Search results for: multi track diplomacy

Authors: Tayyab Ahmad, Gerard Healey

Abstract:

Sustainability in built environment sector is subject to many development constraints. Building projects are developed under different requirements of deliverables which makes each project unique. For an owner organization, i.e., a higher-education institution, involved in a significant building stock, it is important to prioritize some of the sustainability initiatives over the others in order to align the sustainable building development with organizational goals. The point-based green building rating tools i.e. Green Star, LEED, BREEAM are becoming increasingly popular and are well-acknowledged worldwide for verifying a sustainable development. It is imperative to synthesize a multi-criteria decision-making tool that can capitalize on the point-based methodology of rating systems while customizing the sustainable development of building projects according to the individual requirements and constraints of the client organization. A multi-criteria decision-making tool for the University of Melbourne is developed that builds on the action-learning and experience of implementing Green Buildings at the University of Melbourne. The tool evaluates the different sustainable building initiatives based on the framework of Green Star rating tool of Green Building Council of Australia. For each different sustainability initiative the decision-making tool makes an assessment based on at least five performance criteria including the ease with which a sustainability initiative can be achieved and the potential of a sustainability initiative to enhance project objectives, reduce life-cycle costs, enhance University’s reputation, and increase the confidence in quality construction. The use of a weighted aggregation mathematical model in the proposed tool can have a considerable role in the decision-making process of a Green Building project by indexing the Green Building initiatives in terms of organizational priorities. The index value of each initiative will be based on its alignment with some of the key performance criteria. The usefulness of the decision-making tool is validated by conducting structured interviews with some of the key stakeholders involved in the development of sustainable building projects at the University of Melbourne. The proposed tool is realized to help a client organization in deciding that within limited resources which sustainability initiatives and practices are more important to be pursued than others.

Keywords: higher education institution, multi-criteria decision-making tool, organizational values, prioritizing sustainability initiatives, weighted aggregation model

Procedia PDF Downloads 234

Authors: Matej Komanec, Jan Bohata, Stanislav Zvanovec, Tomas Nemecek, Jan Broucek, Josef Beran

Abstract:

With the exponential growth of social networks, video streaming and increasing demands on data rates, the number of newly built data centers rises proportionately. The data centers, however, have to adjust to the rapidly increased amount of data that has to be processed. For this purpose, multi-mode (MM) fiber based infrastructures are often employed. It stems from the fact, the connections in data centers are typically realized within a short distance, and the application of MM fibers and components considerably reduces costs. On the other hand, the usage of MM components brings specific requirements for installation service conditions. Moreover, it has to be taken into account that MM fiber components have a higher production tolerance for parameters like core and cladding diameters, eccentricity, etc. Due to the high demands for the reliability of data center components, the determination of properly excited optical field inside the MM fiber core belongs to the key parameters while designing such an MM optical system architecture. Appropriately excited mode field of the MM fiber provides optimal power budget in connections, leads to the decrease of insertion losses (IL) and achieves effective modal bandwidth (EMB). The main parameter, in this case, is the encircled flux (EF), which should be properly defined for variable optical sources and consequent different mode-field distribution. In this paper, we present detailed investigation and measurements of the mode field distribution for short MM links purposed in particular for data centers with the emphasis on reliability and safety. These measurements are essential for large MM network design. The various scenarios, containing different fibers and connectors, were tested in terms of IL and mode-field distribution to reveal potential challenges. Furthermore, we focused on estimation of particular defects and errors, which can realistically occur like eccentricity, connector shifting or dust, were simulated and measured, and their dependence to EF statistics and functionality of data center infrastructure was evaluated. The experimental tests were performed at two wavelengths, commonly used in MM networks, of 850 nm and 1310 nm to verify EF statistics. Finally, we provide recommendations for data center systems and networks, using OM3 and OM4 MM fiber connections.

