Search results for: fly ash based geopolymer

Authors: Arnault Morisson

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Innovation districts are being implemented as urban regeneration strategies in cities as diverse as Barcelona (Spain), Boston (Massachusetts), Chattanooga (Tennessee), Detroit (Michigan), Medellin (Colombia), and Montréal (Canada). Little, however, is known about the concept. This paper aims to provide a framework to define innovation districts. The research methodology is based on a qualitative approach using 22@ Barcelona as a case study. 22@ Barcelona was the first innovation district ever created and has been a model for the innovation districts of Medellin (Colombia) and Boston (Massachusetts) among others. Innovation districts based on the 22@ Barcelona’s model can be defined as top-down urban innovation ecosystems designed around four multilayered and multidimensional models of innovation: urban planning, productive, collaborative, and creative, all coordinated under strong leadership, with the ultimate objectives to accelerate the innovation process and competitiveness of a locality. Innovation districts aim to respond to a new economic paradigm in which economic production flows back to cities.

Keywords: innovation ecosystem, governance, technology park, urban planning, urban policy, urban regeneration

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Authors: Krassimir Todorov

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The purpose of the paper is to redefine the levels of structure of corporate, business and functional strategies that were established over the past several decades, to a conceptual model, consisting of corporate, business and operations strategies, that are reinforced by functional strategies. We will propose a conceptual framework of different perspectives in the role of strategic operations as a separate strategic place and reposition the remaining functional strategies as supporting tools, existing at all three levels. The proposed model is called ‘the strategic engine’, since the mutual relationships of its ingredients are identical with main elements and working principle of the internal combustion engine. Based on theoretical essence, related to every strategic level, we will prove that the strategic engine model is useful for managers seeking to safeguard the competitive advantage of their companies. Each strategy level is researched through its basic elements. At the corporate level we examine the scope of firm’s product, the vertical and geographical coverage. At the business level, the point of interest is limited to the SWOT analysis’ basic elements. While at operations level, the key research issue relates to the scope of the following performance indicators: cost, quality, speed, flexibility and dependability. In this relationship, the paper provides a different view for the role of operations strategy within the overall strategy concept. We will prove that the theoretical essence of operations goes far beyond the scope of traditionally accepted business functions. Exploring the applications of Resource-based theory and Market-based theory within the strategic levels framework, we will prove that there is a logical consequence of the theoretical impact in corporate, business and operations strategy – at every strategic level, the validity of one theory is substituted to the level of the other. Practical application of the conceptual model is tested in automotive industry. Actually, the proposed theoretical concept is inspired by a leading global automotive group – Inchcape PLC, listed on the London Stock Exchange, and constituent of the FTSE 250 Index.

Keywords: business strategy, corporate strategy, functional strategies, operations strategy

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Authors: Ahmed Hamida Boudinar, Noureddine Benouzza, Azeddine Bendiabdellah, Mohamed El Amine Khodja

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This paper describes a new diagnosis approach for identification of the progressive stator winding inter-turn short-circuit fault in induction motor. This approach is based on a simple monitoring of the combined information related to both magnitude and phase-angle obtained from the fundamental by the three line currents frequency analysis. In addition, to simplify the interpretation and analysis of the data; a new graphical tool based on a triangular representation is suggested. This representation, depending on its size, enables to visualize in a simple and clear manner, the existence of the stator inter-turn short-circuit fault and its discrimination with respect to a healthy stator. Experimental results show well the benefit and effectiveness of the proposed approach.

Keywords: induction motor, magnitude, phase-angle, spectral analysis, stator fault

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Authors: Maamar Ali Saud Al Tobi, Geraint Bevan, K. P. Ramachandran, Peter Wallace, David Harrison

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Centrifugal pumps are complex machines which can experience different types of fault. Condition monitoring can be used in centrifugal pump fault detection through vibration analysis for mechanical and hydraulic forces. Vibration analysis methods have the potential to be combined with artificial intelligence systems where an automatic diagnostic method can be approached. An automatic fault diagnosis approach could be a good option to minimize human error and to provide a precise machine fault classification. This work aims to introduce an approach to centrifugal pump fault diagnosis based on artificial intelligence and genetic algorithm systems. An overview of the future works, research methodology and proposed experimental setup is presented and discussed. The expected results and outcomes based on the experimental work are illustrated.

