Search results for: Maximum Entropy Bootstrapping approach

Authors: Nicholas Fletcher, Zachary Houston, Yongmei Zhao, Christopher Howard, Kristofer Thurecht

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One promising approach to enhance nanomedicine therapeutic efficacy is to include a targeting agent, such as an antibody, to increase accumulation at the tumor site. However, the application of such targeted nanomedicines remains limited, in part due to difficulties involved with biomolecule conjugation to synthetic nanomaterials. One approach recently developed to overcome this has been to engineer bispecific antibodies (BsAbs) with dual specificity, whereby one portion binds to methoxy polyethyleneglycol (mPEG) epitopes present on synthetic nanomedicines, while the other binds to molecular disease markers of interest. In this way, noncovalent complexes of nanomedicine core, comprising a hyperbranched polymer (HBP) of primarily mPEG, decorated with targeting ligands are able to be produced by simple mixing. Further work in this area has now demonstrated such complexes targeting the breast cancer marker epidermal growth factor receptor (EGFR) to show enhanced binding to tumor cells both in vitro and in vivo. Indeed the enhanced accumulation at the tumor site resulted in improved therapeutic outcomes compared to untargeted nanomedicines and free chemotherapeutics. The current work on these BsAb-HBP conjugates focuses on further probing antibody-nanomaterial interactions and demonstrating broad applicability to a range of cancer types. Herein are reported BsAb-HBP materials targeted towards prostate-specific membrane antigen (PSMA) and study of their behavior in vivo using ⁸⁹Zr positron emission tomography (PET) in a dual-tumor prostate cancer xenograft model. In this model mice bearing both PSMA+ and PSMA- tumors allow for PET imaging to discriminate between nonspecific and targeted uptake in tumors, and better quantify the increased accumulation following BsAb conjugation. Also examined is the potential for formation of these targeted complexes in situ following injection of individual components? The aim of this approach being to avoid undesirable clearance of proteinaceous complexes upon injection limiting available therapeutic. Ultimately these results demonstrate BsAb functionalized nanomaterials as a powerful and versatile approach for producing targeted nanomedicines for a variety of cancers.

Keywords: bioengineering, cancer, nanomedicine, polymer chemistry

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Authors: In-Lee Choi, Min Jae Jeong, Jun Pill Baek, Ho-Min Kang

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As the consumption trends of vegetables become different from the past, it is increased using vegetable more convenience such as fresh-cut vegetables, sprouts, baby vegetables rather than an existing hole piece of vegetables. Selected baby vegetables have various functional materials but they have short shelf life. This study was conducted to improve storability by using suitable laser ablation OTR (oxygen transmission rate) films. Baby vegetable of endive (Cichorium endivia L.) and pak choi (Brassica rapa chinensis) for this research, around 10 cm height, cultivated in glass greenhouse during 3 weeks. Harvested endive and pak choi were stored at 8 ℃ for 5 days and were packed by PP (Polypropylene) container and covered different types of laser ablation OTR film (DaeRyung Co., Ltd.) such as 1,300 cc, 10,000 cc, 20,000 cc, 40,000 cc /m2•day•atm, and control (perforated film) with heat sealing machine (SC200-IP, Kumkang, Korea). All the samples conducted 5 times replication. Statistical analysis was carried out using a Microsoft Excel 2010 program and results were expressed as standard deviations. The fresh weight loss rate of both baby vegetables were less than 0.3 % in treated films as maximum weight loss rate. On the other hands, control in the final storage day had around 3.0 % weight loss rate and it followed decreasing quantity. Endive had less 2.0 % carbon dioxide contents as maximum contents in 20,000 cc and 40,000 cc. Oxygen contents was maintained between 17 and 20 % in endive, 19 and 20 % in pak choi. Ethylene concentration of both vegetables maintained little lower contents in 20,000 cc treatments than others at final storage day without statistical significance. In the case of hardness, 40,000 cc film was shown little higher value at both baby vegetables without statistical significance. Visual quality was good at 10,000 cc and 20,000 cc in endive and pak choi, and off-flavor was not appeard any off-flavor in both vegetables. Chlorophyll (SPAD-502, Minolta, Japan) value of endive was shown as similar result with initial in all treatments except 20,000 cc as little lower. And chlorophyll value of pak choi decreased in all treatments compared with initial value but was not shown significantly difference each other. Color of leaves (CR-400, Minolta, Japan) changed significantly in 40,000 cc at endive. In an event of pak choi, all the treatments started yellowing by increasing hunter b value, among them control increased substantially. As above the result, 10,000 cc film was most reasonable packaging film for storing at endive and 20,000 cc at pak choi with good quality.

