Search results for: logistics support

Authors: Sy-Wei Lo, Chi-Heng Yu

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A new design of aerostatic thrust bearing is proposed for high static stiffness. The bearing body, which is mead of polymer covered with metallic membrane, is held by a circular ring. Such a support helps form a concave air gap to grasp the air pressure. The polymer body, which can be made rapidly by either injection or molding is able to provide extra damping under dynamic loading. The smooth membrane not only serves as the bearing surface but also protects the polymer body. The restrictor is a capillary inside a silicone tube. It can passively compensate the variation of load by expanding the capillary diameter for more air flux. In the present example, the stiffness soars from 15.85 N/µm of typical bearing to 349.85 N/µm at bearing elevation 9.5 µm; meanwhile the load capacity also enhances from 346.86 N to 704.18 N.

Keywords: aerostatic, bearing, polymer, static stiffness

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Authors: Menna Brown, Tania Domun

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Digital health interventions are effective across a wide array of health conditions spanning physical health, lifestyle behaviour change, and mental health and wellbeing; furthermore, they are rapidly increasing in volume within both the academic literature and society as commercial apps continue to proliferate the digital health market. However, adherence and engagement to digital health interventions remains problematic. Technology-based personalised and tailored reminder strategies can support engagement to digital health interventions. Interventions which support individuals’ mental health and wellbeing are of critical importance in the wake if the COVID-19 pandemic. Student and young person’s mental health has been negatively affected and digital resources continue to offer cost effective means to address wellbeing at a population level. Develop a databank of digital co-produced tailored messages to support engagement to a range of digital health interventions including those focused on mental health and wellbeing, and lifestyle behaviour change. Qualitative research design. Participants discussed their views of health and wellbeing, engagement and adherence to digital health interventions focused around a 12-week wellbeing intervention via a series of focus group discussions. They worked together to co-create content following a participatory design approach. Three focus group discussions were facilitated with (n=15) undergraduate students at one Welsh university to provide an empirically derived, co-produced, databank of (n=145) tailored messages. Messages were explored and categorised thematically, and the following ten themes emerged: Autonomy, Recognition, Guidance, Community, Acceptance, Responsibility, Encouragement, Compassion, Impact and Ease. The findings provide empirically derived, co-produced tailored messages. These have been made available for use, via ‘ACTivate your wellbeing’ a digital, automated, 12-week health and wellbeing intervention programme, based on acceptance and commitment therapy (ACT). The purpose of which is to support future research to evaluate the impact of thematically categorised tailored messages on engagement and adherence to digital health interventions.

Keywords: digital health, engagement, wellbeing, participatory design, positive psychology, co-production

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Authors: Dalicia Bouallouche, Jean-Baptiste Vioix, Stéphane Millot, Eric Busvelle

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When researchers or logistics software developers deal with vehicle routing optimization, they mainly focus on minimizing the total travelled distance or the total time spent in the tours by the trucks, and maximizing the number of visited customers. They assume that the upstream real data given to carry the optimization of a transporter tours is free from errors, like customers’ real constraints, customers’ addresses and their GPS-coordinates. However, in real transporter situations, upstream data is often of bad quality because of address geocoding errors and the irrelevance of received addresses from the EDI (Electronic Data Interchange). In fact, geocoders are not exempt from errors and could give impertinent GPS-coordinates. Also, even with a good geocoding, an inaccurate address can lead to a bad geocoding. For instance, when the geocoder has trouble with geocoding an address, it returns those of the center of the city. As well, an obvious geocoding issue is that the mappings used by the geocoders are not regularly updated. Thus, new buildings could not exist on maps until the next update. Even so, trying to optimize tours with impertinent customers GPS-coordinates, which are the most important and basic input data to take into account for solving a vehicle routing problem, is not really useful and will lead to a bad and incoherent solution tours because the locations of the customers used for the optimization are very different from their real positions. Our work is supported by a logistics software editor Tedies and a transport company Upsilon. We work with Upsilon's truck routes data to carry our experiments. In fact, these trucks are equipped with TOMTOM GPSs that continuously save their tours data (positions, speeds, tachograph-information, etc.). We, then, retrieve these data to extract the real truck routes to work with. The aim of this work is to use the experience of the driver and the feedback of the real truck tours to validate GPS-coordinates of well geocoded addresses, and bring a correction to the badly geocoded addresses. Thereby, when a vehicle makes its tour, for each visited customer, the vehicle might have trouble with finding this customer’s address at most once. In other words, the vehicle would be wrong at most once for each customer’s address. Our method significantly improves the quality of the geocoding. Hence, we achieve to automatically correct an average of 70% of GPS-coordinates of a tour addresses. The rest of the GPS-coordinates are corrected in a manual way by giving the user indications to help him to correct them. This study shows the importance of taking into account the feedback of the trucks to gradually correct address geocoding errors. Indeed, the accuracy of customer’s address and its GPS-coordinates play a major role in tours optimization. Unfortunately, address writing errors are very frequent. This feedback is naturally and usually taken into account by transporters (by asking drivers, calling customers…), to learn about their tours and bring corrections to the upcoming tours. Hence, we develop a method to do a big part of that automatically.

