Search results for: meta-simulation based

Authors: Gokhan Egilmez, Erika Hatfield, Julie Turner

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In this study, we investigated the impacts of service-learning integration on an undergraduate level business analytics course from multiple perspectives, including academic proficiency, community awareness, engagement, social responsibility, and reflection. We assessed the impact of the service-learning experience by using a survey developed primarily based on the literature review and secondarily on an ad hoc group of researchers. Then, we implemented the survey in two sections, where one of the sections was a control group. We compared the results of the empirical survey visually and statistically.

Keywords: business analytics, service learning, experiential education, statistical analysis, survey research

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Authors: Rashedul Islam

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A firmly-validated aim of teaching science is to support student enthusiasm for science learning with an outspread interest in scientific issues in future life. This is in keeping with the recent development in Gifted and Talented Education statement which instructs that gifted students have a renewed interest and natural aptitude in science. Yet, the practice of science teaching leaves many students with the feeling that science is difficult and compared to other school subjects, students interest in science is declining at the final years of the primary school. As a curriculum guides the teaching-learning activities in school, where significant consequences may result from the context of the curricula and syllabi, are a major feature of certain educational jurisdictions in NSW, Australia. The purpose of this study was an exploration of the curriculum sets the context to identify how science education is practiced through primary schools in Sydney, Australia. This phenomenon was explored through document review from two publicly available documents namely: the NSW Science Syllabus K-6, and Australian Curriculum: Foundation - 10 Science. To analyse the data, this qualitative study applied themed content analysis at three different levels, i.e., first cycle coding, second cycle coding- pattern codes, and thematic analysis. Preliminary analysis revealed the phenomenon of teaching-learning practices drawn from eight themes under three phenomena aligned with teachers’ practices and gifted student’s learning characteristics based on Gagné’s Differentiated Model of Gifted and Talent (DMGT). From the results, it appears that, overall, the two documents are relatively well-placed in terms of identifying the context of teaching and learning primary science to gifted students. However, educators need to make themselves aware of the ways in which the curriculum needs to be adapted to meet gifted students learning needs in science. It explores the important phenomena of teaching-learning context to provide gifted students with optimal educational practices including inquiry-based learning, problem-solving, open-ended tasks, creativity in science, higher order thinking, integration, and challenges. The significance of such a study lies in its potential to schools and further research in the field of gifted education.

Keywords: teaching primary science, gifted student learning, curriculum context, science syllabi, Australia

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Authors: Huijing Wen, Daibao Guo

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Writing is thought to be the most complex facet of language arts. Assessing writing is difficult and subjective, and there are few scientifically validated assessments exist. Research has proposed evaluating writing using a multidimensional approach, including both qualitative and quantitative measures of handwriting, spelling and prose. Given that narrative writing has historically been a staple of literacy instruction in primary grades and is one of the three major genres Common Core State Standards required students to acquire starting in kindergarten, it is essential for teachers to understand how to measure beginning writers writing development and sources of writing difficulties through narrative writing. Guided by the theoretical models of early written expression and using empirical data, this study examines ways teachers can enact a comprehensive approach to understanding beginning writer’s narrative writing through three writing rubrics developed for a Curriculum-based Measurement (CBM). The goal is to help classroom teachers structure a framework for assessing early writing in primary classrooms. Participants in this study included 380 first-grade students from 50 classrooms in 13 schools in three school districts in a Mid-Atlantic state. Three writing tests were used to assess first graders’ writing skills in relation to both transcription (i.e., handwriting fluency and spelling tests) and translational skills (i.e., a narrative prompt). First graders were asked to respond to a narrative prompt in 20 minutes. Grounded in theoretical models of earlier expression and empirical evidence of key contributors to early writing, all written samples to the narrative prompt were coded three ways for different dimensions of writing: length, quality, and genre elements. To measure the quality of the narrative writing, a traditional holistic rating rubric was developed by the researchers based on the CCSS and the general traits of good writing. Students' genre knowledge was measured by using a separate analytic rubric for narrative writing. Findings showed that first-graders had emerging and limited transcriptional and translational skills with a nascent knowledge of genre conventions. The findings of the study provided support for the Not-So-Simple View of Writing in that fluent written expression, measured by length and other important linguistic resources measured by the overall quality and genre knowledge rubrics, are fundamental in early writing development. Our study echoed previous research findings on children's narrative development. The study has practical classroom application as it informs writing instruction and assessment. It offered practical guidelines for classroom instruction by providing teachers with a better understanding of first graders' narrative writing skills and knowledge of genre conventions. Understanding students’ narrative writing provides teachers with more insights into specific strategies students might use during writing and their understanding of good narrative writing. Additionally, it is important for teachers to differentiate writing instruction given the individual differences shown by our multiple writing measures. Overall, the study shed light on beginning writers’ narrative writing, indicating the complexity of early writing development.

Keywords: writing assessment, early writing, beginning writers, transcriptional skills, translational skills, primary grades, simple view of writing, writing rubrics, curriculum-based measurement

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Authors: Maryam Gallab, Hafida Bouloiz, Youness Chater, Mohamed Tkiouat

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The aim of this paper is to present a model based on multi-agent systems in order to manage the maintenance activities and to ensure the reliability and availability of machines just with the required resources (operators, tools). The interest of the simulation is to solve the complexity of the system and to find results without cost or wasting time. An implementation of the model is carried out on the AnyLogic platform to display the defined performance indicators.

Keywords: maintenance, complexity, simulation, multi-agent systems, AnyLogic platform

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Authors: Narimen Rdhaounia Mohamed Kouni

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Our aim in this paper is to identify the origins of inflation in Tunisia on the period from 1988 to 2018. In order to estimate the model, an ARDL methodology is used. We studied also the effect of informal economy on inflation. Indeed, we estimated the size of the informal economy in Tunisia based on Gutmann method. The results showed that there are three main origins of inflation. In fact, the first origin is the fiscal policy adopted by Tunisia, particularly after revolution. The second origin is the increase of monetary variables. Finally, informal economy played an important role in inflation.