Keywords: centrifugal pump setup, vibration analysis, artificial intelligence, genetic algorithm

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Authors: Minho Lee, Donghyun Back, Jaemoon Jung, Woojin Park

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The current 3-dimensional (3D) posture prediction models commonly provide only a few optimal postures to achieve a specific objective. The problem with such models is that they are incapable of rapidly providing several optimal posture candidates according to various situations. In order to solve this problem, this paper presents a 3D memory-based posture planning (3D MBPP) model, which is a new digital human model that can analyze the feasible postures in 3D space for reaching tasks that have postural constraints and specific reaching space. The 3D MBPP model can be applied to the types of works that are done with constrained working postures and have specific reaching space. The examples of such works include driving an excavator, driving automobiles, painting buildings, working at an office, pitching/batting, and boxing. For these types of works, a limited amount of space is required to store all of the feasible postures, as the hand reaches boundary can be determined prior to perform the task. This prevents computation time from increasing exponentially, which has been one of the major drawbacks of memory-based posture planning model in 3D space. This paper validates the utility of 3D MBPP model using a practical example of analyzing baseball batting posture. In baseball, batters swing with both feet fixed to the ground. This motion is appropriate for use with the 3D MBPP model since the player must try to hit the ball when the ball is located inside the strike zone (a limited area) in a constrained posture. The results from the analysis showed that the stored and the optimal postures vary depending on the ball’s flying path, the hitting location, the batter’s body size, and the batting objective. These results can be used to establish the optimal postural strategies for achieving the batting objective and performing effective hitting. The 3D MBPP model can also be applied to various domains to determine the optimal postural strategies and improve worker comfort.

Keywords: baseball, memory-based, posture prediction, reaching area, 3D digital human models

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Authors: Yanhua Zhao, Chenli Rao, Dongdong Li, Chuanmin Tao

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The Chinese Centers for Disease Control and Prevention (CCDC) issued a new laboratory-based algorithm for HIV diagnosis on April 2016, which initially screens with a combination HIV-1/HIV-2 antigen/antibody fourth-generation immunoassay (IA) followed, when reactive, an HIV-1/HIV-2 undifferentiated antibody IA in duplicate. Reactive specimens with concordant results undergo supplemental tests with western blots, or HIV-1 nucleic acid tests (NATs) and non-reactive specimens with discordant results receive HIV-1 NATs or p24 antigen tests or 2-4 weeks follow-up tests. However, little data evaluating the application of the new algorithm have been reported to date. The study was to evaluate the performance of new laboratory-based HIV diagnostic algorithm in an inpatient population of Southwest China over the initial 6 months by compared with the old algorithm. Plasma specimens collected from inpatients from May 1, 2016, to October 31, 2016, are submitted to the laboratory for screening HIV infection performed by both the new HIV testing algorithm and the old version. The sensitivity and specificity of the algorithms and the difference of the categorized numbers of plasmas were calculated. Under the new algorithm for HIV diagnosis, 170 of the total 52 749 plasma specimens were confirmed as positively HIV-infected (0.32%). The sensitivity and specificity of the new algorithm were 100% (170/170) and 100% (52 579/52 579), respectively; while 167 HIV-1 positive specimens were identified by the old algorithm with sensitivity 98.24% (167/170) and 100% (52 579/52 579), respectively. Three acute HIV-1 infections (AHIs) and two early HIV-1 infections (EHIs) were identified by the new algorithm; the former was missed by old procedure. Compared with the old version, the new algorithm produced fewer WB-indeterminate results (2 vs. 16, p = 0.001), which led to fewer follow-up tests. Therefore, the new HIV testing algorithm is more sensitive for detecting acute HIV-1 infections with maintaining the ability to verify the established HIV-1 infections and can dramatically decrease the greater number of WB-indeterminate specimens.

Keywords: algorithm, diagnosis, HIV, laboratory

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Authors: David C. Ni

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In the previous efforts, we constructed N-Body Systems by an extended Blaschke product (EBP), which represents a non-temporal and nonlinear extension of Lorentz transformation. In this construction, we rely only on two parameters, nonlinear degree, and relative momentum to characterize the systems. We further explored root computation via iteration with an algorithm extended from Jenkins-Traub method. The solution sets demonstrate a form of σ+ i [-t, t], where σ and t are the real numbers, and the [-t, t] shows various canonical distributions. In this paper, we correlate the convergent sets in the original domain with solution sets, which demonstrating large-deviation distributions in the codomain. We proceed to compare our approach with the formula or principles, such as Donsker-Varadhan and Wentzell-Freidlin theories. The deterministic model based on this construction allows us to explore applications in the areas of finance and statistical mechanics.