Keywords: driver experience feedback, geocoding correction, real truck tours

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for easy creation and classification of institutional risk profiles supporting endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support set up of the most important risk factors. Subsequently, risk profiles employ risk factors classifier and associated configurations to support digital preservation experts with a semi-automatic estimation of endangerment group for file format risk profiles. Our goal is to make use of an expert knowledge base, accuired through a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation of risk factors for a requried dimension for analysis. Using the naive Bayes method, the decision support system recommends to an expert the matching risk profile group for the previously selected institutional risk profile. The proposed methods improve the visibility of risk factor values and the quality of a digital preservation process. The presented approach is designed to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and values of file format risk profiles. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert and to define its profile group. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: linked open data, information integration, digital libraries, data mining

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Authors: Youmen Chaaban, Abdallah Abu-Tineh

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This article examines the development of a professional development (PD) model for educator growth and learning that is embedded into the school context. The School based Support Program (SBSP), designed for the Qatari context, targets the practices, knowledge, and skills of both school leadership and teachers in an attempt to improve students’ learning outcomes. Key aspects of the model include the development of learning communities among teachers, strong leadership that supports school improvement activities, and the use of research-based PD to improve teacher practices and student achievement. This paper further presents the results of a qualitative study examining the perceptions of nineteen instructional coaches about the strengths of the PD program, the challenges they face in their day-to-day implementation of the program, and their suggestions for the betterment of the program’s implementation and outcomes. Data were collected from the instructional coaches through open-ended surveys followed by focus group interviews. The instructional coaches reported several strengths, which were compatible with the literature on effective PD. However, the challenges they faced were deeply rooted within the structure of the program, in addition to external factors operating at the school and Ministry of Education levels. Thus, a general consensus on the way the program should ultimately develop was reached.

Keywords: situated professional development, school reform, instructional coach, school based support program

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Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

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In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: decision support system, data mining, knowledge discovery, data discovery, fuzzy logic

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Authors: Sofiane Bendoukha, Daniel Moldt, Hayat Bendoukha

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Workflow concepts are essential for the development of remote sensing applications. They can help users to manage and process satellite data and execute scientific experiments on distributed resources. The objective of this paper is to introduce an approach for the specification and the execution of complex scientific workflows in Cloud-like environments. The approach strives to support scientists during the modeling, the deployment and the monitoring of their workflows. This work takes advantage from Petri nets and more pointedly the so-called reference nets formalism, which provides a robust modeling/implementation technique. RENEWGRASS is a tool that we implemented and integrated into the Petri nets editor and simulator RENEW. It provides an easy way to support not experienced scientists during the specification of their workflows. It allows both modeling and enactment of image processing workflows from the remote sensing domain. Our case study is related to the implementation of vegetation indecies. We have implemented the Normalized Differences Vegetation Index (NDVI) workflow. Additionally, we explore the integration possibilities of the Cloud technology as a supplementary layer for the deployment of the current implementation. For this purpose, we discuss migration patterns of data and applications and propose an architecture.

Keywords: cloud computing, scientific workflows, petri nets, RENEWGRASS

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Authors: Yushen Dai, Tao Deng, Miaoying Chen, Baoqin Huang, Yan Ji, Yongshen Feng, Shaofei Liu, Dongmei Zhong, Tao Zhang, Lifeng Zhang