Keywords: inflation, consumer price index, informal, gutmann method, ARDL model

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Authors: Atish Bagchi, Siva Chandrasekaran

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Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

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Authors: Madia Safdar, G. Amjad Hussain, Mashhood Ahmad

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One of the major challenges of today’s era is peak demand which causes stress on the transmission lines and also raises the cost of energy generation and ultimately higher electricity bills to the end users, and it was used to be managed by the supply side management. However, nowadays this has been withdrawn because of existence of potential in the demand side management (DSM) having its economic and- environmental advantages. DSM in domestic load can play a vital role in reducing the peak load demand on the network provides a significant cost saving. In this paper the potential of demand response (DR) in reducing the peak load demands and electricity bills to the electric users is elaborated. For this purpose the domestic appliances are modeled in MATLAB Simulink and controlled by a module called energy management controller. The devices are categorized into controllable and uncontrollable loads and are operated according to real-time tariff pricing pattern instead of fixed time pricing or variable pricing. Energy management controller decides the switching instants of the controllable appliances based on the results from optimization algorithms. In GAMS software, the MILP (mixed integer linear programming) algorithm is used for optimization. In different cases, different constraints are used for optimization, considering the comforts, needs and priorities of the end users. Results are compared and the savings in electricity bills are discussed in this paper considering real time pricing and fixed tariff pricing, which exhibits the existence of potential to reduce electricity bills and peak loads in demand side management. It is seen that using real time pricing tariff instead of fixed tariff pricing helps to save in the electricity bills. Moreover the simulation results of the proposed energy management system show that the gained power savings lie in high range. It is anticipated that the result of this research will prove to be highly effective to the utility companies as well as in the improvement of domestic DR.

Keywords: controllable and uncontrollable domestic loads, demand response, demand side management, optimization, MILP (mixed integer linear programming)

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Authors: Twinkle Sara Joseph

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Virtual reality technology has emerged as a revolutionary power that can transform the education sector in many ways. VR environments can break the boundaries of the traditional classroom setting by immersing the students in realistic 3D environments where they can interact with virtual characters without fearing being judged. Communication skills are essential for every profession, and studies suggest the importance of implementing basic-level communication courses at both the school and graduate levels. Interpersonal communication is a skill that gains prominence as it is required in every profession. Traditional means of training have limitations for trainees as well as participants. The fear of being judged, the audience interaction, and other factors can affect the performance of a participant in a traditional classroom setting. Virtual reality offers a unique opportunity for its users to participate in training that does not set any boundaries that prevent the participants from performing in front of an audience. Specialised applications designed in VR headsets offer a range of training and exercises for participants without any time, space, or audience limitations. The present study aims at measuring the effectiveness of VR training in improving interpersonal communication skills among students. The study uses a mixed-method approach, in which a pre-and post-test will be designed to measure effectiveness. A preliminary selection process involving a questionnaire and a screening test will identify suitable candidates based on their current communication proficiency levels. Participants will undergo specialised training through the VR application Virtual Speech tailored for interpersonal communication and public speaking, designed to operate without the traditional constraints of time, space, or audience. The training's impact will subsequently be measured through situational exercises to engage the participants in interpersonal communication tasks, thereby assessing the improvement in their skills. The significance of this study lies in its potential to provide empirical evidence supporting VR technology's role in enhancing communication skills, thereby offering valuable insights for integrating VR-based methodologies into educational frameworks to prepare students more effectively for their professional futures.

Keywords: virtual reality, VR training, interpersonal communication, communication skills, 3D environments

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Authors: John Zanetich

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Designing an educational activity that encourages inquiry and collaboration is key to engaging students in meaningful learning. Educational Information and Communications Technology (EICT) plays an important role in facilitating cooperative and collaborative learning in the classroom. The EICT also facilitates students’ learning and development of the critical thinking skills needed to solve real world problems. Projects and activities based on constructivism encourage students to embrace complexity as well as find relevance and joy in their learning. It also enhances the students’ capacity for creative and responsible real-world problem solving. Classroom activities based on constructivism offer students an opportunity to develop the higher–order-thinking skills of defining problems and identifying solutions. Participating in a classroom project is an activity for both acquiring experiential knowledge and applying new knowledge to practical situations. It also provides an opportunity for students to integrate new knowledge into a skill set using reflection. Classroom projects can be developed around a variety of learning objects including social media, knowledge management and learning communities. The construction of meaning through project-based learning is an approach that encourages interaction and problem-solving activities. Projects require active participation, collaboration and interaction to reach the agreed upon outcomes. Projects also serve to externalize the invisible cognitive and social processes taking place in the activity itself and in the student experience. This paper describes a classroom project designed to elicit interactions by helping students to unfreeze existing knowledge, to create new learning experiences, and then refreeze the new knowledge. Since constructivists believe that students construct their own meaning through active engagement and participation as well as interactions with others. knowledge management can be used to guide the exchange of both tacit and explicit knowledge in interpersonal interactions between students and guide the construction of meaning. This paper uses an action research approach to the development of a classroom project and describes the use of technology, social media and the active use of tacit knowledge in the college classroom. In this project, a closed group Facebook page becomes the virtual classroom where interaction is captured and measured using engagement analytics. In the virtual learning community, the principles of knowledge management are used to identify the process and components of the infrastructure of the learning process. The project identifies class member interests and measures student engagement in a learning community by analyzing regular posting on the Facebook page. These posts are used to foster and encourage interactions, reflect a student’s interest and serve as reaction points from which viewers of the post convert the explicit information in the post to implicit knowledge. The data was collected over an academic year and was provided, in part, by the Google analytic reports on Facebook and self-reports of posts by members. The results support the use of active tacit knowledge activities, knowledge management and social media to enhance the student learning experience and help create the knowledge that will be used by students to construct meaning.