Keywords: optical fiber, multi-mode, data centers, encircled flux

Procedia PDF Downloads 375

Authors: Yoke-Mui Lim, Yahaya Ahmad

Abstract:

Conservation works in Malaysia that is procured by public organisation usually follow the traditional approach where the works are tendered based on Bills of Quantities (BQ). One of the purposes of tendering is to enable the selection of a competent contractor that offers a competitive price. While competency of the contractors are assessed by their technical knowledge, experience and track records, the assessment of pricing will be dependent on the tender amount. However, the issue currently faced by the conservation works sector is the difficulty in assessing the competitiveness and reasonableness of the tender amount due to the high variance between the tenders amount. Thus, this paper discusses the factors that cause difficulty to the tenderers in pricing competitively in a bidding exercise for conservation tenders. Data on tendering is collected from interviews with conservation works contractors to gain in-depth understanding of the barriers faced in pricing tenders of conservation works. Findings from the study lent support to the contention that the variance of tender amount is very high amongst tenderers. The factors identified in the survey are the format of BQ, hidden works, experience and labour and material costs.

Keywords: building conservation, Malaysia, bill of quantities, tender

Procedia PDF Downloads 386

Authors: Bheki R. Mngomezulu

Abstract:

The present paper cogently and systematically traces the history of Umkhonto Wesizwe (MK) and identifies its important role in shaping South Africa’s post-apartheid foreign policy and international relations under black leadership. It provides the political and historical contexts within which we can interpret and better understand South Africa’s controversial ‘Quiet Diplomacy’ approach to Zimbabwe’s endemic political and economic crises, which have dragged for too long. On 16 December 1961, the African National Congress (ANC) officially launched the MK as its military wing. The main aim was to train liberation fighters outside South Africa who would return into the country to topple the apartheid regime. Subsequently, the ANC established links with various countries across Africa and the globe in order to solicit arms, financial resources and military training for its recruits into the MK. Drawing from archival research and empirical data obtained through oral interviews that were conducted with some of the former MK cadres, this paper demonstrates how the ANC forged relations with a number of countries that were like-minded in order to ensure that its dream of removing the apartheid government became a reality. The findings reveal that South Africa’s foreign policy posture and international relations after the demise of apartheid in 1994 built on these relations. As such, even former and current socialist countries that were frowned upon by the Western world became post-apartheid South Africa’s international partners. These include countries such as Cuba and China, among others. Even countries that were not recognized by the Western world as independent states received good reception in post-apartheid South Africa’s foreign policy agenda. One of these countries is Palestine. Within Africa, countries with questionable human rights records such as Nigeria and Zimbabwe were accommodated in South Africa’s foreign policy agenda after 1994. Drawing from this history, the paper concludes that it would be difficult to fully understand and appreciate South Africa’s foreign policy direction and international relations after 1994 without bringing the history and the politics of the MK into the equation. Therefore, the paper proposes that the utilitarian role of history should never be undermined in the analysis of a country’s foreign policy direction and international relations. Umkhonto Wesizwe and South Africa are used as examples to demonstrate how such a link could be drawn through archival and empirical evidence.

Keywords: African National Congress, apartheid, foreign policy, international relations

Procedia PDF Downloads 185

Authors: Aravind G., Arshinder Kaur, Pushpavanam S.

Abstract:

There is a strong emphasis on shifting to electric vehicles (EVs) throughout the globe for reducing the impact on global warming following the Paris climate accord. Lithium-ion batteries (LIBs) are predominantly used in EVs, and these can be a significant threat to the environment if not disposed of safely. Lithium is also a valuable resource not widely available. There are several research groups working on developing an efficient recycling process for LIBs. Two routes - pyrometallurgical and hydrometallurgical processes have been proposed for recycling LIBs. In this paper, we focus on life cycle assessment (LCA) as a tool to quantify the environmental impact of these recycling processes. We have defined the boundary of the LCA to include only the recycling phase of the end-of-life (EoL) of the battery life cycle. The analysis is done assuming ideal conditions for the hydrometallurgical and a combined hydrometallurgical and pyrometallurgical process in the inventory analysis. CML-IA method is used for quantifying the impact assessment across eleven indicators. Our results show that cathode, anode, and foil contribute significantly to the impact. The environmental impacts of both hydrometallurgical and combined recycling processes are similar across all the indicators. Further, the results of LCA are used in developing a multi-objective optimization model for the design of lithium-ion battery recycling network. Greenhouse gas emissions and cost are the two parameters minimized for the optimization study.