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Background: Detection and diagnosis are prerequisites for early interventions in the care of children with Autism Spectrum Disorder (ASD). However, few studies have focused on this topic. Aim: This study aims to characterize the timing from symptom detection to intervention in children with ASD and to identify the potential predictors of early detection, diagnosis, and intervention. Methods and procedures: A cross-sectional survey was conducted with 314 parents of children with ASD in Guangzhou, China. Outcomes and Results: This study found that most children (76.24%) were diagnosed within one year after detection, and 25.8% of them did not receive the intervention after diagnosis. Predictors to ASD diagnosis included ASD-related symptoms identified at a younger age, more serious symptoms, and initial symptoms with abnormal development and sensory anomalies. ASD-related symptoms observed at an older age, initial symptoms with the social deficit, sensory anomalies, and without language impairment, parents as the primary caregivers, family with lower income and less social support utilization increased the odds of the time lag between detection and diagnosis. Children whose fathers had a lower level of education were less likely to receive the intervention. Conclusions and Implications: The study described the time for detection, diagnosis, and interventions of children with ASD. Findings suggest that the ASD-related symptoms, the timing at which symptoms first become a concern, primary caregivers’ roles, father’s educational level, and the family economic status should be considered when offering support to improve early detection, diagnosis, and intervention. Helping children and their families take full advantage of support is also important.

Keywords: autism spectrum disorder, child, detection, diagnosis, intervention, social support

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Authors: Ala Hanetite

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The purpose of this article is to present, by means of a model, the determinants of organisational culture which influence creativity and innovation. A literature study showed that a model, based on the open systems theory and the work of Schein, can offer a holistic approach in describing organisational culture. The relationship between creativity, innovation and culture is discussed in this context. Against the background of this model, the determinants of organisational culture were identified. The determinants are strategy, structure, support mechanisms, behaviour that encourages innovation, and open communication. The influence of each determinant on creativity and innovation is discussed. Values, norms and beliefs that play a role in creativity and innovation can either support or inhibit creativity and innovation depending on how they influence individual and group behaviour. This is also explained in the article.

Keywords: attitudes, creativity, innovation, organisational culture

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Authors: Eric Sitorus, Septian Prahastudhi, Turgod Nainggolan, Erwin Riyanto

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Mining by block or panel caving is a mining method that takes advantage of fractures within an ore body, coupled with gravity, to extract material from a predetermined column of ore. The caving column is weakened from beneath through the use of undercutting, after which the ore breaks up and is extracted from below in a continuous cycle. The nature of this method induces cyclical stresses on the pillars of excavations as stress is built up and released over time, which has a detrimental effect on both the installed ground support and the rock mass itself. Ground support capacity, especially on the production where excavation void ratio is highest, is subjected to heavy loading. Strain above threshold of the elongation of support capacity can yield resulting in damage to excavations. Geotechnical engineers must evaluate not only the remnant capacity of ground support systems but also investigate depth of rock mass yield within pillars, backs and floors. Ground Penetrating Radar (GPR) is a geophysical method that has the ability to evaluate rock mass damage using electromagnetic waves. This paper illustrates a case study from the Grasberg mining complex where non-invasive information on the depth of damage and condition of the remaining rock mass was required. GPR with 100 MHz antenna resolution was used to obtain images of the subsurface to determine rehabilitation requirements prior to recommencing production activities. The GPR surveys were used to calibrate the reflection coefficient response of varying rock mass conditions to known Rock Quality Designation (RQD) parameters observed at the mine. The calibrated GPR survey allowed site engineers to map subsurface conditions and plan rehabilitation accordingly.

Keywords: block caving, ground penetrating radar, reflectivity, RQD

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Authors: Elsayeda M. Elgaml, Dina M. Ibrahim, Elsayed A. Sallam

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Association rule mining is one of the most important fields of data mining and knowledge discovery. In this paper, we propose an efficient multiple support frequent pattern growth algorithm which we called “MSFP-growth” that enhancing the FP-growth algorithm by making infrequent child node pruning step with multiple minimum support using maximum constrains. The algorithm is implemented, and it is compared with other common algorithms: Apriori-multiple minimum supports using maximum constraints and FP-growth. The experimental results show that the rule mining from the proposed algorithm are interesting and our algorithm achieved better performance than other algorithms without scarifying the accuracy.

Keywords: association rules, FP-growth, multiple minimum supports, Weka tool

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Authors: Azita Ramezani, Atousa Ramezani

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In the ever-escalating landscape of windows malware the necessity for pioneering defense strategies turns into undeniable this study introduces an avant-garde approach fusing the capabilities of clustering random forests and support vector machines SVM to combat the intricate web of cyber threats our fusion model triumphs with a staggering accuracy of 98.67 and an equally formidable f1 score of 98.68 a testament to its effectiveness in the realm of windows malware defense by deciphering the intricate patterns within malicious code our model not only raises the bar for detection precision but also redefines the paradigm of cybersecurity preparedness this breakthrough underscores the potential embedded in the fusion of diverse analytical methodologies and signals a paradigm shift in fortifying against the relentless evolution of windows malicious threats as we traverse through the dynamic cybersecurity terrain this research serves as a beacon illuminating the path toward a resilient future where innovative fusion models stand at the forefront of cyber threat defense.