Keywords: constructivism, knowledge management, tacit knowledge, social media

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Authors: Assad Maalouf, Lunjin Lu, James Lynott

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We design and implement a precise model of string operations using finite state machine transformers and state transformers to approximate the values string variables can take throughout the execution of the program.We use our model to analyze Android program string variables. Our experimental results show that our string analysis is very efficient at detecting the contextual effect of string operations on the string variables. Our model proved to be very useful when it came to verifying statements about the string variables of the program.

Keywords: abstract interpretation, android, static analysis, string analysis

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Authors: Z. Arabshahi, I. Afara, A. Oloyede, H. Moody, J. Kashani, T. Klein

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Articular cartilage is a fluid-swollen tissue of synovial joints that functions by providing a lubricated surface for articulation and to facilitate the load transmission. The biomechanical function of this tissue is highly dependent on the integrity of its ultrastructural matrix. Any alteration of articular cartilage matrix, either by injury or degenerative conditions such as osteoarthritis (OA), compromises its functional behaviour. Therefore, the assessment of articular cartilage is important in early stages of degenerative process to prevent or reduce further joint damage with associated socio-economic impact. Therefore, there has been increasing research interest into the functional assessment of articular cartilage. This study developed a characterization parameter for articular cartilage assessment based on the response of cartilage surface to loading/unloading. This is because the response of articular cartilage to compressive loading is significantly depth-dependent, where the superficial zone and underlying matrix respond differently to deformation. In addition, the alteration of cartilage matrix in the early stages of degeneration is often characterized by PG loss in the superficial layer. In this study, it is hypothesized that the response of superficial layer is different in normal and proteoglycan depleted tissue. To establish the viability of this hypothesis, samples of visually intact and artificially proteoglycan-depleted bovine cartilage were subjected to compression at a constant rate to 30 percent strain using a ring-shaped indenter with an integrated ultrasound probe and then unloaded. The response of articular surface which was indirectly loaded was monitored using ultrasound during the time of loading/unloading (deformation/recovery). It was observed that the rate of cartilage surface response to loading/unloading was different for normal and PG-depleted cartilage samples. Principal Component Analysis was performed to identify the capability of the cartilage surface response to loading/unloading, to distinguish between normal and artificially degenerated cartilage samples. The classification analysis of this parameter showed an overlap between normal and degenerated samples during loading. While there was a clear distinction between normal and degenerated samples during unloading. This study showed that the cartilage surface response to loading/unloading has the potential to be used as a parameter for cartilage assessment.

Keywords: cartilage integrity parameter, cartilage deformation/recovery, cartilage functional assessment, ultrasound

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Authors: Imad Zeyad Ramadan

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In this paper a genetic algorithm was developed to construct the optimal portfolio based on the Treynor method. The GA maximizes the Treynor ratio under budget constraint to select the best allocation of the budget for the companies in the portfolio. The results show that the GA was able to construct a conservative portfolio which includes companies from the three sectors. This indicates that the GA reduced the risk on the investor as it choose some companies with positive risks (goes with the market) and some with negative risks (goes against the market).

Keywords: oOptimization, genetic algorithm, portfolio selection, Treynor method

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Authors: Ayla Hoeta

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The focus of this research is mahi Maramataka, ‘the practices of Maramataka’ as a traditional and evolving knowledge system and its connection to whaanau oranga (wellbeing) and healing. Centering kaupapa Maaori methods and knowledge this research will explore how Maramataka can be used as a tool for oranga and healing for whaanau to engage with different environments aligned with Maramataka flow and optimal time based on the environment. Maramataka is an ancestral lunar environmental knowledge system rooted within korero tuku iho, Maaori creation stories, dating back to the beginning of time. The significance of Maramataka is the ancient environmental knowledge and the connecting energy flow of mauri (life force) between whenua (land), moana (ocean) and rangi (sky). The lunar component of the Maramataka is widely understood and highlights the different phases of the moon. Each moon phase is named with references to puurakau stories and environmental and ecological information. Marama, meaning moon and taka, meaning cycle, is used as a lunar and environmental calendar. There are lunar phases that are optimal for specific activities, such as the Tangaroa phase, a time of abundance and productivity and ocean-based activities like fishing. Other periods in the Maramataka, such as Rakaunui (full moon), connect the highest tides and highest energy of the lunar cycle, ideal for social, physical activity and particularly planting. Other phases like Tamatea are unpredictable whereas Whiro (new moon/s) is reflective, deep and cautious during the darkest nights. Whaanau, particularly in urban settings have become increasingly disconnected from the natural environment, the Maramataka has become a tool that they can connect to which offers an alternative to dominant perspectives of health and is an approach that is uniquely Maaori. In doing so, this research will raise awareness of oranga or lack of oranga, and lived experience of whaanau in Tamaki Makaurau - Aotearoa, on a journey to revival of Maramataka and healing. The research engages Hautu Waka as a methodology using the methods of ancient kaupapa Māori practises based on wayfinding and attunement with the natural environment. Using ancient ways of being, knowing, seeing and doing the Hautu Waka will centre kaupapa Maaori perspectives to process design, reflection and evaluation. The methods of Hautu Waka consists of five interweaving phases, 1) Te Rapunga (the search) in infinite potential, 2) Te Kitenga (the seeing), observations of and attunement to tohu 3) te whainga (the pursuit) and deeply exploring key tohu 4) te whiwhinga (the acquiring), of knowledge and clearer ideas, 5) Te Rawenga (the celebration), reflection and acknowledgement of the journey and achievements. This research is an expansion from my creative practices across whaanau-centred inquiry, to understand the benefits of Maramataka and how it can be embodied and practised in a modern-day context to support oranga and healing. Thus, the goal is to work with kaupapa Maaori methodologies to authenticate as a Maaori practitioner and researcher and allow an authentic indigenous approach to the exploration of Maramataka and through a kaupapa Maaori lens.