Keywords: nonlinear Lorentz transformation, Blaschke equation, iteration solutions, root computation, large deviation distribution, deterministic model

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Authors: Benbya Hind, Belbaly Nassim

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Markets and communities are often cast as alternative forms of knowledge sharing, but an open question is how and why people dynamically transition between them. To study these transitions, we design a technology that allows geographically distributed participants to either buy knowledge (using virtual points) or request it for free. We use a data-driven, inductive approach, studying 550 members in over 5000 interactions, during nine months. Because the technology offered participants choices between market or community forms, we can document both individual and collective transitions that emerge as people cycle between these forms. Our inductive analysis revealed that uncertainties endemic to knowledge sharing were the impetus for these transitions. Communities evoke uncertainties about knowledge sharing’s costs and benefits, which markets resolve by quantifying explicit prices. However, if people manipulate markets, they create uncertainties about the validity of those prices, allowing communities to reemerge to establish certainty via identity-based validation.

Keywords: knowledge sharing, communities, information technology design, transitions, markets

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Authors: Hailyie Tekleselase

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Deep learning is increasingly used as a building block of security systems. However, neural networks are hard to interpret and typically solid to the practitioner. This paper presents a detail survey of computing methods in cyber security, and analyzes the prospects of enhancing the cyber security capabilities by suggests that of accelerating the intelligence of the security systems. There are many AI-based applications used in industrial scenarios such as Internet of Things (IoT), smart grids, and edge computing. Machine learning technologies require a training process which introduces the protection problems in the training data and algorithms. We present machine learning techniques currently applied to the detection of intrusion, malware, and spam. Our conclusions are based on an extensive review of the literature as well as on experiments performed on real enterprise systems and network traffic. We conclude that problems can be solved successfully only when methods of artificial intelligence are being used besides human experts or operators.

Keywords: artificial intelligence, machine learning, deep learning, cyber security, big data

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Authors: Arindam Pramanik, Parimal Karmakar

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We have explored the synergistic anti-cancer activity of copper ion and acetylacetone complex containing 1,3 diketone group (like curcumin) in metallorganic compound “Copper acetylacetonate” (CuAA). The cytotoxicity mechanism of CuAA complex was evaluated on various cancer cell lines in vitro. Among these, reactive oxygen species (ROS), glutathione level (GSH) in the cell was found to increase. Further mitochondrial membrane damage was observed. The fate of cell death was found to be induced by apoptosis. For application purpose, we have developed a novel biodegradable, non-toxic polymer-based nanoparticle which has hydrophobically modified core for loading of the CuAA. Folic acid is conjugated on the surface of the polymer (chitosan) nanoparticle for targeting to cancer cells for minimizing toxicity to normal cells in-vivo. Thus, this novel drug CuAA has an efficient anticancer activity which has been targeted specifically to cancer cells through polymer nanoparticle.

Keywords: anticancer, apoptosis, copper nanoparticle, targeted drug delivery

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Authors: Jalal Maqbool, Gyu Myoung Lee

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Using smart devices for context aware mobile learning is becoming increasingly popular. This has led to mobile learning technology becoming an indispensable part of today’s learning environment and platforms. However, some fundamental issues remain - namely, mobile learning still lacks the ability to truly understand human reaction and user behaviour. This is due to the fact that current mobile learning systems are passive and not aware of learners’ changing contextual situations. They rely on static information about mobile learners. In addition, current mobile learning platforms lack the capability to incorporate dynamic contextual situations into learners’ preferences. Thus, this thesis aims to address these issues highlighted by designing a context aware framework which is able to sense learner’s contextual situations, handle data dynamically, and which can use contextual information to suggest bespoke learning content according to a learner’s preferences. This is to be underpinned by a robust recommendation system, which has the capability to perform these functions, thus providing learners with a truly context-aware mobile learning experience, delivering learning contents using smart devices and adapting to learning preferences as and when it is required. In addition, part of designing an algorithm for the recommendation engine has to be based on learner and application needs, personal characteristics and circumstances, as well as being able to comprehend human cognitive processes which would enable the technology to interact effectively and deliver mobile learning content which is relevant, according to the learner’s contextual situations. The concept of this proposed project is to provide a new method of smart learning, based on a capable recommendation engine for providing an intuitive mobile learning model based on learner actions.