Keywords: fusion models, cyber threat defense, windows malware, clustering, random forests, support vector machines (SVM), accuracy, f1-score, cybersecurity, malicious code detection

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Authors: M. Abdallah

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Urban development requires deep excavations near buildings and other structures. Deep excavation has become more a necessity for better utilization of space as the population of the world has dramatically increased. In Lebanon, some urban areas are very crowded and lack spaces for new buildings and underground projects, which makes the usage of underground space indispensable. In this paper, a numerical modeling is performed using the finite element method to study the deep excavation-diaphragm wall soil-structure interaction in the case of nonlinear soil behavior. The study is focused on a comparison of the results obtained using different support systems. Furthermore, a parametric study is performed according to the remoteness of the structure.

Keywords: deep excavation, ground anchors, interaction soil-structure, struts

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Authors: Ismail Karaca, Ridvan Saracoglu, Omer Soner

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Fuzzy Logic, an advanced method to support decision-making, is used by various scientists in many disciplines. Fuzzy programming is a product of fuzzy logic, fuzzy rules, and implication. In marine science, fuzzy programming for ships is dramatically increasing together with autonomous ship studies. In this paper, a program to support the decision-making process for ship navigation has been designed. The program is produced in fuzzy logic and rules, by taking the marine accidents and expert opinions into account. After the program was designed, the program was tested by 46 ship accidents reported by the Transportation Safety Investigation Center of Turkey. Wind speed, sea condition, visibility, day/night ratio have been used as input data. They have been converted into a risk factor within the Fuzzy Logic Designer application and fuzzy rules set by marine experts. Finally, the expert's meteorological risk factor for each accident is compared with the program's risk factor, and the error rate was calculated. The main objective of this study is to improve the navigational safety of ships, by using the advance decision support model. According to the study result, fuzzy programming is a robust model that supports safe navigation.

Keywords: calculation of risk factor, fuzzy logic, fuzzy programming for ship, safety navigation of ships

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Authors: Yavuz Unal, Kemal Polat, H. Erdinc Kocer

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In this study, a decision support system comprising three stages has been proposed to detect the disc abnormalities of the lumbar region. In the first stage named the feature extraction, T2-weighted sagittal and axial Magnetic Resonance Images (MRI) were taken from 55 people and then 27 appearance and shape features were acquired from both sagittal and transverse images. In the second stage named the feature weighting process, k-means clustering based feature weighting (KMCBFW) proposed by Gunes et al. Finally, in the third stage named the classification process, the classifier algorithms including multi-layer perceptron (MLP- neural network), support vector machine (SVM), Naïve Bayes, and decision tree have been used to classify whether the subject has lumbar disc or not. In order to test the performance of the proposed method, the classification accuracy (%), sensitivity, specificity, precision, recall, f-measure, kappa value, and computation times have been used. The best hybrid model is the combination of k-means clustering based feature weighting and decision tree in the detecting of lumbar disc disease based on both sagittal and axial MR images.

Keywords: lumbar disc abnormality, lumbar MRI, lumbar spine, hybrid models, hybrid features, k-means clustering based feature weighting

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Authors: Amit Prakash Singh, Shyamli Singh, Chavi Srivastav

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This paper presents the idea of Internet of Thing (IoT) for the infrastructure of smart cities. Internet of Thing has been visualized as a communication prototype that incorporates myriad of digital services. The various component of the smart cities shall be implemented using microprocessor, microcontroller, sensors for network communication and protocols. IoT enabled systems have been devised to support the smart city vision, of which aim is to exploit the currently available precocious communication technologies to support the value-added services for function of the city. Due to volume, variety, and velocity of data, it requires analysis using Big Data concept. This paper presented the various techniques used to analyze big data using machine learning.

Keywords: IoT, smart city, embedded systems, sustainable environment

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Authors: Urszula Malaga-Toboła, Marek Gugała, Rafał Kornas, Robert Rusinek, Marek Gancarz

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The work focused on presenting the elements that determine the quality of fresh milk in the context of the quality of its transport. The quality of the raw material depends on the quality of transport. Milk transport involves many activities in which, apart from the temperature and sterility of the means of transport, it is important not to expose the raw material to shocks. Recently, there have been changes in the milk supply chain, thus affecting the logistics processes between its links. Based on the conducted research and analyses, it was found that the condition of the road surface on which milk is transported affects its quality. For the T1 milk transport route- gravel roads of very poor and poor quality, the lowest number of bacteria and the highest number of somatic cells, fat content, and temperature of the transported milk were obtained. A well-organized integrated transport system is a real need for most companies today. The analysis showed significant differences in the quality of milk delivered to the dairy.