Keywords: maramataka (Maaori calendar), tangata (people), taiao (environment), whenua (land), whaanau (family), hautu waka (navigation framework)

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Authors: S. Delgado, C. Cerrada, R. S. Gómez

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This research introduces an approach to voxelizing the surfaces of triangular meshes with efficiency and accuracy. Our method leverages parallel equidistant scan-lines and introduces a Gap Detection technique to address the limitations of existing approaches. We present a comprehensive study showcasing the method's effectiveness, scalability, and versatility in different scenarios. Voxelization is a fundamental process in computer graphics and simulations, playing a pivotal role in applications ranging from scientific visualization to virtual reality. Our algorithm focuses on enhancing the voxelization process, especially for complex models and high resolutions. One of the major challenges in voxelization in the Graphics Processing Unit (GPU) is the high cost of discovering the same voxels multiple times. These repeated voxels incur in costly memory operations with no useful information. Our scan-line-based method ensures that each voxel is detected exactly once when processing the triangle, enhancing performance without compromising the quality of the voxelization. The heart of our approach lies in the use of parallel, equidistant scan-lines to traverse the interiors of triangles. This minimizes redundant memory operations and avoids revisiting the same voxels, resulting in a significant performance boost. Moreover, our method's computational efficiency is complemented by its simplicity and portability. Written as a single compute shader in Graphics Library Shader Language (GLSL), it is highly adaptable to various rendering pipelines and hardware configurations. To validate our method, we conducted extensive experiments on a diverse set of models from the Stanford repository. Our results demonstrate not only the algorithm's efficiency, but also its ability to produce 26 tunnel free accurate voxelizations. The Gap Detection technique successfully identifies and addresses gaps, ensuring consistent and visually pleasing voxelized surfaces. Furthermore, we introduce the Slope Consistency Value metric, quantifying the alignment of each triangle with its primary axis. This metric provides insights into the impact of triangle orientation on scan-line based voxelization methods. It also aids in understanding how the Gap Detection technique effectively improves results by targeting specific areas where simple scan-line-based methods might fail. Our research contributes to the field of voxelization by offering a robust and efficient approach that overcomes the limitations of existing methods. The Gap Detection technique fills a critical gap in the voxelization process. By addressing these gaps, our algorithm enhances the visual quality and accuracy of voxelized models, making it valuable for a wide range of applications. In conclusion, "Closing the Gap: Efficient Voxelization with Equidistant Scan-lines and Gap Detection" presents an effective solution to the challenges of voxelization. Our research combines computational efficiency, accuracy, and innovative techniques to elevate the quality of voxelized surfaces. With its adaptable nature and valuable innovations, this technique could have a positive influence on computer graphics and visualization.

Keywords: voxelization, GPU acceleration, computer graphics, compute shaders

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Authors: Lizeth Fuentes-Mera, Vanessa Perez-Silos, Nidia K. Moncada-Saucedo, Alejandro Garcia-Ruiz, Alberto Camacho, Jorge Lara-Arias, Ivan Marino-Martinez, Victor Romero-Diaz, Adolfo Soto-Dominguez, Humberto Rodriguez-Rocha, Hang Lin, Victor Pena-Martinez

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Biphasic scaffolds in cartilage tissue engineering have been designed to influence not only the recapitulation of the osteochondral architecture but also to take advantage of the healing ability of bone to promote the implant integration with the surrounding tissue and then bone restoration and cartilage regeneration. This study reports the development and characterization of a biphasic scaffold based on the assembly of a cartilage phase constituted by fibroin biofunctionalized with bovine cartilage matrix; cellularized with differentiated pre-chondrocytes from adipose tissue stem cells (autologous) and well attached to a bone phase (bone bovine decellularized) to mimic the structure of the nature of native tissue and to promote the cartilage regeneration in a model of joint damage in pigs. Biphasic scaffolds were assembled by fibroin crystallization with methanol. The histological and ultrastructural architectures were evaluated by optical and scanning electron microscopy respectively. Mechanical tests were conducted to evaluate Young's modulus of the implant. For the biological evaluation, pre-chondrocytes were loaded onto the scaffolds and cellular adhesion, proliferation, and gene expression analysis of cartilage extracellular matrix components was performed. The scaffolds that were cellularized and matured for 10 days were implanted into critical 3 mm in diameter and 9-mm in depth osteochondral defects in a porcine model (n=4). Three treatments were applied per knee: Group 1: monophasic cellular scaffold (MS) (single chondral phase), group 2: biphasic scaffold, cellularized only in the chondral phase (BS1), group 3: BS cellularized in both bone and chondral phases (BS2). Simultaneously, a control without treatment was evaluated. After 4 weeks of surgery, integration and regeneration tissues were analyzed by x-rays, histology and immunohistochemistry evaluation. The mechanical assessment showed that the acellular biphasic composites exhibited Young's modulus of 805.01 kPa similar to native cartilage (400-800 kPa). In vitro biological studies revealed the chondroinductive ability of the biphasic implant, evidenced by an increase in sulfated glycosaminoglycan (GAGs) and type II collagen, both secreted by the chondrocytes cultured on the scaffold during 28 days. No evidence of adverse or inflammatory reactions was observed in the in vivo trial; however, In group 1, the defects were not reconstructed. In group 2 and 3 a good integration of the implant with the surrounding tissue was observed. Defects in group 2 were fulfilled by hyaline cartilage and normal bone. Group 3 defects showed fibrous repair tissue. In conclusion; our findings demonstrated the efficacy of biphasic and bioactive scaffold based on silk fibroin, which entwined chondroinductive features and biomechanical capability with appropriate integration with the surrounding tissue, representing a promising alternative for osteochondral tissue-engineering applications.