Keywords: aware, context, learning, mobile

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Authors: Keith T. S. Tung, Frederick K. Ho, Rosa S. Wong, Camilla K. M. Lo, Wilfred H. S. Wong, C. B. Chow, Patrick Ip

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Objectives: Underage drinking is an important public health problem both locally and globally. Conventional prevention/intervention relies on unidirectional knowledge transfer such as mail leaflets or health talks which showed mixed results in changing the target behaviour. Previously, we conducted a school internet-based intervention which was found to be effective in reducing alcohol use among adolescents, yet the underlying mechanisms have not been properly investigated. This study, therefore, examined the mechanisms that explain how the intervention produced a change in alcohol drinking behaviours among Chinese adolescent as observed in our previous clustered randomised controlled trial (RCT) study. Methods: This is a cluster randomised controlled trial with parallel group design. Participating schools were randomised to the Internet intervention or the conventional health education group (control) with a 1:1 allocation ratio. Secondary 1–3 students of the participating schools were enrolled in this study. The Internet intervention was a web-based quiz game competition, in which participating students would answer 1,000 alcohol-related multiple-choice quiz questions. Conventional health education group received a promotional package on equivalent alcohol-related knowledge. The participants’ alcohol-related attitude, knowledge, and perceived behavioural control were self-reported before the intervention (baseline) and one month and three months after the intervention. Results: Our RCT results showed that participants in the Internet group were less likely to drink (risk ratio [RR] 0.79, p < 0.01) as well as in lesser amount (β -0.06, p < 0.05) compared to those in the control group at both post-intervention follow-ups. Within the intervention group, regression analyses showed that high quiz scorer had greater improvement in alcohol-related knowledge (β 0.28, p < 0.01) and attitude (β -0.26, p < 0.01) at 1 month after intervention, which in turn increased their perceived behavioural control against alcohol use (β 0.10 and -0.26, both p < 0.01). Attitude, compared to knowledge, was found to be a stronger contributor to the intervention effect on perceived behavioural control. Conclusions: Our internet-based intervention has demonstrated effectiveness in reducing the risk of underage drinking when compared with conventional health education. Our study results further showed an attitude to be a more important factor than knowledge in changing health-related behaviour. This has an important implication for future prevention/intervention on an underage drinking problem.

Keywords: adolescents, internet-based intervention, randomized controlled trial, underage drinking

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Authors: Wesam Darawsheh

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Purpose: There is an absence of studies directed to evaluate the effectiveness of Community Based Rehabilitation (CBR) programs in Jordan. This research study is aimed at investigating the effectiveness of the services of CBR programmes in Jordan. Method: A questionnaire anonymized survey was carried out with forty-seven participants (stakeholders and volunteers) from four CBR centres in Jordan. It comprised eighteen questions that collected both qualitative and quantitative data with both closed- and open-ended questions. The survey assessed participants’ knowledge of CBR and perception of the effectiveness of services provided. The quantitative data were analyzed using SPSS Version 22.0 (2016, IBM Corporation New York). Qualitative data were analyzed through thematic content and analysis and open coding to identify emergent themes. Results: The ROC curve revealed that the AUC for questions of the survey to be (AUC=0.846) which indicated a good specificity and sensitivity of the questions of the survey. The MANOVA revealed insignificant results in the effect of the CBR site (p= 0.157), and the level of education of participants (p=0.549), on the perception of the effectiveness of CBR services. There were insignificant differences between the scores of PWDs and volunteers (p=0.781). 40.4% evaluated the effectiveness of CBR services to be low. This mainly stemmed out from the lack of efforts of the CBR programmes to raise the knowledge of the local community about CBR, disability and the role toward PWDs. Conclusions: A speculation for priorities of CBR programmes in Jordan was offered where efforts need to be directed at promoting livelihood and the empowerment components, in order to actualize the main three principles of CBR mainly by promoting multispectral collaboration as a way of operation.

Keywords: community based rehabilitation (CBR), people with disabilities (PWDS), CBR centres, rehabilitation services, Jordan, mixed-methods, evaluative study

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Authors: Kourosh Fatehi, Niloofar Hanafi

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One of the challenges in providing optimal prosthetic legs for lower limb amputees is to select the appropriate foot stiffness that suits their individual needs and preferences. Foot stiffness affects various aspects of walking, such as stability, comfort, and energy expenditure. However, the current prescription process is largely based on trial-and-error, manufacturer recommendations, or clinician judgment, which may not reflect the prosthesis user’s subjective experience or psychophysical sensitivity. Therefore, there is a need for more scientific and technological tools to measure and understand how prosthesis users perceive and prefer different foot stiffness levels, and how this preference relates to clinical outcomes. This review covers how to measure and design lower leg prostheses based on user preference and foot stiffness. It also explores how these factors affect walking outcomes and quality of life, and identifies the current challenges and gaps in this field from a mechanical engineering standpoint.