Keywords: fresh milk, transport, milk quality, dairy

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Authors: Hatice Yildirim

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This study was an investigation into the role of teaching assistants (TAs) for deaf pupils in an English primary school. This study aimed to provide knowledge about how TAs support deaf pupils in mainstream schools in England. It is accepted that TAs have an important role in the inclusion of students with disabilities in mainstream schools. However, there has been a lack of attention paid to the role of TAs for deaf pupils in the literature. A qualitative case study approach was used to address the research questions. Twelve semi-structured classroom observations and six semi-structured interviews were carried out with four TAs and two teachers in one English mainstream primary school. The data analysis followed a thematic analysis framework. The results indicated that TAs are utilised based on a one-on-one support model and are deployed under the class teachers in the classroom. The classroom activities are carried out in small groups with the TAs and the class teacher’s agreement, as per the school’s policy. Findings show that TAs carried out seven different roles in the education of deaf pupils in an English mainstream primary school. Supporting the academic and social development of deaf pupils is TA`s main role. Also, they record pupils’ progress, communicate with pupils’ parents, take on a pastoral care role, tutor pupils in additional support lessons and raise awareness of deaf pupils’ issues.

Keywords: deaf, mainstream primary school, teaching assistant, teaching assistant`s roles

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Authors: Qing Wu, Fei-Yan Li, Heng-Chang Zhang

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Multitask learning support vector machines (SVMs) have recently attracted increasing research attention. Given several related tasks, the single-task learning methods trains each task separately and ignore the inner cross-relationship among tasks. However, multitask learning can capture the correlation information among tasks and achieve better performance by training all tasks simultaneously. In addition, the asymmetric squared loss function can better improve the generalization ability of the models on the most asymmetric distributed data. In this paper, we first make two assumptions on the relatedness among tasks and propose two multitask learning proximal support vector machine algorithms, named MTL-a-PSVM and EMTL-a-PSVM, respectively. MTL-a-PSVM seeks a trade-off between the maximum expectile distance for each task model and the closeness of each task model to the general model. As an extension of the MTL-a-PSVM, EMTL-a-PSVM can select appropriate kernel functions for shared information and private information. Besides, two corresponding special cases named MTL-PSVM and EMTLPSVM are proposed by analyzing the asymmetric squared loss function, which can be easily implemented by solving linear systems. Experimental analysis of three classification datasets demonstrates the effectiveness and superiority of our proposed multitask learning algorithms.

Keywords: multitask learning, asymmetric squared loss, EMTL-a-PSVM, classification

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Authors: T. L. Granzyk, S. Scarborough, J. DeCosmo

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The use of health-related or medical narratives has gained increasing anecdotal and research-based support as a successful device for changing health behavior and outcomes. These narratives, in the form of oral storytelling, short films, and educational documentaries, for example, are most effective when including empathetic characters that transport viewers into the story and command both their attention and emotional response. This case study outlines how and why one large health system created a short narrative film for their internal Sepsis Awareness campaign, which told the dramatic story of a patient recovering from a missed sepsis diagnosis, leaving her a quad-amputee. Results include positive global anecdotal response to the film from healthcare professionals and patients, as well as use of the film to support legislation, ultimately passed in favor of the formation of Sepsis Awareness Workgroups in Maryland. Authors conclude that narrative films can be used successfully to initiate healthcare legislation and to increase internal and external awareness of health-related areas in need of greater improvement and support. As such, healthcare leaders and stakeholders would benefit from learning how to intentionally create, cultivate, and curate narratives from within their own health systems that elicit an empathetic response.

Keywords: healthcare policy, healthcare narratives, sepsis awareness, short films

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Authors: Mookyada Mankrut, Manit Nithitanakul

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An increase in the amount of atmospheric carbon dioxide (CO2) resulting from anthropogenic CO2 emission has been a concerned problem so far. Adsorption using porous materials is feasible way to reduce the content of CO2 emission into the atmosphere due to several advantages: low energy consumption in regeneration process, low-cost raw materials and, high CO2 adsorption capacity. In this work, the porous poly(divinylbenzene) (poly(DVB)) support was synthesized under high internal phase emulsion (HIPE) polymerization then modified with polyethyleneimine (PEI) by using solution plasma process. These porous polymers were then used as adsorbents for CO2 adsorption study. All samples were characterized by some techniques: Fourier transform infrared spectroscopy (FT-IR), scanning electron spectroscopy (SEM), water contact angle measurement and, surface area analyzer. The results of FT-IR and a decrease in contact angle, pore volume and, surface area of PEI-loaded materials demonstrated that surface of poly(DVB) support was modified. In other words, amine groups were introduced to poly(DVB) surface. In addition, not only the outer surface of poly(DVB) adsorbent was modified, but also the inner structure as shown by FT-IR study. As a result, PEI-loaded materials exhibited higher adsorption capacity, comparing with those of the unmodified poly(DVB) support.