Keywords: biphasic scaffold, extracellular cartilage matrix, silk fibroin, osteochondral tissue engineering

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Authors: Dalila Chouder, Djaafer Benachour

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This work concerns the study of the adsorption of metal ions Ag +, Mg +, and Ni2+ in aqueous medium by polydibenzoether-ROWN based on three factors: Temperature, time and concentration. The polydibenzoether crown was synthesized by two means: Chemical and electrochemical. The behavior of the two polymers has been different, and turns out very interesting for chemical polydibenzoether crown has identified conditions. Chemical and électronique polydibenzoether crown have different extraction screw vi property of adsoption of ions fifférents, this study also shows that plyméres doped may have an advantageous electrical conductivity.

Keywords: polymerization, electrochemical, conductivity, complexing metal ions

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Authors: Liliana O. Martínez, Juan E González, Manuel Ramírez-Aranda, Ana Cervantes-Herrera

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A serious game category mobile application called Math Dominoes is presented. The main objective of this applications is to strengthen the teaching-learning process of solving algebraic equations and is based on the board game "Double 6" dominoes. Math Dominoes allows the practice of solving first, second-, and third-degree algebraic equations. This application is aimed to students who seek to strengthen their skills in solving algebraic equations in a dynamic, interactive, and fun way, to reduce the risk of failure in subsequent courses that require mastery of this algebraic tool.

Keywords: algebra, equations, dominoes, serious games

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Authors: Josua Sihotang

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Jakarta Capital Special Region is the province that densely populated with rapidly growing infrastructure but less attention for the environmental condition. This makes some social problem happened like lack of clean water supply. Shallow groundwater and river water condition that has contaminated make the layer of deep water carrier (aquifer) should be done. This research aims to provide the people insight about deep groundwater potential and to determine the depth, location, and quality where the aquifer can be found in Jakarta’s area, particularly Kapuk-Cengkareng’s people. This research was conducted by geophysical method namely Well Logging Analysis. Well Logging is the geophysical method to know the subsurface lithology with the physical characteristic. The observation in this research area was conducted with several well devices that is Spontaneous Potential Log (SP Log), Resistivity Log, and Gamma Ray Log (GR Log). The first devices well is SP log which is work by comprising the electrical potential difference between the electrodes on the surface with the electrodes that is contained in the borehole and rock formations. The second is Resistivity Log, used to determine both the hydrocarbon and water zone based on their porosity and permeability properties. The last is GR Log, work by identifying radioactivity levels of rocks which is containing elements of thorium, uranium, or potassium. The observation result is curve-shaped which describes the type of lithological coating in subsurface. The result from the research can be interpreted that there are four of the deep groundwater layer zone with different quality. The good groundwater layer can be found in layers with good porosity and permeability. By analyzing the curves, it can be known that most of the layers which were found in this wellbore are clay stone with low resistivity and high gamma radiation. The resistivity value of the clay stone layers is about 2-4 ohm-meter with 65-80 Cps gamma radiation. There are several layers with high resistivity value and low gamma radiation (sand stone) that can be potential for being an aquifer. This is reinforced by the sand layer with a right-leaning SP log curve proving that this layer is permeable. These layers have 4-9 ohm-meter resistivity value with 40-65 Cps gamma radiation. These are mostly found as fresh water aquifer.

Keywords: aquifer, deep groundwater potential, well devices, well logging analysis

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Authors: Wafa Benaatou, Adnane Latif

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In this document we studied more in detail the Performances of the vertical handover in the networks WLAN, WiMAX, UMTS before studying of it the Procedure of Handoff Vertical, the whole buckled by simulations putting forward the performances of the handover in the heterogeneous networks. The goal of Vertical Handover is to carry out several accesses in real-time in the heterogeneous networks. This makes it possible a user to use several networks (such as WLAN UMTS and WiMAX) in parallel, and the system to commutate automatically at another basic station, without disconnecting itself, as if there were no cut and with little loss of data as possible.

Keywords: vertical handoff, WLAN, UMTS, WIMAX, heterogeneous

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Authors: Manutchanok Jongprasithporn, Rawiphorn Srivilai, Paweena Pongsopha

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Fall is the most serious accident leading to increased unintentional injuries and mortality. Falls are not only the cause of suffering and functional impairments to the individuals, but also the cause of increasing medical cost and days away from work. The early detection of falls could be an advantage to reduce fall-related injuries and consequences of falls. Smartphones, embedded accelerometer, have become a common device in everyday life due to decreasing technology cost. This paper explores a physical activity monitoring and fall detection application in smartphones which is a non-invasive biomedical device to determine physical activities and fall event. The combination of application and sensors could perform as a biomedical sensor to monitor physical activities and recognize a fall. We have chosen Android-based smartphone in this study since android operating system is an open-source and no cost. Moreover, android phone users become a majority of Thai’s smartphone users. We developed Thai 3 Axis (TH3AX) as a physical activities and fall detection application which included command, manual, results in Thai language. The smartphone was attached to right hip of 10 young, healthy adult subjects (5 males, 5 females; aged< 35y) to collect accelerometer and gyroscope data during performing physical activities (e.g., walking, running, sitting, and lying down) and falling to determine threshold for each activity. Dependent variables are including accelerometer data (acceleration, peak acceleration, average resultant acceleration, and time between peak acceleration). A repeated measures ANOVA was performed to test whether there are any differences between DVs’ means. Statistical analyses were considered significant at p<0.05. After finding threshold, the results were used as training data for a predictive model of activity recognition. In the future, accuracies of activity recognition will be performed to assess the overall performance of the classifier. Moreover, to help improve the quality of life, our system will be implemented with patients and elderly people who need intensive care in hospitals and nursing homes in Thailand.