Keywords: carbon dioxide, shelf-life, visual quality, pak choi

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Authors: Kapila Warnakulasuriya, Walimuni Janaka Mendis

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In this study, an artificial intelligence-based approach is developed to diagnose abnormal tissues in human or animal bodies by analyzing magnetic resonance signals. As opposed to the conventional method of generating an image from the magnetic resonance signals, which are then evaluated by a radiologist for the diagnosis of abnormalities, in the discussed approach, the magnetic resonance signals are analyzed by an artificial intelligence algorithm without having to generate or analyze an image. The AI-based program compares magnetic resonance signals with millions of possible magnetic resonance waveforms which can be generated from various types of normal tissues. Waveforms generated by abnormal tissues are then identified, and images of the abnormal tissues are generated with the possible location of them in the body for further diagnostic tests.

Keywords: magnetic resonance, artificial intelligence, magnetic waveform analysis, abnormal tissues

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Authors: De Castro-Pardo M., Cabello J. M., Martin J. M., Ruiz F.

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In this paper, we propose a new Water Sustainability Indicator based on a Multi-Reference methodology that permits modeling compensation between the analysed criteria and provides a participative approach. The proposed indicator provides results based on 19 variables grouped into 5 dimensions: availability, access, resilience, good governance and economic capacity. The indicator was applied to assess water sustainability in 27 European countries. The results showed that Finland, the Netherlands, Sweden and the United Kingdom obtained the best global results in terms of weak water (compensatory) sustainability. In terms of strong water (non-compensatory) sustainability, no country gained acceptable results in terms of strong sustainability. Climate change and the state of freshwater resources were detected as especially vulnerable in all the analysed countries. The results identified some eastern European countries with low GDP and good performance of availability and cost of water, with bad results in terms of governance and water productivity. These results could jeopardize water sustainability in the event of a potential economic development if these limitations are not addressed. In a context of economic and political instability due to the current armed conflict in nearby countries such as Ukraine, it is especially important to pay attention to these countries, whose good governance indicators could worsen even more. The proposed indicator allowed to the identification of warning signs and could contribute to the improvement in decision-making processes. Moreover, it could improve the monitoring of international water policies.

Keywords: water sustainability, composite indicators, compensatory approach, sustainability European policies

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Authors: Faiza Mahi, Fatima Debbat, Mohamed Fayçal Khelfi

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This paper proposes a control approach using Fuzzy Lo system. More precisely, the study focuses on the improvement of users service in terms of analysis and control of a transportation system their waiting times in the exchange platforms of passengers. Many studies have been developed in the literature for such problematic, and many control tools are proposed. In this paper we focus on the use of fuzzy logic technique to control the system during its evolution in order to minimize the arrival gap of connected transportation means at the exchange points of passengers. An example of illustration is worked out and the obtained results are reported. an important area of research is the modeling and simulation ordering system. We describe an approach to analysis using Fuzzy Logic. The hybrid simulator developed in toolbox Matlab consists calculation of waiting time transportation mode.

Keywords: Fuzzy logic, Hybrid system, Waiting Time, Transportation system, Control

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Authors: Brian W. Mandikiana

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Homestead food production has the potential to alleviate hunger, improve health and nutrition for children and adults. This article examines the relationship between self-reported hunger and homestead food production using the ordered probit model. A sample of households participating in homestead food production was drawn from the first wave of the South African National Income Dynamics Survey, a nationally representative cross-section. The sample selection problem was corrected using an ordered probit model with sample selection approach. The findings show that homestead food production exerts a positive and significant impact on children and adults’ ability to cope with hunger and malnutrition. Yet, on the contrary, potential gains of homestead food production are threatened by shocks such as crop failure.

Keywords: agriculture, hunger, nutrition, sample selection

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Authors: Artur Matuck, Guilherme F. Nobre

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Machines can be either tool, media, or social agents. Advances in technology have been delivering machines capable of autonomous expression, both through communication and art. This paper deals with models (theoretical approach) and experiments (applied approach) related to artificial agents. On one hand it traces how social sciences' scholars have worked with topics such as text automatization, man-machine writing cooperation, and communication. On the other hand it covers how computer sciences' scholars have built communicative and artistic machines, including the programming of creativity. The aim is to present a brief survey on artificially intelligent communicators and artificially creative writers, and provide the basis to understand the meta-authorship and also to new and further man-machine co-authorship.