Keywords: polyHIPEs, CO2 adsorption, solution plasma process, high internal phase emulsion

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Authors: Chris Nelson

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Quality and excellence are qualitative topics that are usually addressed based on knowledge and past experience from leadership and those in charge of the organization. The significance of this study is to highlight the differences and similarities between these two mindsets and how an operational staff can most appropriately use them in the workplace. Quality and excellence are two words that are talked about a lot in the manufacturing world. Buzzwords such as operational excellence, quality controls, and efficiencies are discussed in the boardroom as well on the shop floor. These terms are used quite frequently and with good reasons. When a person visits their favorite local restaurant, They go because 1) they like the food and 2) the people are some of the greatest individuals to be around. With that in mind, they know they always put out quality food. They do not always go because the quality of the food is far superior than other restaurants. But the quality of ingredients always meets their expectations. When they compare them to the term excellence, they are disappointed. The food never looks like the pictures on the menu. But when have you ever been to a restaurant where the food looks the same as on the menu? For them, when evaluating which buzzword to use as a guiding star, its simple: excellence. The corporation can accomplish these goals by operating at a standard that far exceeds customer’s wants and needs.

Keywords: industrial engineering, innovation, management and technology, logistics and scheduling, six sigma

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Authors: Roselyn Alejandro-Ymana

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The study was an attempt to assess the MTAP Saturday Class Program along its eight components namely, modules, instructional materials, scheduling, trainer-teachers, supervisory support, administrative support, financial support and educational facilities, the results of which served as bases in developing policy guidelines to enhance the MTAP Saturday Class Program. Using a descriptive development method of research, this study involved the participation of twenty-eight (28) schools with MTAP Saturday Class Program in the Division of Dasmarinas City where twenty-eight school heads, one hundred twenty-five (125) teacher-trainer, one hundred twenty-five (125) pupil program participants, and their corresponding one hundred twenty-five (125) parents were purposively drawn to constitute the study’s respondent. A self-made validated survey questionnaire together with Pre and Post-Test Assessment Test in Mathematics for pupils participating in the program, and an unstructured interview guide was used to gather the data needed in the study. Data obtained from the instruments administered was organized and analyzed through the use of statistical tools that included the Mean, Weighted Mean, Relative Frequency, Standard Deviation, F-Test or One-Way ANOVA and the T-Test. Results of the study revealed that all the eight domains involved in the MTAP Saturday Class Program were practiced with the areas of 'trainer-teachers', 'educational facilities', and 'supervisory support' identified as the program’s strongest components while the areas of 'financial support', 'modules' and 'scheduling' as being the weakest program’s components. Moreover, the study revealed based on F-Test, that there was a significant difference in the assessment made by the respondents in each of the eight (8) domains. It was found out that the parents deviated significantly from the assessment of either the school heads or the teachers on the indicators of the program. There is much to be desired when it comes to the quality of the implementation of the MTAP Saturday Class Program. With most of the indicators of each component of the program, having received overall average ratings that were at least 0.5 point away from the ideal rating 5 for total quality, school heads, teachers, and supervisors need to work harder for total quality of the implementation of the MTAP Saturday Class Program in the division.

Keywords: mathematics achievement, MTAP program, policy guidelines, program assessment

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Authors: Noor S. Nasri, Eric C. A. Tatt, Usman D. Hamza, Jibril Mohammed, Husna M. Zain

