may occur due to the high load, among other reasons, which translates to errors resulting in malfunctions or even server downtime. The most important hardware parts, that are causing most of the errors, are the CPU, RAM, and the hard drive - HDD. In this work, we investigate selected CPU, RAM, and HDD errors, observed or simulated in kernel ring buffer log files from GNU/Linux servers. Moreover, a severity characterization is given for each error type. Understanding these errors is crucial for the efficient analysis of kernel logs that are usually utilized for monitoring servers and diagnosing faults. In addition, to support the previous analysis, we present possible ways of simulating hardware errors in RAM and HDD, aiming to facilitate the testing of methods for detecting and tackling the above issues in a server running on GNU/Linux.

COVID-19 Pandemic Influence on Toddlers and Preschoolers’ Screen Time

Year: 2021 Volume: 15 Issue: 12 250 - 254 Pages

Abstract: The average daily screen time (ST) has been increasing in children, even at young ages. This seems to be associated with a higher incidence of neurodevelopmental disorders, and as the time of exposure increases, the greater is the functional impact. This study aims to compare the daily ST of toddlers and preschoolers previously and during the COVID-19 pandemic. A questionnaire was applied by telephone to parents/caregivers of children between 1 and 5 years old, followed up at four primary care units belonging to the Group of Primary Health Care Centers of Western Porto, Portugal. A total of 520 children were included: 52.9% male, mean age 39.4 ± 13.9 months. The mean age of first exposure to screens was 13.9 ± 8.0 months, and most of the children were exposed to more than one screen daily. Considering the WHO recommendations, before the COVID-19 pandemic, 385 (74.0%) and 408 (78.5%) children had excessive ST during the week and the weekend, respectively; during the lockdown, these values increased to 495 (95.2%) and 482 (92.7%). Maternal education and both the child's median age and the median age of first exposure to screens had a statistically significant association with excessive ST, with OR 0.2 (p = 0.03, CI 95% 0.07-0.86), OR 1.1 (p = 0.01, 95% CI 1.05-1.14) and OR 0.9 (p = 0.05, 95% CI 0. 87-0.98), respectively. Most children in this sample had a higher than recommended ST, which increased with the onset of the COVID-19 pandemic. These results are worrisome and point to the need for urgent intervention.

Incentive Policies to Promote Green Infrastructure in Urban Jordan

Year: 2021 Volume: 15 Issue: 12 338 - 344 Pages

Authors:
Zayed Freah Zeadat

Abstract: The wellbeing of urban dwellers is strongly associated with the quality and quantity of green infrastructure. Nevertheless, urban green infrastructure is still lagging in many Arab cities, and Jordan is no exception. The capital city of Jordan, Amman, is becoming more urban dense with limited green spaces. The unplanned urban growth in Amman has caused several environmental problems such as urban heat islands, air pollution and lack of green spaces. This study aims to investigate the most suitable drivers to leverage the implementation of urban green infrastructure in Jordan through qualitative and quantitative analysis. The qualitative research includes an extensive literature review to discuss the most common drivers used internationally to promote urban green infrastructure implementation in the literature. The quantitative study employs a questionnaire survey to rank the suitability of each driver. Consultants, contractors and policymakers were invited to fill the research questionnaire according to their judgments and opinions. Relative Importance Index has been used to calculate the weighted average of all drivers and the Kruskal-Wallis test to check the degree of agreement among groups. This study finds that research participants agreed that indirect financial incentives (i.e., tax reductions, reduction in stormwater utility fee, reduction of interest rate, density bonus etc.) are the most effective incentive policy whilst granting sustainability certificate policy is the least effective driver to ensure widespread of UGI is elements in Jordan.

Freighter Aircraft Selection Using Entropic Programming for Multiple Criteria Decision Making Analysis

Year: 2021 Volume: 15 Issue: 12 70 - 77 Pages

Authors:
C. Ardil

Abstract: This paper proposes entropic programming for the freighter aircraft selection problem using the multiple criteria decision analysis method. The study aims to propose a systematic and comprehensive framework by focusing on the perspective of freighter aircraft selection. In order to achieve this goal, an integrated entropic programming approach was proposed to evaluate and rank alternatives. The decision criteria and aircraft alternatives were identified from the research data analysis. The objective criteria weights were determined by the mean weight method and the standard deviation method. The proposed entropic programming model was applied to a practical decision problem for evaluating and selecting freighter aircraft. The proposed entropic programming technique gives robust, reliable, and efficient results in modeling decision making analysis problems. As a result of entropic programming analysis, Boeing B747-8F, a freighter aircraft alternative ( a3), was chosen as the most suitable freighter aircraft candidate.