Keywords: activity recognition, accelerometer, fall, gyroscope, smartphone

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Authors: Sašo Pečnik, Borut Žalik

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This paper presents a real-time visualization technique and filtering of classified LiDAR point clouds. The visualization is capable of displaying filtered information organized in layers by the classification attribute saved within LiDAR data sets. We explain the used data structure and data management, which enables real-time presentation of layered LiDAR data. Real-time visualization is achieved with LOD optimization based on the distance from the observer without loss of quality. The filtering process is done in two steps and is entirely executed on the GPU and implemented using programmable shaders.

Keywords: filtering, graphics, level-of-details, LiDAR, real-time visualization

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Authors: Farahnaz Sadat Golestan Hashemi, Mohd Razi Ismail, Mohd Y. Rafii

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A huge revolution has emerged in genome engineering by the discovery of CRISPR (clustered regularly interspaced palindromic repeats) and CRISPR-associated system genes (Cas) in bacteria. The function of type II Streptococcus pyogenes (Sp) CRISPR/Cas9 system has been confirmed in various species. Other S. thermophilus (St) CRISPR-Cas systems, CRISPR1-Cas and CRISPR3-Cas, have been also reported for preventing phage infection. The CRISPR1-Cas system interferes by cleaving foreign dsDNA entering the cell in a length-specific and orientation-dependant manner. The S. thermophilus CRISPR3-Cas system also acts by cleaving phage dsDNA genomes at the same specific position inside the targeted protospacer as observed in the CRISPR1-Cas system. It is worth mentioning, for the effective DNA cleavage activity, RNA-guided Cas9 orthologs require their own specific PAM (protospacer adjacent motif) sequences. Activity levels are based on the sequence of the protospacer and specific combinations of favorable PAM bases. Therefore, based on the specific length and sequence of PAM followed by a constant length of target site for the three orthogonals of Cas9 protein, a well-organized procedure will be required for high-throughput and accurate mining of possible target sites in a large genomic dataset. Consequently, we created a reliable procedure to explore potential gRNA sequences for type I (Streptococcus thermophiles), II (Streptococcus pyogenes), and III (Streptococcus thermophiles) CRISPR/Cas systems. To mine CRISPR target sites, four different searching modes of sgRNA binding to target DNA strand were applied. These searching modes are as follows: i) coding strand searching, ii) anti-coding strand searching, iii) both strand searching, and iv) paired-gRNA searching. The output of such procedure highlights the power of comparative genome mining for different CRISPR/Cas systems. This could yield a repertoire of Cas9 variants with expanded capabilities of gRNA design, and will pave the way for further advance genome and epigenome engineering.

Keywords: CRISPR/Cas systems, gRNA mining, Streptococcus pyogenes, Streptococcus thermophiles

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Authors: Yongjun Kim

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Since the agreement on the historicity of historical Buddha in eastern India, the beginning, heyday and decline of Buddhism in Early India have been discussed in urbanization, commercialism and state formation context, in short, Weberian socio-politico frame. Recent Scholarship, notably in archaeology and anthropology, has proposed ‘re-materialization of Buddhism in Early India’ based on what Buddhist had actually done rather than what they should do according to canonical teachings or philosophies. But its historical narrations still remain with a domain of socio-politico meta-narrative which tends to unjustifiably dismiss the naturally existing heterogeneity and often chaotic dynamic of diverse agencies, landscape perceptions, localized traditions, etc. An author will argue the multiplicity of theoretical standpoints for the reconstruction on the Buddhism in Early India. For this, at first, the diverse agencies, localized traditions, landscape patterns of Buddhist communities and monasteries in Trans-Himalayan regions; focusing Zanskar Valley and Spiti Valley in India will be illustrated based on an author’s field work. And then an author will discuss this anthropological landscape analysis is better appropriated with textual and archaeological evidences on the tension between urban monastic and forest Buddhism, the phenomena of sacred landscape, cemetery, garden, natural cave along with socio-economic landscape, the demographic heterogeneity in Early India. Finally, it will be attempted to compare between anthropological landscape of present Trans-Himalayan and archaeological one of ancient Western India. The study of Buddhism in Early India has hardly been discussed through multivalent theoretical archaeology and anthropology of religion, thus traditional and recent scholarship have produced historical meta-narrative though heterogeneous among them. The multidisciplinary approaches of textual critics, archaeology and anthropology will surely help to deconstruct the grand and all-encompassing historical description on Buddhism in Early India and then to reconstruct the localized, behavioral and multivalent narratives. This paper expects to highlight the importance of lesser-studied Buddhist archaeological sites and the dynamic views on religious landscape in Early India with a help of critical anthropology of religion.

Keywords: analogy by living traditions, Buddhism in Early India, landscape analysis, meta-narrative

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Authors: H. Yousefnia, S. Zolghadri, S. Shanesazzadeh, A.Lahooti, A. R. Jalilian

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In this study, 68Ga-ECC and 67Ga-ECC were both prepared with the radiochemical purity of higher than 97% in less than 30 min. The biodistribution data for 68Ga-ECC showed the extraction of the most of the activity from the urinary tract. The absorbed dose was estimated based on biodistribution data in mice by the medical internal radiation dose (MIRD) method. Comparison between human absorbed dose estimation for these two agents indicated the values of approximately ten-fold higher after injection of 67Ga-ECC than 68Ga-ECC in the most organs. The results showed that 68Ga-ECC can be considered as a more potential agent for renal imaging compared to 67Ga-ECC.