Keywords: life cycle assessment, lithium-ion battery recycling, multi-objective optimization, network design, reverse supply chain

Procedia PDF Downloads 157

Authors: Bidzina Matsaberidze, Anna Sikharulidze, Gia Sirbiladze, Bezhan Ghvaberidze

Abstract:

In the modern world emergency management decision support systems are actively used by state organizations, which are interested in extreme and abnormal processes and provide optimal and safe management of supply needed for the civil and military facilities in geographical areas, affected by disasters, earthquakes, fires and other accidents, weapons of mass destruction, terrorist attacks, etc. Obviously, these kinds of extreme events cause significant losses and damages to the infrastructure. In such cases, usage of intelligent support technologies is very important for quick and optimal location-transportation of emergency service in order to avoid new losses caused by these events. Timely servicing from emergency service centers to the affected disaster regions (response phase) is a key task of the emergency management system. Scientific research of this field takes the important place in decision-making problems. Our goal was to create an expert knowledge-based intelligent support system, which will serve as an assistant tool to provide optimal solutions for the above-mentioned problem. The inputs to the mathematical model of the system are objective data, as well as expert evaluations. The outputs of the system are solutions for Fuzzy Multi-Objective Emergency Location-Transportation Problem (FMOELTP) for disasters’ regions. The development and testing of the Intelligent Support System were done on the example of an experimental disaster region (for some geographical zone of Georgia) which was generated using a simulation modeling. Four objectives are considered in our model. The first objective is to minimize an expectation of total transportation duration of needed products. The second objective is to minimize the total selection unreliability index of opened humanitarian aid distribution centers (HADCs). The third objective minimizes the number of agents needed to operate the opened HADCs. The fourth objective minimizes the non-covered demand for all demand points. Possibility chance constraints and objective constraints were constructed based on objective-subjective data. The FMOELTP was constructed in a static and fuzzy environment since the decisions to be made are taken immediately after the disaster (during few hours) with the information available at that moment. It is assumed that the requests for products are estimated by homeland security organizations, or their experts, based upon their experience and their evaluation of the disaster’s seriousness. Estimated transportation times are considered to take into account routing access difficulty of the region and the infrastructure conditions. We propose an epsilon-constraint method for finding the exact solutions for the problem. It is proved that this approach generates the exact Pareto front of the multi-objective location-transportation problem addressed. Sometimes for large dimensions of the problem, the exact method requires long computing times. Thus, we propose an approximate method that imposes a number of stopping criteria on the exact method. For large dimensions of the FMOELTP the Estimation of Distribution Algorithm’s (EDA) approach is developed.

Keywords: epsilon-constraint method, estimation of distribution algorithm, fuzzy multi-objective combinatorial programming problem, fuzzy multi-objective emergency location/transportation problem

Procedia PDF Downloads 321

Authors: Anshuman Srivastava, Shiv Singh, Sheelendra Pratap Singh

Abstract:

A simple, sensitive and effective gas chromatography tandem mass spectrometry (GC-MS/MS) method was developed for simultaneous analysis of multi pesticide residues (organophosphate, organochlorines, synthetic pyrethroids and herbicides) in food commodities using phenolic resin based activated carbon fibers (ACFs) as reversed-dispersive solid phase extraction (r-DSPE) sorbent in modified QuEChERS (Quick Easy Cheap Effective Rugged Safe) method. The acetonitrile-based QuEChERS technique was used for the extraction of the analytes from food matrices followed by sample cleanup with ACFs instead of traditionally used primary secondary amine (PSA). Different physico-chemical characterization techniques such as Fourier transform infrared spectroscopy, scanning electron microscopy, X-ray diffraction and Brunauer-Emmet-Teller surface area analysis were employed to investigate the engineering and structural properties of ACFs. The recovery of pesticides and herbicides was tested at concentration levels of 0.02 and 0.2 mg/kg in different commodities such as cauliflower, cucumber, banana, apple, wheat and black gram. The recoveries of all twenty-six pesticides and herbicides were found in acceptable limit (70-120%) according to SANCO guideline with relative standard deviation value < 15%. The limit of detection and limit of quantification of the method was in the range of 0.38-3.69 ng/mL and 1.26 -12.19 ng/mL, respectively. In traditional QuEChERS method, PSA used as r-DSPE sorbent plays a vital role in sample clean-up process and demonstrates good recoveries for multiclass pesticides. This study reports that ACFs are better in terms of removal of co-extractives in comparison of PSA without compromising the recoveries of multi pesticides from food matrices. Further, ACF replaces the need of charcoal in addition to the PSA from traditional QuEChERS method which is used to remove pigments. The developed method will be cost effective because the ACFs are significantly cheaper than the PSA. So the proposed modified QuEChERS method is more robust, effective and has better sample cleanup efficiency for multiclass multi pesticide residues analysis in different food matrices such as vegetables, grains and fruits.

Keywords: QuEChERS, activated carbon fibers, primary secondary amine, pesticides, sample preparation, carbon nanomaterials

Procedia PDF Downloads 271

Authors: Kenneth Fon Mbah, Arash Habibi Lashkari, Ali A. Ghorbani

Abstract:

Phishing e-mails are a security issue that not only annoys online users, but has also resulted in significant financial losses for businesses. Phishing advertisements and pornographic e-mails are difficult to detect as attackers have been becoming increasingly intelligent and professional. Attackers track users and adjust their attacks based on users’ attractions and hot topics that can be extracted from community news and journals. This research focuses on deceptive Phishing attacks and their variants such as attacks through advertisements and pornographic e-mails. We propose a framework called Phishing Alerting System (PHAS) to accurately classify e-mails as Phishing, advertisements or as pornographic. PHAS has the ability to detect and alert users for all types of deceptive e-mails to help users in decision making. A well-known email dataset has been used for these experiments and based on previously extracted features, 93.11% detection accuracy is obtainable by using J48 and KNN machine learning techniques. Our proposed framework achieved approximately the same accuracy as the benchmark while using this dataset.

Keywords: phishing e-mail, phishing detection, anti phishing, alarm system, machine learning

Procedia PDF Downloads 340

Authors: Bashar Mahmoud, Lee Mortimer, Michael Fairweather

Abstract:

New methods have recently been introduced to improve the thermal property values of molten nitrate salts (a binary mixture of NaNO3:KNO3in 60:40 wt. %), by doping them with minute concentration of nanoparticles in the range of 0.5 to 1.5 wt. % to form the so-called: Nano-heat-transfer-fluid, apt for thermal energy transfer and storage applications. The present study aims to assess the stability of these nanofluids using the advanced computational modelling technique, Lagrangian particle tracking. A multi-phase solid-liquid model is used, where the motion of embedded nanoparticles in the suspended fluid is treated by an Euler-Lagrange hybrid scheme with fixed time stepping. This technique enables measurements of various multi-scale forces whose characteristic (length and timescales) are quite different. Two systems are considered, both consisting of 50 nm Al2O3 ceramic nanoparticles suspended in fluids of different density ratios. This includes both water (5 to 95 °C) and molten nitrate salt (220 to 500 °C) at various volume fractions ranging between 1% to 5%. Dynamic properties of both phases are coupled to the ambient temperature of the fluid suspension. The three-dimensional computational region consists of a 1μm cube and particles are homogeneously distributed across the domain. Periodic boundary conditions are enforced. The particle equations of motion are integrated using the fourth order Runge-Kutta algorithm with a very small time-step, Δts, set at 10-11 s. The implemented technique demonstrates the key dynamics of aggregated nanoparticles and this involves: Brownian motion, soft-sphere particle-particle collisions, and Derjaguin, Landau, Vervey, and Overbeek (DLVO) forces. These mechanisms are responsible for the predictive model of aggregation of nano-suspensions. An energy transport-based method of predicting the thermal conductivity of the nanofluids is also used to determine thermal properties of the suspension. The simulation results confirms the effectiveness of the technique. The values are in excellent agreement with the theoretical and experimental data obtained from similar studies. The predictions indicates the role of Brownian motion and DLVO force (represented by both the repulsive electric double layer and an attractive Van der Waals) and its influence in the level of nanoparticles agglomeration. As to the nano-aggregates formed that was found to play a key role in governing the thermal behavior of nanofluids at various particle concentration. The presentation will include a quantitative assessment of these forces and mechanisms, which would lead to conclusions about nanofluids, heat transfer performance and thermal characteristics and its potential application in solar thermal energy plants.

Keywords: thermal energy storage, molten salt, nano-fluids, multi-scale computational modelling

Procedia PDF Downloads 191

Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

Abstract:

In multi-echelon supply chain networks, optimal supplier selection significantly depends on the accuracy of suppliers’ performance prediction. Different methods of multi criteria decision making such as ANN, GA, Fuzzy, AHP, etc have been previously used to predict the supplier performance but the “black-box” characteristic of these methods is yet a major concern to be resolved. Therefore, the primary objective in this paper is to implement an artificial intelligence-based gene expression programming (GEP) model to compare the prediction accuracy with that of ANN. A full factorial design with %95 confidence interval is initially applied to determine the appropriate set of criteria for supplier performance evaluation. A test-train approach is then utilized for the ANN and GEP exclusively. The training results are used to find the optimal network architecture and the testing data will determine the prediction accuracy of each method based on measures of root mean square error (RMSE) and correlation coefficient (R2). The results of a case study conducted in Supplying Automotive Parts Co. (SAPCO) with more than 100 local and foreign supply chain members revealed that, in comparison with ANN, gene expression programming has a significant preference in predicting supplier performance by referring to the respective RMSE and R-squared values. Moreover, using GEP, a mathematical function was also derived to solve the issue of ANN black-box structure in modeling the performance prediction.

Keywords: Supplier Performance Prediction, ANN, GEP, Automotive, SAPCO

Procedia PDF Downloads 419

Authors: Pradeep Singh, Shrish Verma

Abstract:

Software fault prediction models are created by using the source code, processed metrics from the same or previous version of code and related fault data. Some company do not store and keep track of all artifacts which are required for software fault prediction. To construct fault prediction model for such company, the training data from the other projects can be one potential solution. The earlier we predict the fault the less cost it requires to correct. The training data consists of metrics data and related fault data at function/module level. This paper investigates fault predictions at early stage using the cross-project data focusing on the design metrics. In this study, empirical analysis is carried out to validate design metrics for cross project fault prediction. The machine learning techniques used for evaluation is Naïve Bayes. The design phase metrics of other projects can be used as initial guideline for the projects where no previous fault data is available. We analyze seven data sets from NASA Metrics Data Program which offer design as well as code metrics. Overall, the results of cross project is comparable to the within company data learning.

Keywords: software metrics, fault prediction, cross project, within project.