Advanced Jet Trainer and Light Attack Aircraft Selection Using Composite Programming in Multiple Criteria Decision Making Analysis Method

Year: 2021 Volume: 15 Issue: 12 376 - 381 Pages

Authors:
C. Ardil

Abstract: In this paper, composite programming is discussed for aircraft evaluation and selection problem using the multiple criteria decision analysis method. The decision criteria and aircraft alternatives were identified from the literature review. The importance of criteria weights was determined by the standard deviation method. The proposed model is applied to a practical decision problem for evaluating and selecting advanced jet trainer and light attack aircraft. The proposed technique gives robust and efficient results in modeling multiple criteria decisions. As a result of composite programming analysis, Hürjet, an advanced jet trainer and light attack aircraft alternative (a3), was chosen as the most suitable aircraft candidate.

Decision-Making Strategies on Smart Dairy Farms: A Review

Year: 2021 Volume: 15 Issue: 11 132 - 139 Pages

Abstract: Farm management and operations will drastically change due to access to real-time data, real-time forecasting and tracking of physical items in combination with Internet of Things (IoT) developments to further automate farm operations. Dairy farms have embraced technological innovations and procured vast amounts of permanent data streams during the past decade; however, the integration of this information to improve the whole farm decision-making process does not exist. It is now imperative to develop a system that can collect, integrate, manage, and analyze on-farm and off-farm data in real-time for practical and relevant environmental and economic actions. The developed systems, based on machine learning and artificial intelligence, need to be connected for useful output, a better understanding of the whole farming issue and environmental impact. Evolutionary Computing (EC) can be very effective in finding the optimal combination of sets of some objects and finally, in strategy determination. The system of the future should be able to manage the dairy farm as well as an experienced dairy farm manager with a team of the best agricultural advisors. All these changes should bring resilience and sustainability to dairy farming as well as improving and maintaining good animal welfare and the quality of dairy products. This review aims to provide an insight into the state-of-the-art of big data applications and EC in relation to smart dairy farming and identify the most important research and development challenges to be addressed in the future. Smart dairy farming influences every area of management and its uptake has become a continuing trend.

Simulation with Uncertainties of Active Controlled Vibration Isolation System for Astronaut’s Exercise Platform

Year: 2021 Volume: 15 Issue: 11 361 - 368 Pages

Abstract: In a task to assist NASA in analyzing the dynamic forces caused by operational countermeasures of an astronaut’s exercise platform impacting the spacecraft, an active proportional-integral-derivative controller commanding a linear actuator is proposed in a vibration isolation system to regulate the movement of the exercise platform. Computer simulation shows promising results that most exciter forces can be reduced or even eliminated. This paper emphasizes on parameter uncertainties, variations and exciter force variations. Drift and variations of system parameters in the vibration isolation system for astronaut’s exercise platform are analyzed. An active controlled scheme is applied with the goals to reduce the platform displacement and to minimize the force being transmitted to the spacecraft structure. The controller must be robust enough to accommodate the wide variations of system parameters and exciter forces. Computer simulation for the vibration isolation system was performed via MATLAB/Simulink and Trick. The simulation results demonstrate the achievement of force reduction with small platform displacement under wide ranges of variations in system parameters.