Keywords: perception, preference, prosthetics, stiffness

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Authors: Yao Wu

Abstract:

In the context of financial globalization, China has put forward the policy goal of high-quality development, and the digital economy, with its advantage of information resources, is driving China's export trade to achieve high-quality development. Due to the long-standing financing constraints of small and medium-sized export enterprises, how to expand the export scale of small and medium-sized enterprises has become a major threshold for the development of China's export trade. This paper firstly adopts the hierarchical analysis method to establish the evaluation system of high-quality development of China's export trade; secondly, the panel data of 30 provinces in China from 2011 to 2018 are selected for empirical analysis to establish the impact model of digital inclusive finance on the high-quality development of China's export trade; based on the analysis of heterogeneous enterprise trade model, a mediating effect model is established to verify the mediating role of credit constraint in the development of high-quality export trade in China. Based on the above analysis, this paper concludes that inclusive digital finance, with its unique digital and inclusive nature, alleviates the credit constraint problem among SMEs, enhances the binary marginal effect of SMEs' exports, optimizes their export scale and structure, and promotes the high-quality development of regional and even national export trade. Finally, based on the findings of this paper, we propose insights and suggestions for inclusive digital finance to promote the high-quality development of export trade.

Keywords: digital inclusive finance, high-quality development of export trade, fixed effects, binary marginal effects

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Authors: N. Damenia, E. Kharaishvili, N. Sagareishvili, M. Saghareishvili

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Women's Employment is one of the most important issues in the global economy. The article discusses the stated topic in Georgia, through historical content, Soviet experience, and modern perspectives. The paper discusses segmentation insa terms of employment and related problems. Based on statistical analysis, women's unemployment rate and its factors are analyzed. The level of employment of women in Transcaucasia (Georgia, Armenia, and Azerbaijan) is discussed and is compared with Baltic countries (Lithuania, Latvia, and Estonia). The study analyzes women’s level of development, according to the average age of marriage and migration level. The focus is on Georgia's Association Agreement with the EU in 2014, which includes economic, social, trade and political issues. One part of it is gender equality at workplaces. According to the research, the average monthly remuneration of women managers in the financial and insurance sector equaled to 1044.6 Georgian Lari, while in overall business sector average monthly remuneration equaled to 961.1 GEL. Average salaries are increasing; however, the employment rate remains problematic. For example, in 2017, 74.6% of men and 50.8% of women were employed from a total workforce. It is also interesting that the proportion of men and women at managerial positions is 29% (women) to 71% (men). Based on the results, the main recommendation for government and civil society is to consider women as a part of the country’s economic development. In this aspect, the experience of developed countries should be considered. It is important to create additional jobs in urban or rural areas and help migrant women return and use their working resources properly.

Keywords: employment of women, segregation in terms of employment, women's employment level in Transcaucasia, migration level

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Authors: M. Fakharian, M. I. Khodakarami

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In this paper, a new trend for improvement in semi-analytical method based on scale boundaries in order to solve the 2D elastodynamic problems is provided. In this regard, only the boundaries of the problem domain discretization are by specific sub-parametric elements. Mapping functions are uses as a class of higher-order Lagrange polynomials, special shape functions, Gauss-Lobatto -Legendre numerical integration, and the integral form of the weighted residual method, the matrix is diagonal coefficients in the equations of elastodynamic issues. Differences between study conducted and prior research in this paper is in geometry production procedure of the interpolation function and integration of the different is selected. Validity and accuracy of the present method are fully demonstrated through two benchmark problems which are successfully modeled using a few numbers of DOFs. The numerical results agree very well with the analytical solutions and the results from other numerical methods.

Keywords: 2D elastodynamic problems, lagrange polynomials, G-L-Lquadrature, decoupled SBFEM

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Authors: Yousef Rostami Gharainy

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This paper presents resource consumption accounting as an imaginative way to deal with management accounting which concentrates on administrators as the essential clients of the data and gives the best information of conventional management accounting. This system underscores that association's asset reasons costs, accordingly in costing frameworks the emphasis ought to be on assets and utilization of them. Resource consumption accounting consolidates two costing methodologies, action based and German cost accounting method known as GPK. This methodology notwithstanding giving a chance to managers to decide, makes task management accounting as operational. The reason for this article is to clarify the idea of resource consumption accounting, its parts and highlights and use of this strategy in associations. In the first place we deliver to presentation of resource consumption accounting, foundation, reasons for its development and the issues that past costing frameworks confronted it. At that point we give standards and presumptions of this technique; at last we depict the execution of this strategy in associations and its preferences over other costing strategies.