Keywords: artificial communication, artificial creativity, artificial writers, meta-authorship, robotic art

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Authors: Mariayee Doraisamy, Suhaimi bin Ibrahim, Mohd Naz’ri Mahrin

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There are several methods to monitor software projects and the objective for monitoring is to ensure that the software projects are developed and delivered successfully. A performance measurement is a method that is closely associated with monitoring and it can be scrutinized by looking at two important attributes which are efficiency and effectiveness both of which are factors that are important for the success of a software project. Consequently, a successful steering is achieved by monitoring and controlling a software project via the performance measurement criteria and metrics. Hence, this paper is aimed at identifying the performance measurement criteria and the metrics for monitoring the performance of a software project by using the Goal Question Metrics (GQM) approach. The GQM approach is utilized to ensure that the identified metrics are reliable and useful. These identified metrics are useful guidelines for project managers to monitor the performance of their software projects.

Keywords: component, software project performance, goal question metrics, performance measurement criteria, metrics

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Authors: Kolade Olawande Owoeye, George Weir

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Terrorism and extremism activities on the internet are becoming the most significant threats to national security because of their potential dangers. In response to this challenge, law enforcement and security authorities are actively implementing comprehensive measures by countering the use of the internet for terrorism. To achieve the measures, there is need for intelligence gathering via the internet. This includes real-time monitoring of potential websites that are used for recruitment and information dissemination among other operations by extremist groups. However, with billions of active webpages, real-time monitoring of all webpages become almost impossible. To narrow down the search domain, there is a need for efficient webpage classification techniques. This research proposed a new approach tagged: SentiPosit-based method. SentiPosit-based method combines features of the Posit-based method and the Sentistrenght-based method for classification of terrorism and extremism webpages. The experiment was carried out on 7500 webpages obtained through TENE-webcrawler by International Cyber Crime Research Centre (ICCRC). The webpages were manually grouped into three classes which include the ‘pro-extremist’, ‘anti-extremist’ and ‘neutral’ with 2500 webpages in each category. A supervised learning algorithm is then applied on the classified dataset in order to build the model. Results obtained was compared with existing classification method using the prediction accuracy and runtime. It was observed that our proposed hybrid approach produced a better classification accuracy compared to existing approaches within a reasonable runtime.

Keywords: sentiposit, classification, extremism, terrorism

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Authors: Fadoua Ouamani, Narjès Bellamine Ben Saoud, Henda Hajjami Ben Ghézala

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In the last few years and over the last decades, there was a growing interest in the development of Computer Supported Collaborative Learning (CSCL) environments. However, the existing systems ignore the variety of learners and their socio-cultural differences, especially in the case of distant and networked learning. In fact, within such collaborative learning environments, learners from different socio-cultural backgrounds may interact together. These learners evolve within various cultures and social contexts and acquire different socio-cultural values and behaviors. Thus, they should be assisted while communicating and collaborating especially in an intercultural group. Besides, the communication and collaboration tools provided to each learner must depend on and be adapted to her/his socio-cultural profile. The main goal of this paper is to present the proposed socio-cultural adaptation approach based on and guided by ontologies to adapt CSCL environments to the socio-cultural profiles of its users (learners or others).

Keywords: CSCL, socio-cultural profile, adaptation, ontology

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Authors: Mohammad Reza Oftadeh

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The purpose of the article is to describe project objective structure (POS) concept that was developed on research activities and experiences about project management, Balanced Scorecard (BSC) and European Foundation Quality Management Excellence Model (EFQM Excellence Model). Furthermore, this paper tries to define a balanced, systematic, and integrated measurement approach to meet project objectives and project strategic goals based on a process-oriented model. In this paper, POS is suggested in order to measure project performance in the project life cycle. After using the POS model, the project manager can ensure in order to achieve the project objectives on the project charter. This concept can help project managers to implement integrated and balanced monitoring and control project work.

Keywords: project objectives, project performance management, PMBOK, key performance indicators, integration management

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Authors: Abdelaziz Hussien

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This article reports investigations of a study into the effectiveness of a traits cooperative learning (TCL) on teacher candidates’ writing achievement, composition, and attitudes towards traits of writing approach and small group learning. Mixed methodologies were used with the participants in a repeated measures quasi-experimental design. Forty-two class teacher candidates, enrolled in the Bahrain Teachers College, completed the pre and post author-developed measures. The results suggest that TCL has a positive effect on the participants’ writing achievement, composition, and attitudes towards traits of writing approach, but not on the attitudes towards small group learning. Further implications to teacher education are presented.