Procedia PDF Downloads 344

Authors: Yi Ming Zhang, Zhan Xi Wang, Hang Chen, Gang Wang

Abstract:

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

Keywords: robot polishing, force feedback, impedance control, adaptive control

Procedia PDF Downloads 199

Authors: Orhan Kurtuluş, Cüneyt Yavuz

Abstract:

The end of the line controls of the finished products in the automotive industry is important. The control that has been conducted with the manual methods for the sliding doors tracks is not sufficient and faulty products cannot be identified. As a result, the customer has the faulty products. In the scope of this study, the design criteria of the PLC integrated modular end of line control unit has been examined, designed and manufactured to make the control of the 10 different track profile to 2 different vehicles with an objective to minimize the salvage costs by obtaining more sensitive, certain and accurate measurement results. In the study that started with literature and patent review, the design inputs have been specified, the technical concept has been developed, computer supported mechanic design, control system and automation design, design review and design improvement have been made. Laser analog sensors at high sensitivity, probes and modular blocks have been used in the unit. The measurement has been conducted in the system and it is observed that measurement results are more sensitive than the previous methods.

Keywords: control unit design, end of line, modular design, sliding door system

Procedia PDF Downloads 445

Authors: K. S. Hemant Yadav, H. G. Shivakumar

Abstract:

The present study investigation was to prepare and evaluate the mucoadhesive multi-particulate system for nasal drug delivery of anti-histaminic drug. Ebastine was chosen as the model drug. Drug loaded nanoparticles of Ebastine were prepared by ionic gelation method using chitosan as polymer using the drug-polymer weight ratios 1:1, 1:2, 1:3. Sodium tripolyphosphate (STPP) was used as the cross-linking agent in the range of 0.5 and 0.7% w/v. FTIR and DSC studies indicated that no chemical interaction occurred between the drug and polymers. Particle size ranged from 169 to 500 nm. The drug loading and entrapment efficiency was found to increase with increase in chitosan concentration and decreased with increase in poloxamer 407 concentration. The results of in vitro mucoadhesion carried out showed that all the prepared formulation had good mucoadhesive property and mucoadhesion increases with increase in the concentration of chitosan. The in vitro release pattern of all the formulations was observed to be in a biphasic manner characterized by slight burst effect followed by a slow release. By the end of 8 hrs, formulation F6 showed a release of only 86.9% which explains its sustained behaviour. The ex-vivo permeation of the pure drug ebastine was rapid than the optimized formulation(F6) indicating the capability of the chitosan polymer to control drug permeation rate through the sheep nasal mucosa. The results indicated that the mucoadhesive nanoparticulate system can be used for the nasal delivery of antihistaminic drugs in an effective manner.

Keywords: nasal, nanoparticles, ebastine, anti-histaminic drug, mucoadhesive multi-particulate system

Procedia PDF Downloads 419

Authors: Mariam Shah

Abstract:

‘Honour’ crime has commonly been perceived in the UK as being a ‘domestic violence’ related issue due to incidents perceived to take place within a domestic context, and commonly by familial perpetrators. The lack of differentiation between domestic violence and ‘honour’ related incidents has several negative implications. Firstly, the prevalence and extent of ‘honour’ related crime within the UK cannot be accurately quantified due to ‘honour’ incidents being classed statistically as domestic violence incidents. Secondly, lack of differentiation means that the negative stereotypical attitudes ascribed to domestic violence which has resulted in lower criminal conviction rates that are also impacting the conviction of perpetrators of ‘honour’ crime. Thirdly, ‘honour’ related crime is innately distinct from domestic violence due to the perpetrator’s resolute intent of cleansing perceived ‘shame’ in any way possible, often with the involvement and collusion of multiple perpetrators from within the family and/or community. Domestic violence is typically restricted to the ‘home’, but ‘honour’ crime can operate between national and international boundaries. This paper critically examines the current academic literature and concludes that the few similarities between domestic violence and ‘honour’ related crime are not sufficient to warrant identical treatment under UK criminal law. ‘Honour’ related crime is a distinct and stand-alone offence which should be recognised as such. The appropriate identification and treatment of ‘honour’ crime are crucial, particularly in light of the UK’s first ‘white’ honour killing which saw a young English woman murdered after being deemed to have brought ‘shame’ on her ex-boyfriend’s family. This incident highlights the possibility of ‘honour’ crime extending beyond its perceived ‘ethnic minority’ roots and becoming more of a ‘mainstream’ issue for the multi-cultural and multi-racial UK.