Keywords: resource consumption accounting, management accounting, action based method, German cost accounting method

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Authors: Azhar Ulhaq, Zubair Yameen, Almas Anjum

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Frequency behaviour of self-excited induction generator (SEIG) wind turbines during control mode transition from grid connected to islanded mode is studied in detail. A robust control scheme for frequency regulation based on combined action of STATCOM, energy storage system (ESS) and pitch angle control for wind powered microgrid (MG) is proposed. Suggested STATCOM controller comprises a 3-phase voltage source converter (VSC) that contains insulated gate bipolar transistors (IGBTs) based pulse width modulation (PWM) inverters along with a capacitor bank. Energy storage system control consists of current controlled voltage source converter and battery bank. Both of them acting simultaneously after detection of island compensates for reactive and active power demands, thus regulating frequency at point of common coupling (PCC) and also improves load stability. STATCOM integrates at point of common coupling and ESS is connected to microgrids main bus. Results reveal that proposed control not only stabilizes frequency during transition duration but also minimizes sudden frequency imbalance caused by load variation or wind intermittencies in islanded operation. System is investigated with and without suggested control scheme. The efficacy of proposed strategy has been verified by simulation in MATLAB/Simulink.

Keywords: energy storage system, island, wind, STATCOM, self-excited induction generator, SEIG, transient

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Authors: Mojtaba Saeedinezhad, Sarah Yousefi

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In this paper, we present a hybrid subspace approach for Time Delay Estimation (TDE) in multivariable systems. While several methods have been proposed for time delay estimation in SISO systems, delay estimation in MIMO systems were always a big challenge. In these systems the existing TDE methods have significant limitations because most of procedures are just based on system response estimation or correlation analysis. We introduce a new hybrid method for TDE in MIMO systems based on subspace identification and explicit output error method; and compare its performance with previously introduced procedures in presence of different noise levels and in a statistical manner. Then the best method is selected with multi objective decision making technique. It is shown that the performance of new approach is much better than the existing methods, even in low signal-to-noise conditions.

Keywords: system identification, time delay estimation, ARX, OE, merit ratio, multi variable decision making

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Authors: M. Taheri Tehrani, H. Ajorloo

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In this paper, an intelligent multi-agent framework is developed for each router in which agents have two vital functionalities, traffic shaping and buffer allocation and are positioned in the ports of the routers. With traffic shaping functionality agents shape the traffic forward by dynamic and real time allocation of the rate of generation of tokens in a Token Bucket algorithm and with buffer allocation functionality agents share their buffer capacity between each other based on their need and the conditions of the network. This dynamic and intelligent framework gives this opportunity to some ports to work better under burst and more busy conditions. These agents work intelligently based on Reinforcement Learning (RL) algorithm and will consider effective parameters in their decision process. As RL have limitation considering much parameter in its decision process due to the volume of calculations, we utilize our novel method which invokes Principle Component Analysis (PCA) on the RL and gives a high dimensional ability to this algorithm to consider as much as needed parameters in its decision process. This implementation when is compared to our previous work where traffic shaping was done without any sharing and dynamic allocation of buffer size for each port, the lower packet drop in the whole network specifically in the source routers can be seen. These methods are implemented in our previous proposed intelligent simulation environment to be able to compare better the performance metrics. The results obtained from this simulation environment show an efficient and dynamic utilization of resources in terms of bandwidth and buffer capacities pre allocated to each port.

Keywords: principal component analysis, reinforcement learning, buffer allocation, multi- agent systems

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Authors: Adnan Baig, Ishteeaq Naeem, Saad Mansoor

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The Internet of Things (IoT) gadgets have advanced quickly in recent years, and their use is steadily rising daily. However, cyber-attackers can target these gadgets due to their distributed nature. Additionally, many IoT devices have significant security flaws in their implementation and design, making them vulnerable to security threats. Hence, these threats can cause important data security and privacy loss from a single attack on network devices or systems. Botnets are a significant security risk that can harm the IoT network; hence, sophisticated techniques are required to mitigate the risk. This work uses a machine learning-based method to identify IoT orchestrated by botnets. The proposed technique identifies the net attack by distinguishing between legitimate and malicious traffic. This article proposes a hyperparameter tuning model to improvise the method to improve the accuracy of existing processes. The results demonstrated an improved and more accurate indication of botnet-based cyber-attacks.