Keywords: trait-based language education, cooperative learning, writing achievement, writing composition, traits of writing, teacher education

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Authors: Sai Maniveer Adapa, Sai Guptha Perla, Adithya Reddy P.

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Thyroid nodules can often be diagnosed with ultrasound imaging, although differentiating between benign and malignant nodules can be challenging for medical professionals. This work suggests a novel approach to increase the precision of thyroid nodule identification by combining machine learning and deep learning. The new approach first extracts information from the ultrasound pictures using a deep learning method known as a convolutional autoencoder. A support vector machine, a type of machine learning model, is then trained using these features. With an accuracy of 92.52%, the support vector machine can differentiate between benign and malignant nodules. This innovative technique may decrease the need for pointless biopsies and increase the accuracy of thyroid nodule detection.

Keywords: thyroid tumor diagnosis, ultrasound images, deep learning, machine learning, convolutional auto-encoder, support vector machine

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Authors: Karen Odendaal

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Accounting transactions are becoming more complex, and more extensive accounting guidance is provided on a continuous basis. It is widely perceived that conceptual teaching of accounting contributes to lifelong learning. Such a conceptual teaching approach also contributes to effective accounting problem-solving. This framework-based approach is rooted in educational psychologies such as constructivism and Ausubel’s subsumption theory. This study aimed at investigating the ability of students to solve complex accounting problems by using only concepts underlying the Conceptual Framework. An assignment was administered to pre-graduate students at a South African university and this study made use of an interpretative research design which implemented multiple research instruments to investigate the ability of students to solve complex accounting problems using only concepts underlying the Conceptual Framework. Student perceptions were analysed and were aided by a related reflective questionnaire. The importance of the study indicates the necessity of Accounting educators to enhance a conceptual understanding among students as a mechanism for problem-solving of accounting issues. The results indicate that the ability of students to solve accounting problems effectively using only the Conceptual Framework depends on the complexity of the scenario and the students’ familiarity with the problem. The study promotes a balanced and more conceptual (rather than only technical) preference to the problem-solving of complex accounting problems. The study indubitably promotes considerable emphasis on the importance of the Conceptual Framework in accounting education and the promotion of life-long learning in the subject field.

Keywords: accounting education, conceptual teaching, constructivism, framework-based, problem-solving

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Authors: H. Hosseini, B. V. Berdyshev, I. Iskopintsev

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This paper presents a rheological model for producing shape-memory thermoplastic polymers. Shape-memory occurs as a result of internal rearrangement of the structural elements of a polymer. A non-linear viscoelastic model was developed that allows qualitative and quantitative prediction of the stress-strain behavior of shape-memory polymers during heating. This research was done to develop a technique to determine the maximum possible change in size of heat-shrinkable products during heating. The rheological model used in this work was particularly suitable for defining process parameters and constructive parameters of the processing equipment.

Keywords: elastic deformation, heating, shape-memory polymers, stress-strain behavior, viscoelastic model

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Authors: Maryam Memarian, Mahmood Naghizadeh

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Deconstruction is an approach that is entirely incompatible with the traditional prevalent architecture. Considering the fact that this approach attempts to put architecture in sharp contrast with its opposite events and transpires with attending to the neglected and missing aspects of architecture and deconstructing its stable structures. It also recklessly proceeds beyond the existing frameworks and intends to create a different and more efficient prospect for space. The aim of deconstruction architecture is to satisfy both the prospective and retrospective visions as well as takes into account all tastes of the present in order to transcend time. Likewise, it ventures to fragment the facts and symbols of the past and extract new concepts from within their heart, which coincide with today’s circumstances. Since this approach is an attempt to surpass the limits of the prevalent architecture, it can be employed to design places in which creative events occur and imagination and ambition flourish. Thought-provoking artistic events can grow and mature in such places and be represented in the best way possible to all people. The concept of event proposed in the plan grows out of the interaction between space and creation. In addition to triggering surprise and high impressions, it is also considered as a bold journey into the suspended realms of the traditional conflicts in architecture such as architecture-landscape, interior-exterior, center-margin, product-process, and stability-instability. In this project, at first, through interpretive-historical research method and examining the inputs and data collection, recognition and organizing takes place. After evaluating the obtained data using deductive reasoning, the data is eventually interpreted. Given the fact that the research topic is in its infancy and there is not a similar case in Iran with limited number of corresponding instances across the world, the selected topic helps to shed lights on the unrevealed and neglected parts in architecture. Similarly, criticizing, investigating and comparing specific and highly prized cases in other countries with the project under study can serve as an introduction into this architecture style.