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Climate change has becoming a global environmental issue that may trigger irreversible changes in the environment with catastrophic consequences for human, animals and plants on our planet. Methane, carbon dioxide and nitrous oxide are the greenhouse gases (GHG) and as the main factor that significantly contributes to the global warming. Mainly carbon dioxide be produced and released to atmosphere by thermal industrial and power generation sectors. Methane is dominant component of natural gas releases significant of thermal heat, and the gaseous pollutants when homogeneous thermal combustion takes place at high temperature. Heterogeneous catalytic Combustion (HCC) principle is promising technologies towards environmental friendly energy production should be developed to ensure higher yields with lower pollutants gaseous emissions and perform complete combustion oxidation at moderate temperature condition as comparing to homogeneous high thermal combustion. Hence the principle has become a very interesting alternative total oxidation for the treatment of pollutants gaseous emission especially NOX product formation. Noble metals are dispersed on a support-porous HCC such as γ- Al2O3, TiO2 and ThO2 to increase thermal stability of catalyst and to increase to effectiveness of catalytic combustion. Support-porous HCC material to be selected based on factors of the surface area, porosity, thermal stability, thermal conductivity, reactivity with reactants or products, chemical stability, catalytic activity, and catalyst life. γ- Al2O3 with high catalytic activity and can last longer life of catalyst, is commonly used as the support for Pd catalyst at low temperatures. Sustainable and renewable support-material of bio-mass char was derived from agro-industrial waste material and used to compare with those the conventional support-porous material. The abundant of biomass wastes generated in palm oil industries is one potential source to convert the wastes into sustainable material as replacement of support material for catalysts. Objective of this study was to compare the kinetic rate of reaction the combustion of methane on Palladium (Pd) based catalyst with Al2O3 support and bio-char (Bc) support derived from shell kernel. The 2wt% Pd was prepared using incipient wetness impregnation method and the HCC performance was accomplished using tubular quartz reactor with gas mixture ratio of 3% methane and 97% air. Material characterization was determined using TGA, SEM, and BET surface area. The methane porous-HCC conversion was carried out by online gas analyzer connected to the reactor that performed porous-HCC. BET surface area for prepared 2 wt% Pd/Bc is smaller than prepared 2wt% Pd/ Al2O3 due to its low porosity between particles. The order of catalyst activity based on kinetic rate on reaction of catalysts in low temperature is prepared 2wt% Pd/Bc > calcined 2wt% Pd/ Al2O3 > prepared 2wt% Pd/ Al2O3 > calcined 2wt% Pd/Bc. Hence the usage of agro-industrial bio-mass waste material can enhance the sustainability principle.

Keywords: catalytic-combustion, environmental, support-bio-char material, sustainable and renewable material

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Authors: Kyle Burke Pfeiffer, Carmella Burdi, Karen Marsh

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The evacuation and shelter-in-place planning process employed by most jurisdictions within the United States is not informed by a scientifically-derived framework that is inclusive of the behavioral and policy-related indicators of public compliance with evacuation orders. While a significant body of work exists to define these indicators, the research findings have not been well-integrated nor translated into useable planning factors for public safety officials. Additionally, refinement of the planning factors alone is insufficient to support science-based evacuation planning as the behavioral elements of evacuees—even with consideration of policy-related indicators—must be examined in the context of specific regional transportation and shelter networks. To address this problem, the Federal Emergency Management Agency and Argonne National Laboratory developed an agent-based model to support regional analysis of zone-based evacuation in southeastern Georgia. In particular, this model allows public safety officials to analyze the consequences that a range of hazards may have upon a community, assess evacuation and shelter-in-place decisions in the context of specified evacuation and response plans, and predict outcomes based on community compliance with orders and the capacity of the regional (to include extra-jurisdictional) transportation and shelter networks. The intention is to use this model to aid evacuation planning and decision-making. Applications for the model include developing a science-driven risk communication strategy and, ultimately, in the case of evacuation, the shortest possible travel distance and clearance times for evacuees within the regional boundary conditions.

Keywords: agent-based modeling for evacuation, decision-support for evacuation planning, evacuation planning, human behavior in evacuation

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Authors: Hromada Martin

Abstract:

Risk analysis is considered as a fundamental aspect relevant for ensuring the level of critical infrastructure protection, where the critical infrastructure is seen as system, asset or its part which is important for maintaining the vital societal functions. Article actually discusses and analyzes the potential application of selected tools of information support for the implementation and within the framework of risk analysis and critical infrastructure protection. Use of the information in relation to their risk analysis can be viewed as a form of simplifying the analytical process. It is clear that these instruments (information support) for these purposes are countless, so they were selected representatives who have already been applied in the selected area of critical infrastructure, or they can be used. All presented fact were the basis for critical infrastructure resilience evaluation methodology development.