Keywords: Internet of Things, Botnet, BoT-IoT dataset, ML techniques

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Authors: Jixiang Lei, Alexander Fuchs, Franz Pernkopf, Katrin Ellermann

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Within the Space@Sea project, funded by the Horizon 2020 program, an island consisting of multiple platforms was designed. The platforms are connected by ropes and fenders. The connection is critical with respect to the safety of the whole system. Therefore, fault detection systems are investigated, which could detect early warning signs for a possible failure in the connection elements. Previously, a model-based method called Extended Kalman Filter was developed to detect the reduction of rope stiffness. This method detected several types of faults reliably, but some types of faults were much more difficult to detect. Furthermore, the model-based method is sensitive to environmental noise. When the wave height is low, a long time is needed to detect a fault and the accuracy is not always satisfactory. In this sense, it is necessary to develop a more accurate and robust technique that can detect all rope faults under a wide range of operational conditions. Inspired by this work on the Space at Sea design, we introduce a fault diagnosis method based on deep neural networks. Our method cannot only detect rope degradation by using the acceleration data from each platform but also estimate the contributions of the specific acceleration sensors using methods from explainable AI. In order to adapt to different operational conditions, the domain adaptation technique DANN is applied. The proposed model can accurately estimate rope degradation under a wide range of environmental conditions and help users understand the relationship between the output and the contributions of each acceleration sensor.

Keywords: fault diagnosis, deep learning, domain adaptation, explainable AI

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Authors: Annabelle Onyefulu-Kingston

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One of the major purposes of AI today is to evaluate and analyze millions of micro and macro data in order to determine what is relevant in a particular case and proffer it in an adequate manner. Microdata, as far as it relates to AI in international arbitration, is the millions of key issues specifically mentioned by either one or both parties or by their counsels, arbitrators, or arbitral tribunals in arbitral proceedings. This can be qualifications of expert witness and admissibility of evidence, amongst others. Macro data, on the other hand, refers to data derived from the resolution of the dispute and, consequently, the final and binding award. A notable example of this includes the rationale of the award and specific and general damages awarded, amongst others. This paper aims to critically evaluate and analyze the possibility of technological inclusion in international arbitration. This research will be imploring the qualitative method by evaluating existing literature on the consequence of applying AI to both micro and macro data in international arbitration, and how this can be of assistance to parties, counsels, and arbitrators.

Keywords: AI-based technologies, algorithms, arbitrators, international arbitration

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Authors: Qiu Chen, Koji Kotani, Feifei Lee, Tadahiro Ohmi

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In this paper, we propose an improved face recognition algorithm using histogram-based features in spatial and frequency domains. For adding spatial information of the face to improve recognition performance, a region-division (RD) method is utilized. The facial area is firstly divided into several regions, then feature vectors of each facial part are generated by Binary Vector Quantization (BVQ) histogram using DCT coefficients in low frequency domains, as well as Local Binary Pattern (LBP) histogram in spatial domain. Recognition results with different regions are first obtained separately and then fused by weighted averaging. Publicly available ORL database is used for the evaluation of our proposed algorithm, which is consisted of 40 subjects with 10 images per subject containing variations in lighting, posing, and expressions. It is demonstrated that face recognition using RD method can achieve much higher recognition rate.

Keywords: binary vector quantization (BVQ), DCT coefficients, face recognition, local binary patterns (LBP)

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Authors: Y. Laib Dit Leksir, S. Bouhouche

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Analysis and processing of data bases resulting from infrared thermal measurements made on the electrical installation requires the development of new tools in order to obtain correct and additional information to the visual inspections. Consequently, the methods based on the capture of infrared digital images show a great potential and are employed increasingly in various fields. Although, there is an enormous need for the development of effective techniques to analyse these data base in order to extract relevant information relating to the state of the equipments. Our goal consists in introducing recent techniques of modeling based on new methods, image and signal processing to develop mathematical models in this field. The aim of this work is to capture the anomalies existing in electrical equipments during an inspection of some machines using A40 Flir camera. After, we use binarisation techniques in order to select the region of interest and we make comparison between these methods of thermal images obtained to choose the best one.