Keywords: anti-architecture, creativity, deconstruction, event

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Authors: Serag El Hegazi

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The development of an assessment methodological framework for local and institutional sustainability is a key factor for future development plans and visions. This paper develops an approach to local and institutional sustainability assessment (ALISA). The ALISA methodology is a methodological framework that assists in the clarification, formulation, preparation, selection, and ranking of key indicators to facilitate the assessment of the level of sustainability at the local and institutional levels in North African and Middle Eastern cities. According to the literature review, this paper formulates a methodological framework, ALISA, which is a combination of the UNCSD (2001) Theme Indicators Framework and the issue-based Framework illustrated by McLaren (1996). The methodological framework has been implemented to formulate, select, and prioritise key indicators that most directly reflect the issues of a case study at the local community and institutional level. Yet, in the meantime, there is a lack of clear indicators and frameworks that can be developed to apply successfully at the local and institutional levels in the MENA Region, particularly in the cities of Benghazi and Amman. This is an essential issue for sustainability development estimation. Therefore, a conceptual framework was developed to be tested as a methodology to collect and classify data. The Approach to Local and Institutional Sustainability Assessment (ALISA) is a methodological framework that was developed to apply to certain cities in the MENA region. The main goal is to develop the ALISA framework to formulate, choose, and prioritize sustainability key indicators, which then can assist in guiding an assessment progress to improve decisions and policymakers towards the development of sustainable cities at the local and institutional level in the city of Benghazi. The conceptual, methodological framework, which supports this research with joint documentary and analysed data in two case studies, including focus-group discussions, semi-structured interviews, and questionnaires, reflects the approach required to develop a combined framework that assists the development of sustainability indicators. To achieve this progress and reach the aim of this paper, which is developing a practical approach for sustainability indicators framework that could be used as a tool to develop local and institutional sustainability indicators, appropriate stages must be applied to propose a set of local and institutional sustainability indicators as follows: Step one: issues clarifications, Step two: objectives formation/analysing of issues and boundaries, Step three: indicators preparation, First list of proposed indictors, Step four: indicator selection, Step five: indicator rating/ranking.

Keywords: sustainability indicators, approach to local and institutional level, ALISA, policymakers

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Authors: Wan You Ning

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Addressing the rising prevalence of mental health issues among youths, the Multi-dimensional Approach to Resilience and Support in Advanced School-based Mental Health Service Delivery (MARS-ASMHSD) framework proposes the implementation of advanced mental health services in low-resource areas to further instil mental health resilience among students in a school-based setting. Recognizing the unsustainability of direct service delivery due to rapidly growing demands and costs, the MARS-ASMHSD framework endorses the deinstitutionalization of mental healthcare and explores a tiered, multi-dimensional approach in mental healthcare provision, establishing advanced school-based mental health service delivery. The framework is developed based on sustainable and credible evidence-based practices and modifications of existing mental health service deliveries in Asia, including Singapore, Thailand, Malaysia, Japan, and Taiwan. Dissemination of the framework model for implementation will enable a more progressive and advanced school-based mental health service delivery in low-resource areas. Through the evaluation of the mental health landscape and the role of stakeholders in the respective countries, the paper concludes with a multi-dimensional framework model for implementation in low-resource areas. A mixed-method independent research study is conducted to facilitate the framework's development.

Keywords: mental health, youths, school-based services, framework development

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Authors: S. Benzitouni, M. Zaabat, A. Mahdjoub, A. Benaboud, T.Saidani ‎

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To improve the physical properties of ZnO nanostructures textured (103) by sol-gel ‎dip coating method, Al and In are used as dopant with different weight ratios (5%, 10%). ‎The comparative study between Al doped ZnO thin films (AZO) and In doped ZnO (IZO) ‎are made by different analysis technic. XRD showed that the films are Pollycristallins with ‎hexagonal wûrtzite structure and preferred orientation (002) and (103). UV-Vis ‎spectroscopy showed that all films have a high transmission (> 85%); the interference ‎fringes are only observed for IZO. The optical gap is reduced due to the introduction of In ‎‎(minimum value is 3.12 eV), but increased in the presence of Al (maximum value is 3.34 ‎eV). The thickness of the layers was obtained by modeling (using Forouhi Bloomer ‎method). AFM used to observe the surface texture of the films and determined grain size ‎and surface roughness (RMS) which varies in a small range [3.14 to 1.25] nm‎.