Methodology of Personalizing Interior Spaces in Public Libraries

Year: 2021 Volume: 15 Issue: 11 331 - 337 Pages

Authors:
Baharak Mousapour

Abstract: Creating public spaces which are tailored for the specific demands of the individuals is one of the challenges for the contemporary interior designers. Improving the general knowledge as well as providing a forum for all walks of life to exploit is one of the objectives of a public library. In this regard, interior design in consistent with the demands of the individuals is of paramount importance. Seemingly, study spaces, in particular, those in close relation to the personalized sector, have proven to be challenging, according to the literature. To address this challenge, attributes of individuals, namely, perception of people from public spaces and their interactions with the so-called spaces, should be analyzed to provide interior designers with something to work on. This paper follows the analytic-descriptive research methodology by outlining case study libraries which have personalized public libraries with the investigation of the type of personalization as its primary objective and (I) recognition of physical schedule and the know-how of the spatial connection in indoor design of a library and (II) analysis of each personalized space in relation to other spaces of the library as its secondary objectives. The significance of the current research lies in the concept of personalization as one of the most recent methods of attracting people to libraries. Previous research exists in this regard, but the lack of data concerning personalization makes this topic worth investigating. Hence, this study aims to put forward approaches through real-case studies for the designers to deal with this concept.

A Comprehensive Survey on Machine Learning Techniques and User Authentication Approaches for Credit Card Fraud Detection

Year: 2021 Volume: 15 Issue: 11 459 - 472 Pages

Abstract: With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Educational Experiences in Engineering in the COVID-19 Era and Their Comparative Analysis: Spain, March-June 2020

Year: 2021 Volume: 15 Issue: 11 795 - 801 Pages

Abstract: In March 2020, in Spain, a sanitary and unexpected crisis caused by COVID-19 was declared. All of a sudden, all degrees, classes and evaluation tests and projects had to be transformed into online activities. However, the chaotic situation generated by a complex operation like that, executed without any well-established procedure, led to very different experiences and, finally, results. In this paper, we are describing three experiences in two different Universities in Madrid. On the one hand, the Technical University of Madrid, a public university with little experience in online education was considered. On the other hand, Alfonso X el Sabio University, a private university with more than five years of experience in online teaching was involved. All analyzed subjects were related to computer engineering. Professors and students answered a survey and personal interviews were also carried out. Besides, the professors’ workload and the students’ academic results were also compared. From the comparative analysis of all these experiences, we are extracting the most successful strategies, methodologies, and activities. The recommendations in this paper will be useful for courses during the next months when the sanitary situation is still affecting an educational organization. While, at the same time, they will be considered as input for the upcoming digitalization process of higher education.

Emotion Detection in Twitter Messages Using Combination of Long Short-Term Memory and Convolutional Deep Neural Networks

Year: 2021 Volume: 15 Issue: 9 438 - 445 Pages

Authors:
B. Golchin
N. Riahi

Abstract: One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.

Psychodidactic Strategies to Facilitate the Flow of Logical Thinking in the Preparation of Academic Documents

Year: 2021 Volume: 15 Issue: 9 744 - 747 Pages

Abstract: The preparation of academic documents, such as thesis, articles and research projects, is one of the requirements of the higher educational level. These documents demand the implementation of logical argumentative thinking which is experienced and executed with difficulty. To mitigate the effect of these difficulties we designed a thesis seminar, with which we have seven years of experience. It is taught in a graduate program in Psychology at the National Autonomous University of Mexico. In this seminar we use the Toulmin model as a mental heuristic and for the application of a set of psychodidactic strategies that facilitate the elaboration of the plot and culmination of the thesis. The efficiency in obtaining the degree in the groups exposed to the seminar has increased by 94% compared to the 10% that existed in the generations that were not exposed to the seminar. In this article we will emphasize the psychodidactic strategies used. The Toulmin model alone does not guarantee the success achieved. A set of actions of a psychological nature (almost psychotherapeutic) and didactics of the teacher also seem to contribute. These are actions that derive from an understanding of the psychological, epistemological and ontogenetic obstacles and the most frequent errors in which thought tends to fall when it is demanded a logical course. We have grouped the strategies into three groups: 1) strategies to facilitate logical thinking, 2) strategies to strengthen the scientific self and 3) strategies to facilitate the act of writing the text. In this work we delve into each of them.