Keywords: effective absorbed dose, ethylenecysteamine cysteine, Ga-67, Ga-68

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Authors: Arcady Ponosov., Ramazan Kadiev

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The work studies the global moment stability of solutions of systems of nonlinear differential Itô equations with delays. A modified regularization method (W-method) for the analysis of various types of stability of such systems, based on the choice of the auxiliaryequations and applications of the theory of positive invertible matrices, is proposed and justified. Development of this method for deterministic functional differential equations is due to N.V. Azbelev and his students. Sufficient conditions for the moment stability of solutions in terms of the coefficients for sufficiently general as well as specific classes of Itô equations are given.

Keywords: asymptotic stability, delay equations, operator methods, stochastic noise

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Authors: Richa Dhingra, Monika, Manav Malhotra, Tilak Raj Bhardwaj, Neelima Dhingra

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5-Alpha-reductases (5AR), a membrane bound, NADPH dependent enzyme and convert male hormone testosterone (T) into more potent androgen dihydrotestosterone (DHT). DHT is the required for the development and function of male sex organs, but its overproduction has been found to be associated with physiological conditions like Benign Prostatic Hyperplasia (BPH). Thus the inhibition of 5ARs could be a key target for the treatment of BPH. In present study, 2D and 3D Quantitative Structure Activity Relationship (QSAR) pharmacophore models have been generated for 5AR based on known inhibitory concentration (IC₅₀) values with extensive validations. The four featured 2D pharmacophore based PLS model correlated the topological interactions (–OH group connected with one single bond) (SsOHE-index); semi-empirical (Quadrupole2) and physicochemical descriptors (Mol. wt, Bromines Count, Chlorines Count) with 5AR inhibitory activity, and has the highest correlation coefficient (r² = 0.98, q² =0.84; F = 57.87, pred r² = 0.88). Internal and external validation was carried out using test and proposed set of compounds. The contribution plot of electrostatic field effects and steric interactions generated by 3D-QSAR showed interesting results in terms of internal and external predictability. The well validated 2D Partial Least Squares (PLS) and 3D k-nearest neighbour (kNN) models were used to search novel 5AR inhibitors with different chemical scaffold. To gain more insights into the molecular mechanism of action of these steroidal derivatives, molecular docking and in silico absorption, distribution, metabolism, and excretion (ADME) studies were also performed. Studies have revealed the hydrophobic and hydrogen bonding of the ligand with residues Alanine (ALA) 63A, Threonine (THR) 60A, and Arginine (ARG) 456A of 4AT0 protein at the hinge region. The results of QSAR, molecular docking, in silico ADME studies provide guideline and mechanistic scope for the identification of more potent 5-Alpha-reductase inhibitors (5ARI).

Keywords: 5α-reductase inhibitor, benign prostatic hyperplasia, ligands, molecular docking, QSAR

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Authors: Onyekachi Onwudike, Russell Lock, Iain Phillips

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The variability that exists across governments, her departments and the provisioning of services has been areas of concern in the E-Government domain. There is a need for reuse and integration across government departments which are accompanied by varying degrees of risks and threats. There is also the need for assessment, prevention, preparation, response and recovery when dealing with these risks or threats. The ability of a government to cope with the emerging changes that occur within it is known as resilience. In order to forge ahead with concerted efforts to manage reuse and integration induced risks or threats to governments, the ambiguities contained within resilience must be addressed. Enhancing resilience in the E-Government domain is synonymous with reducing risks governments face with provisioning of services as well as reuse of components across departments. Therefore, it can be said that resilience is responsible for the reduction in government’s vulnerability to changes. In this paper, we present the use of the ontology to measure the resilience of governments. This ontology is made up of a well-defined construct for the taxonomy of resilience. A specific class known as ‘Resilience Requirements’ is added to the ontology. This class embraces the concept of resilience into the E-Government domain ontology. Considering that the E-Government domain is a highly complex one made up of different departments offering different services, the reliability and resilience of the E-Government domain have become more complex and critical to understand. We present questions that can help a government access how prepared they are in the face of risks and what steps can be taken to recover from them. These questions can be asked with the use of queries. The ontology focuses on developing a case study section that is used to explore ways in which government departments can become resilient to the different kinds of risks and threats they may face. A collection of resilience tools and resources have been developed in our ontology to encourage governments to take steps to prepare for emergencies and risks that a government may face with the integration of departments and reuse of components across government departments. To achieve this, the ontology has been extended by rules. We present two tools for understanding resilience in the E-Government domain as a risk analysis target and the output of these tools when applied to resilience in the E-Government domain. We introduce the classification of resilience using the defined taxonomy and modelling of existent relationships based on the defined taxonomy. The ontology is constructed on formal theory and it provides a semantic reference framework for the concept of resilience. Key terms which fall under the purview of resilience with respect to E-Governments are defined. Terms are made explicit and the relationships that exist between risks and resilience are made explicit. The overall aim of the ontology is to use it within standards that would be followed by all governments for government-based resilience measures.