Keywords: infrared thermography, defect detection, troubleshooting, electrical equipment

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Authors: Byeong-Sam Kim, Kyeongwoo Park

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In this study, induced structural optimization is performed to compare the trade-off between wing weight and induced drag for wing panel extensions, construction of wing panel and winglets. The aerostructural optimization problem consists of parameters with strength condition, and two maneuver conditions using residual stresses in panel production. The results of kinematic motion analysis presented a homogenization based theory for 3D beams and 3D shells for wing panel. This theory uses a kinematic description of the beam based on normalized displacement moments. The displacement of the wing is a significant design consideration as large deflections lead to large stresses and increased fatigue of components cause residual stresses. The stresses in the wing panel are small compared to the yield stress of aluminum alloy. This study describes the implementation of a large wing panel, aerostructural analysis and structural parameters optimization framework that couples a three-dimensional panel method.

Keywords: wing panel, aerostructural optimization, FEM, structural analysis

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Authors: Catalin Croitoru, Ionut Claudiu Roata

Abstract:

Employing concentrated solar energy (CSE) for sintering metallic parts offers distinct advantages, notably in the rapid thermal cycling that significantly influences their microstructure and phase transitions. This study uses the thermal control that CSE affords, enhancing the mechanical properties and tailoring the functionality of nickel-based alloys. We synthesized bulk alloys by sintering Ni-Cr-Al-Y powders in varied ratios using a vertical solar furnace at PROMES-CNRS, Font-Romeu Odeillo, France. The process achieved optimal fusion at 800°C for 10 minutes, resulting in materials with a notable hydrophilic surface due to oxide formation. The alloys’ performance was evaluated through corrosion resistance tests in a 3.5% wt. NaCl solution, utilizing potentiodynamic scanning and electrochemical impedance spectroscopy. Our findings demonstrate the potential of CSE in advancing the material properties of nickel-based alloys for diverse applications.

Keywords: concentrated solar energy, sintering, corrosion resistance, surface properties

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Authors: P. Comendador, I. Garcia, S. Orozco, L. Santamaria, M. Amutio, G. Lopez, M. Olazar

Abstract:

In situ CO₂ capture in steam reforming processes has been studied in the last years as an alternative for increasing H₂ yields and H₂ purity in the product stream. For capturing the CO₂ at the reforming conditions, CaO-based sorbents are usually employed due to their properties at high temperature, low cost and high availability. However, the challenge is to develop high-capacity (gCO₂/gsorbent) materials that retain their capacity over cycles of operation. Besides, since the objective is to capture the CO₂ generated in situ, another key aspect is the sorption dynamics, which means that, in order to efficiently use the sorbent, it has to capture the CO₂ at a rate equal to or higher than the generation rate. In this work, different CaO-based materials have been prepared to aim at meeting these criteria. First, and by using the wet mixing method, different inert materials (Mg, Ce and Al) were combined with CaO. Second, and with the inert material selected (Mg), the effect of its concentration in the final material was studied. Transversally, the calcination temperature was also evaluated. It was determined that the wet mixing method is a simple procedure suitable for the preparation of CaO sorbents mixed with inert materials. The materials prepared by mixing the CaO with Mg have shown satisfactory anti-sintering properties and adequate sorption kinetics for their application in steam reforming processes. Regarding the concentration of Mg in the solid, it was concluded that high values contribute to the stability but at the expense of losing sorption capacity. Finally, it was observed that high calcination temperatures negatively affected the sorption properties of the final materials due to the decrease in the pore volume and the specific surface area.

Keywords: calcination temperature effect, CO₂ capture, Mg-Ce-Al stabilizers, Mg varying concentration effect, Sorbent stabilization

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Authors: Pavel Chmelar, Martin Dobrovolny

Abstract:

Laser projection or laser footprint detection is today widely used in many fields of robotics, measurement, or electronics. The system accuracy strictly depends on precise laser footprint detection on target objects. This article deals with the laser line detection based on the RGB segmentation and the component labeling. As a measurement device was used the developed optical rangefinder. The optical rangefinder is equipped with vertical sweeping of the laser beam and high quality camera. This system was developed mainly for automatic exploration and mapping of unknown spaces. In the first section is presented a new detection algorithm. In the second section are presented measurements results. The measurements were performed in variable light conditions in interiors. The last part of the article present achieved results and their differences between day and night measurements.

Keywords: color segmentation, component labelling, laser line detection, automatic mapping, distance measurement, vector map

Procedia PDF Downloads 432