Keywords: ZnO, optical gap, roughness (RMS), nanostructures‎

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Authors: Alex Ellery

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Geoengineering approaches to climate change mitigation are unpopular and regarded with suspicion. Of these, space-based approaches are regarded as unworkable and enormously costly. Here, a space-based approach is presented that is modest in cost, fully controllable and reversible, and acts as a natural spur to the development of solar power satellites over the longer term as a clean source of energy. The low-cost approach exploits self-replication technology which it is proposed may be enabled by 3D printing technology. Self-replication of 3D printing platforms will enable mass production of simple spacecraft units. Key elements being developed are 3D-printable electric motors and 3D-printable vacuum tube-based electronics. The power of such technologies will open up enormous possibilities at low cost including space-based geoengineering.

Keywords: 3D printing, in-situ resource utilization, self-replication technology, space-based geoengineering

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Authors: Wuthichai Wongthatsanekorn, Nuntana Matheekrieangkrai

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This research proposes Bee Algorithm (BA) to optimize Ready Mixed Concrete (RMC) truck scheduling problem from single batch plant to multiple construction sites. This problem is considered as an NP-hard constrained combinatorial optimization problem. This paper provides the details of the RMC dispatching process and its related constraints. BA was then developed to minimize total waiting time of RMC trucks while satisfying all constraints. The performance of BA is then evaluated on two benchmark problems (3 and 5construction sites) according to previous researchers. The simulation results of BA are compared in term of efficiency and accuracy with Genetic Algorithm (GA) and all problems show that BA approach outperforms GA in term of efficiency and accuracy to obtain optimal solution. Hence, BA approach could be practically implemented to obtain the best schedule.

Keywords: bee colony optimization, ready mixed concrete problem, ruck scheduling, multiple construction sites

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Authors: Stephanie Chen, Mitja Echim, Christof Büskens

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To describe and propagate the behavior of a system mathematical models are formulated. Parameter identification is used to adapt the coefficients of the underlying laws of science. For complex systems this approach can be incomplete and hence imprecise and moreover too slow to be computed efficiently. Therefore, these models might be not applicable for the numerical optimization of real systems, since these techniques require numerous evaluations of the models. Moreover not all quantities necessary for the identification might be available and hence the system must be adapted manually. Therefore, an approach is described that generates models that overcome the before mentioned limitations by not focusing on physical laws, but on measured (sensor) data of real systems. The approach is more general since it generates models for every system detached from the scientific background. Additionally, this approach can be used in a more general sense, since it is able to automatically identify correlations in the data. The method can be classified as a multivariate data regression analysis. In contrast to many other data regression methods this variant is also able to identify correlations of products of variables and not only of single variables. This enables a far more precise and better representation of causal correlations. The basis and the explanation of this method come from an analytical background: the series expansion. Another advantage of this technique is the possibility of real-time adaptation of the generated models during operation. Herewith system changes due to aging, wear or perturbations from the environment can be taken into account, which is indispensable for realistic scenarios. Since these data driven models can be evaluated very efficiently and with high precision, they can be used in mathematical optimization algorithms that minimize a cost function, e.g. time, energy consumption, operational costs or a mixture of them, subject to additional constraints. The proposed method has successfully been tested in several complex applications and with strong industrial requirements. The generated models were able to simulate the given systems with an error in precision less than one percent. Moreover the automatic identification of the correlations was able to discover so far unknown relationships. To summarize the above mentioned approach is able to efficiently compute high precise and real-time-adaptive data-based models in different fields of industry. Combined with an effective mathematical optimization algorithm like WORHP (We Optimize Really Huge Problems) several complex systems can now be represented by a high precision model to be optimized within the user wishes. The proposed methods will be illustrated with different examples.