An Overview of Technology Availability to Support Remote Decentralized Clinical Trials

Year: 2021 Volume: 15 Issue: 9 228 - 234 Pages

Abstract: Developing new medicine and health solutions and improving patient health currently rely on the successful execution of clinical trials, which generate relevant safety and efficacy data. For their success, recruitment and retention of participants are some of the most challenging aspects of protocol adherence. Main barriers include: i) lack of awareness of clinical trials; ii) long distance from the clinical site; iii) the burden on participants, including the duration and number of clinical visits, and iv) high dropout rate. Most of these aspects could be addressed with a new paradigm, namely the Remote Decentralized Clinical Trials (RDCTs). Furthermore, the COVID-19 pandemic has highlighted additional advantages and challenges for RDCTs in practice, allowing participants to join trials from home and not depending on site visits, etc. Nevertheless, RDCTs should follow the process and the quality assurance of conventional clinical trials, which involve several processes. For each part of the trial, the Building Blocks, existing software and technologies were assessed through a systematic search. The technology needed to perform RDCTs is widely available and validated but is yet segmented and developed in silos, as different software solutions address different parts of the trial and at various levels. The current paper is analyzing the availability of technology to perform RDCTs, identifying gaps and providing an overview of Basic Building Blocks and functionalities that need to be covered to support the described processes.

Separation of Composites for Recycling: Measurement of Electrostatic Charge of Carbon and Glass Fiber Particles

Year: 2021 Volume: 15 Issue: 10 309 - 314 Pages

Abstract: Composite waste from manufacturing can consist of different fiber materials, including blends of different fiber. Commercially, the recycling of composite waste is currently limited to carbon fiber waste and recycling glass fiber waste is currently not economically viable due to the low cost of virgin glass fiber and the reduced mechanical properties of the recovered fibers. For this reason, the recycling of hybrid fiber materials, where carbon fiber is blended with glass fibers, cannot be processed economically. Therefore, a separation method is required to remove the glass fiber materials during the recycling process. An electrostatic separation method is chosen for this work because of the significant difference between carbon and glass fiber electrical properties. In this study, an experimental rig has been developed to measure the electrostatic charge achievable as the materials are passed through a tube. A range of particle lengths (80-100 µm, 6 mm and 12 mm), surface state conditions (0%SA, 2%SA and 6%SA), and several tube wall materials have been studied. A polytetrafluoroethylene (PTFE) tube and recycled fiber without sizing agent were identified as the most suitable parameters for the electrical separation method. It was also found that shorter fiber lengths helped to encourage particle flow and attain higher charge values. These findings can be used to develop a separation process to enable the cost-effective recycling of hybrid fiber composite waste.

Adaptive Control Strategy of Robot Polishing Force Based on Position Impedance

Year: 2021 Volume: 15 Issue: 9 317 - 323 Pages

Abstract: Manual polishing has problems such as high labor intensity, low production efficiency and difficulty in guaranteeing the consistency of polishing quality. The use of robot polishing instead of manual polishing can effectively avoid these problems. Polishing force directly affects the quality of polishing, so accurate tracking and control of polishing force is one of the most important conditions for improving the accuracy of robot polishing. The traditional force control strategy is difficult to adapt to the strong coupling of force control and position control during the robot polishing process. Therefore, based on the analysis of force-based impedance control and position-based impedance control, this paper proposed a type of adaptive controller. Based on force feedback control of active compliance control, the controller can adaptively estimate the stiffness and position of the external environment and eliminate the steady-state force error produced by traditional impedance control. The simulation results of the model show that the adaptive controller has good adaptability to changing environmental positions and environmental stiffness, and can accurately track and control polishing force.

A Numerical Study of the Interaction between Residual Stress Profiles Induced by Quasi-Static Plastification

Year: 2021 Volume: 15 Issue: 9 306 - 310 Pages

Abstract: One of the most relevant phenomena in manufacturing is the residual stress state development through the manufacturing chain. In most cases, the residual stresses have their origin in the heterogenous plastification produced by the processes. Although a few manufacturing processes have been successfully approached by numerical modeling, there is still lack of understanding on how these processes' interactions will affect the final stress state. The objective of this work is to analyze the effect of the grinding procedure on the residual stress state generated by a quasi-static indentation. The model consists in a simplified approach of shot peening, modeling four cases with variations in indenter size and force. This model was validated through topography, measured by optical 3D focus-variation. The indentation model configured with two loads was then exposed to two grinding procedures and the result was analyzed. It was observed that the grinding procedure will have a significant effect on the stress state.

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