Keywords: critical infrastructure, protection, resilience, risk analysis

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Authors: Janet Kaningen, Richard N. Kaningen, Jonas Kaningen

Abstract:

This paper aims to discover the best ways to improve production efficiency, cost efficiency, community cohesion, and long-term sustainability in Ghana's housing delivery. Advanced Construction Technologies (ACTs) are set to become the sustainable mainstay of the construction industry due to the demand for innovative housing solutions. Advances in material science, building component production, and assembly technologies are leading to the development of next-generation materials such as polymeric-fiber-based products, light-metal alloys, and eco-materials. Modular housing construction has become more efficient and cost-effective than traditional building methods and is becoming increasingly popular for commercial, industrial, and residential projects. Effective project management and logistics will be imperative in the future speed and cost of modular construction housing.

Keywords: technology blending, sustainability, housing, Ghana

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Authors: Yetunde M. Dairo, Johnny Collett, Helen Dawes

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Background and Aim: Engagement with physical activity (PA) research is poor among adults with intellectual disabilities (ID), particularly in those from residential homes. This study explored why, by asking managers of residential homes, adults with ID and their carers. Methods: Participants: A convenient sample of 23 individuals from two UK local authorities, including a group of ID residential home managers, adults with ID and their support staff. Procedures: A) Residential home managers (n=6) were asked questions about their willingness to allow their residents to participate in PA research; B) eleven adults with ID and their support workers (n=6) were asked questions about their willingness to accept 7-day accelerometer monitoring and/or the International Physical Activity Questionnaire-short version (IPAQ-s) as PA measures. The IPAQ-s was administered by the researcher and they were each provided with samples of accelerometers to try on. Results: A) Five out of six managers said that the burden of wearing the accelerometer for seven days would be too high for the people they support, the majority of whom might be unable to express their wishes. They also said they would be unwilling to act as proxy respondents for the same reason. Additionally, they cited time pressure, understaffing, and reluctance to spend time on the research paperwork as further reasons for non-participation. B) All 11 individuals with ID completed the IPAQ-s while only three accepted the accelerometer, one of whom was deemed inappropriate to wear it. Reasons for rejecting accelerometers included statements from participants of: ‘too expensive’, ‘too heavy’, ‘uncomfortable’, and two people said they would not want to wear it for more than one day. All adults with ID (11) and their support workers (6) provided information about their physical activity levels through the IPAQ-s. Conclusions: Care home managers are a barrier to research participation. However, adults with ID would be happy for the IPAQ-s as a PA measure, but less so for the 7-day accelerometer monitoring. In order to improve participation in this population, the choice of PA measure is considered important. Moreover, there is a need for studies exploring how best to engage ID residential home managers in PA research.

Keywords: intellectual disability, physical activity measurement, research engagement, research participation

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Authors: Athena Pedro, Laura Bradfield, Mike Dare, Zandile Bantwana, Ashley Nayman

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The purpose of the research was to explore mother’s unique experience and knowledge of mothering in the first 1000 day of their child’s life, from birth to age 2. The study used a qualitative research methodology with an exploratory research design. A sample of 12 mothers was used, comprising different racial backgrounds from low income areas in the Western Cape. The data was collected by means of semi-structured, in-depth interviews, which were transcribed verbatim, analysed using Braun’s and Clark’s (2006) six phases of thematic analysis. Some of the findings revealed that the mothers who participated in the study were consistently unable to feed their children and themselves due to profound and extreme situations of poverty, stress, and lack of infrastructural support. These mothers residing in low-income communities are not adequately supported both financially and socially and are often unable to meet the needs of their infants within the first 1000 days. Given the consequential nature of this period, it is imperative that mothers are able to access such support. Single mothers especially are in need of social and financial support. Appropriate interventions are required to assist mothers generally but more specifically, mothers who have children within the first 1000 days of life. By implementing appropriate interventions to address these needs, it will assist mothers to ensure optimal developmental growth of their children. This will positively impact the developmental trajectory of children in South Africa.

Keywords: caring, economic hardship, first one thousand days, mothers

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Authors: Jerome D. Donovan

Abstract:

The pandemic has resulted in a dramatic re-consideration of the reliance on international student fees to support university models in Australia. A key resulting initiative for the Australian Federal Government has been shifting the way universities consider their research model, emphasising the importance of commercialising research. This study specifically examines this shift from the perspective of a university spin-off, examining how university support structures and incubation models have assisted in the translation of fundamental research into a high-growth university spin-off. A focused case study approach is adopted in this study, using an auto-ethnographic research method to document the experiences and insights drawn from being a co-founder in a university spin-off in a time where research commercialisation has emerged as a central focus in Australian universities.

Keywords: research commercialisation, spin-offs, university incubation, entrepreneurship

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