Keywords: adaptive modeling, automatic identification of correlations, data based modeling, optimization

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Authors: Ahmed Tahsin Shams

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The right to dissent through any form of art has been facing challenges through various strict legal measures, particularly since 2018 when the Government of Bangladesh passed the Digital Security Act 2018 (DSA). Therefore, the references to ‘popular’ culture mostly include mainstream religious and national festivals and exclude critical intellectual representation of specific political allusions in any form of storytelling: whether wall art or fiction writing, since the post-DSA period in Bangladesh. Through inductive quantitative and qualitative methodological approaches, this paper aims to study the pattern of censorship, detention or custodial tortures against artists and the banning approach by the Bangladeshi government in the last five years, specifically against static visual arts, i.e., cartoon and wall art. The pattern drawn from these data attempts to redefine the popular notion of ‘pop culture’ as an unorganized folk or mass culture. The results also hypothesize how the post-DSA period forcefully constructs ‘pop culture’ as a very organized repetitive deception of enlightenment or entertainment. Thus the argument theorizes that this censoring trend is a fascist approach making the artists subaltern. So, in this socio-political context, these two similar and overlapping elements: culture and art, are vastly separated in two streams: the former being appreciated by the power, and the latter is a fearful concern for the power. Therefore, the purpose of art also shifts from entertainment to an act of rebellion, adding more layers to the new postmodern definition of ‘pop culture.’

Keywords: popular culture, visual arts, censoring trend, fascist approach, subaltern, digital security act

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Authors: Mariam Vardiashvili

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The economic value of the asset impairment process is quite large. Impairment reflects the reduction of future economic benefits or service potentials itemized in the asset. The assets owned by public sector entities bring economic benefits or are used for delivery of the free-of-charge services. Consequently, they are classified as cash-generating and non-cash-generating assets. IPSAS 21 - Impairment of non-cash-generating assets, and IPSAS 26 - Impairment of cash-generating assets, have been designed considering this specificity.  When measuring impairment of assets, it is important to select the relevant methods. For measurement of the impaired Non-Cash-Generating Assets, IPSAS 21 recommends three methods: Depreciated Replacement Cost Approach, Restoration Cost Approach, and  Service Units Approach. Impairment of Value in Use of Cash-Generating Assets (according to IPSAS 26) is measured by discounted value of the money sources to be received in future. Value in use of the cash-generating asserts (as per IPSAS 26) is measured by the discounted value of the money sources to be received in the future. The article provides classification of the assets in the public sector  as non-cash-generating assets and cash-generating assets and, deals also with the factors which should be considered when evaluating  impairment of assets. An essence of impairment of the non-financial assets and the methods of measurement thereof evaluation are formulated according to IPSAS 21 and IPSAS 26. The main emphasis is put on different methods of measurement of the value in use of the impaired Cash-Generating Assets and Non-Cash-Generation Assets and the methods of their selection. The traditional and the expected cash flow approaches for calculation of the discounted value are reviewed. The article also discusses the issues of recognition of impairment loss and its reflection in the financial reporting. The article concludes that despite a functional purpose of the impaired asset, whichever method is used for measuring the asset, presentation of realistic information regarding the value of the assets should be ensured in the financial reporting. In the theoretical development of the issue, the methods of scientific abstraction, analysis and synthesis were used. The research was carried out with a systemic approach. The research process uses international standards of accounting, theoretical researches and publications of Georgian and foreign scientists.

Keywords: cash-generating assets, non-cash-generating assets, recoverable (usable restorative) value, value of use

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Authors: Nelson Lujara

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The paper presents a practical three-phase PWM inverter suitable for low voltage, low rating energy efficient systems. The work in the paper is conducted with the view to establishing the significance of the loss contribution from the PWM inverter in the determination of the complete losses of a photovoltaic (PV) array-powered induction motor drive water pumping system. Losses investigated include; conduction and switching loss of the devices and gate drive losses. It is found that the PWM inverter operates at a reasonable variable efficiency that does not fall below 92% depending on the load. The results between the simulated and experimental results for the system with or without a maximum power tracker (MPT) compares very well, within an acceptable range of 2% margin.

Keywords: energy, inverter, losses, photovoltaic

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Authors: Somaya Adwan, Rasha Majed, Lamya'a Majed, Hamzah Arof

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In order to produce images with whole body parts, X-ray of different portions of the body parts is assembled using image stitching methods. A new method for image stitching that exploits mutually feature based method and direct based method to identify and merge pairs of X-ray medical images is presented in this paper. The performance of the proposed method based on this hybrid approach is investigated in this paper. The ability of the proposed method to stitch and merge the overlapping pairs of images is demonstrated. Our proposed method display comparable if not superior performance to other feature based methods that are mentioned in the literature on the standard databases. These results are promising and demonstrate the potential of the proposed method for further development to tackle more advanced stitching problems.