Keywords: E-Government, Ontology, Relationships, Resilience, Risks, Threats

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Authors: Nana Weng

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From 2008, Chinese Foreign Direct Investment flows to the European Union continued its rapid rise. Currently, the industrial structure adjustment in developing countries has also been placed on the international movement of factors of production. Now China economy is in an important period of transformation on industrial structure adjustment. Under the international transfer of industry background, the adjustment of industrial structure upgrading and sophistication are the key elements of a successful economic transformation. In order to achieve a virtuous cycle of foreign investment patterns and optimize the industrial structure of foreign direct investment as well, the research on the positive the role of the EU direct investment and how it impact China’s industrial structure optimization and upgrading is of great significance. In this paper, the author explained how the EU as an investment destination is different with the United States and ASEAN. Then, based on the theory of FDI and industrial structure and combining the four kinds of motives of China’s ODI in EU, this paper explained the impact mechanism which has influenced China domestic industrial structure primarily through the Transfer effect, Correlation effect and Competitive effect. On the premise that FDI activities do affect the home country’s domestic industrial structure, this paper made empirical analysis with industrial panel data. With the help of Gray Correlation Method and Limited Distributed Lags, this paper found that China/s ODI in the EU impacted the tertiary industry strongly and had a significant positive impact, particularly the manufacturing industry and the financial industry. This paper also pointed out that Chinese MNEs should realize several issues, such as pay more attention to high-tech industries so that they can make the best use of reverse technology spillover. When Chinese enterprises ‘go out,' they ought to keep in mind that domestic research and development capital contribution can make greater economic growth. Finally, based on theoretical and empirical analysis results, this paper presents the industry choice recommendations in the future of the EU direct investment, particularly through the development of the proper rational industrial policy and industrial development strategic to guide the industrial restructuring and upgrading.

Keywords: china ODI in european union, industrial structure optimization, impact mechanism, empirical analysis

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Authors: Rachmat Mauludin, Dita Sasri Primaviri, Irda Fidrianny

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Propolis contains several antioxidant compounds which can be used in topical application to protect skin against free radical, prevent skin cancer and skin aging. Previous study showed that 70% ethanolic extract of propolis (EEP) provided the greatest antioxidant activity. Since EEP has very small solubility in water, the extract was prepared in nanoemulsion (NE). Nanoemulsion is chosen as cosmetic dosage forms according to its properties namely to decrease the risk of skin’s irritation, increase penetration, prolong its time to remain in our skin, and improve stability. Propolis was extracted using reflux methods and concentrated using rotavapor. EEP was characterized with several tests such as phytochemical screening, density, and antioxidant activity using DPPH method. Optimation of total surfactant, co-surfactant, oil, and amount of EEP that can be included in NE were required to get the best NE formulation. The evaluations included to organoleptic observation, globul size, polydispersity index, morphology using TEM, viscosity, pH, centrifuge, stability, Freeze and Thaw test, radical scavenging activity using DPPH method, and primary irritation test. The yield extracts was 11.12% from raw propolis contained of steroid/triterpenoid, flavonoid, and saponin based on phytochemical screening. EEP had the value of DPPH scavenging activity 61.14% and IC50 0.41629 ppm. The best NE formulation consisted of 26.25% Kolliphor RH40; 8.75% glycerine; 5% rice bran oil; and 3% EEP. NE was transparant, had globul size of 21.9 nm; polydispersity index of 0.338; and pH of 5.67. Based on TEM morphology, NE was almost spherical and has particle size below 50 nm. NE propolis revealed to be physically stable after stability test within 63 days at 25oC, centrifuged for 30 mins at 13.000 rpm, and passed 6 cycles of Freeze and Thaw test without separated. NE propolis reduced 58% of free radical DPPH similar to antioxidant activity of the original extracts. Antioxidant activity of NE propolis is relatively stable after stored for 6 weeks. NE Propolis was proven to be safe by primary irritation test with the value of primary irritation index (OECD) was 0. The best formulation for NE propolis contained of 26.25% Kolliphor RH40; 8.75% glycerine; 5% rice bran oil; and 3% EEP with globul size of 21.9 nm and polydispersity index of 0.338. NE propolis was stable and had antioxidant activity similar to EEP.

Keywords: propolis, antioxidant, nanoemulsion, irritation test

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Authors: Anastasia Poliakova

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Harmful algal bloom (HAB) is a known negative phenomenon that is caused both by natural factors and anthropogenic influence. HABs can result in a series of deleterious effects, such as beach fouling, paralytic shellfish poisoning, mass mortality of marine species, and a threat to human health, especially if toxins pollute drinking water or occur nearby public resorts. In South China, the problem of HABs has an ultimately important meaning. For this study, we used a 1.5 m sediment core LAX-2018-2 collected in 2018 from the Zhanjiang Mangrove National Nature Reserve (109°03´E, 20°30´N), Guangdong Province, South China. High-resolution coastal environment reconstruction with a specific focus on the HABs history during the last ca 2500 yrs was attempted. Age control was performed with five radiocarbon dates obtained from benthic foraminifera. A total number of 71 dinoflagellate cyst types was recorded. The most common types found consistently throughout the sediment sequence were autotrophic Spiniferites spp., Spiniferites hyperacanthus and S. mirabilis, S. ramosus, Operculodinium centrocarpum sensu Wall and Dale 1966, Polysphaeridium zoharyi, and heterotrophic Brigantedinium ssp., cyst of Gymnodinium catenatum and cysts mixture of Protoperidinium. Three local dinoflagellate zones LAX-1 to LAX-3 were established based on the results of the constrained cluster analysis and data ordination; additionally, the middle zone LAX-2 was derived into two subzones, LAX-2a and LAX-2b based on the dynamics of toxic and heterotrophic cysts as well as on the significant changes (probability, P=0.89) in percentages of eutrophic indicators. The total cyst count varied from 106 to 410 dinocysts per slide, with 177 cyst types on average. Dinocyst assemblages are characterized by high values of the dost-depositional degradation index (kt) that varies between 3.6 and 7.6 (averaging 5.4), which is relatively high and is very typical for the areas with selective dinoflagellate cyst preservation that is related to bottom-water oxygen concentrations.

Keywords: reconstruction of palaeoenvironment, harmful algal blooms, anthropogenic influence on coastal zones, South China Sea

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