Keywords: image stitching, direct based method, panoramic image, X-ray

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Authors: S. B. Provost, Susan Sheng

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An alternative bivariate density estimation methodology is introduced in this presentation. The proposed approach involves estimating the density function associated with the marginal distribution of each of the two variables by means of the saddlepoint approximation technique and applying a bivariate polynomial adjustment to the product of these density estimates. Since the saddlepoint approximation is utilized in the context of density estimation, such estimates are determined from empirical cumulant-generating functions. In the univariate case, the saddlepoint density estimate is itself adjusted by a polynomial. Given a set of observations, the coefficients of the polynomial adjustments are obtained from the sample moments. Several illustrative applications of the proposed methodology shall be presented. Since this approach relies essentially on a determinate number of sample moments, it is particularly well suited for modeling massive data sets.

Keywords: density estimation, empirical cumulant-generating function, moments, saddlepoint approximation

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Authors: Lae-Jeong Park

Abstract:

The paper presents a method that utilizes figure-ground color segmentation to extract effective global feature in terms of false positive reduction in the head-shoulder detection. Conventional detectors that rely on local features such as HOG due to real-time operation suffer from false positives. Color cue in an input image provides salient information on a global characteristic which is necessary to alleviate the false positives of the local feature based detectors. An effective approach that uses figure-ground color segmentation has been presented in an effort to reduce the false positives in object detection. In this paper, an extended version of the approach is presented that adopts separate multipart foregrounds instead of a single prior foreground and performs the figure-ground color segmentation with each of the foregrounds. The multipart foregrounds include the parts of the head-shoulder shape and additional auxiliary foregrounds being optimized by a search algorithm. A classifier is constructed with the feature that consists of a set of the multiple resulting segmentations. Experimental results show that the presented method can discriminate more false positive than the single prior shape-based classifier as well as detectors with the local features. The improvement is possible because the presented approach can reduce the false positives that have the same colors in the head and shoulder foregrounds.

Keywords: pedestrian detection, color segmentation, false positive, feature extraction

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Authors: Hassan M. H. Mustafa

Abstract:

This piece of research addresses an interesting comparative analytical study. Which considers two concepts of diverse algorithmic computational intelligence approaches related tightly with Neural and Non-Neural Systems. The first algorithmic intelligent approach concerned with observed obtained practical results after three neural animal systems’ activities. Namely, they are Pavlov’s, and Thorndike’s experimental work. Besides a mouse’s trial during its movement inside figure of eight (8) maze, to reach an optimal solution for reconstruction problem. Conversely, second algorithmic intelligent approach originated from observed activities’ results for Non-Neural Ant Colony System (ACS). These results obtained after reaching an optimal solution while solving Traveling Sales-man Problem (TSP). Interestingly, the effect of increasing number of agents (either neurons or ants) on learning performance shown to be similar for both introduced systems. Finally, performance of both intelligent learning paradigms shown to be in agreement with learning convergence process searching for least mean square error LMS algorithm. While its application for training some Artificial Neural Network (ANN) models. Accordingly, adopted ANN modeling is a relevant and realistic tool to investigate observations and analyze performance for both selected computational intelligence (biological behavioral learning) systems.

Keywords: artificial neural network modeling, animal learning, ant colony system, traveling salesman problem, computational biology

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Authors: Philippe Larvet

Abstract:

This paper presents the concept of an object-based programming language where tests (if... then... else) and control structures (while, repeat, for...) disappear and are replaced by conditions on data. According to the object paradigm, by using this concept, data are still embedded inside objects, as variable-value couples, but object methods are expressed into the form of logical propositions (‘conditions on data’ or COD).For instance : variable1 = value1 AND variable2 > value2 => variable3 = value3. Implementing this approach, a central inference engine turns and examines objects one after another, collecting all CODs of each object. CODs are considered as rules in a rule-based system: the left part of each proposition (left side of the ‘=>‘ sign) is the premise and the right part is the conclusion. So, premises are evaluated and conclusions are fired. Conclusions modify the variable-value couples of the object and the engine goes to examine the next object. The paper develops the principles of writing CODs instead of complex algorithms. Through samples, the paper also presents several hints for implementing a simple mechanism able to process this ‘COD language’. The proposed approach can be used within the context of simulation, process control, industrial systems validation, etc. By writing simple and rigorous conditions on data, instead of using classical and long-to-learn languages, engineers and specialists can easily simulate and validate the functioning of complex systems.

Keywords: conditions on data, logical proposition, programming without code, object-oriented programming, system simulation, system validation

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