Keywords: differentiation, domestic violence, honour crime, United Kingdom

Procedia PDF Downloads 235

Authors: Vaclav Musil, Robert Cep, Sarka Malotova, Jiri Hajnys, Frantisek Spalek

Abstract:

The new designs of satellite gears comprising a number of small gears pose high requirements on the precise production of small module gears. The objective of the experimental activity stated in this article was to compare the conventional rolling gear cutting technology with the modern wire electrical discharge machining (WEDM) technology for the production of small module gear m=0.6 mm (thickness of 2.5 mm and material 30CrMoV9). The WEDM technology lies in copying the profile of gearing from the rendered trajectory which is then transferred to the track of a wire electrode. During the experiment, we focused on the comparison of these production methods. Main measured parameters which significantly influence the lifetime and noise was chosen. The first parameter was to compare the precision of gearing profile in respect to the mathematic model. The second monitored parameter was the roughness and surface topology of the gear tooth side. The experiment demonstrated high accuracy of WEDM technology, but a low quality of machined surface.

Keywords: precision of gearing, small module gears, surface topology, WEDM technology

Procedia PDF Downloads 233

Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang

Abstract:

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level, as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.

Keywords: Alzheimer’s disease, speech emotion recognition, longitudinal biomarker, machine learning

Procedia PDF Downloads 113

Authors: Alexander G. Yushchenko

Abstract:

From a multi-science point of view, we analyze threats to security resulting from globalization of international information space and information and communication aggression of Russia. A definition of Ruschism is formulated as an ideology supporting aggressive actions of modern Russia against the Euro-Atlantic community. Stages of the hybrid war Russia is leading against Ukraine are described, including the elements of subversive activity of the special services, the activation of the military phase and the gradual shift of the focus of confrontation to the realm of information and communication technologies. We reveal an emergence of a threat for democratic states resulting from the destabilizing impact of a target state’s mass media and social networks being exploited by Russian secret services under freedom-of-speech disguise. Thus, we underline the vulnerability of cyber- and information security of the network society in regard of hybrid war. We propose to define the latter a synergetic war. Our analysis is supported with a long-term qualitative monitoring of representation of top state officials on popular TV channels and Facebook. From the memetics point of view, we have detected a destructive psycho-information technology used by the Kremlin, a kind of information catastrophe, the essence of which is explained in detail. In the conclusion, a comprehensive plan for information protection of the public consciousness and mentality of Euro-Atlantic citizens from the aggression of the enemy is proposed.

Keywords: cyber and information security, hybrid war, psycho-information technology, synergetic war, Ruschism

Procedia PDF Downloads 134

Authors: Yenisleidy Martinez Martinez, Yannay Casas-Ledon, Jo Dewulf

Abstract:

The ecosystem services (ES) concept has contributed to draw attention to the benefits ecosystems generate for people and how necessary natural resources are for human well-being. The identification and prioritization of the ES constitute the first steps to undertake conservation and valuation initiatives on behalf of people. Additionally, mapping the supply of ES is a powerful tool to support decision making regarding the sustainable management of landscape and natural resources. In this context, the present study aimed to identify, prioritize and map the primary ES in Biobio and Nuble regions using a methodology that combines expert judgment, multi-attribute evaluation methods, and Geographic Information Systems (GIS). Firstly, scores about the capacity of different land use/cover types to supply ES and the importance attributed to each service were obtained from experts and stakeholders via an online survey. Afterward, the ES assessment matrix was constructed, and the weighted linear combination (WLC) method was applied to mapping the overall capacity of supply of provisioning, regulating and maintenance, and cultural services. Finally, prioritized ES for the study area were selected and mapped. The results suggest that native forests, wetlands, and water bodies have the highest supply capacities of ES, while urban and industrial areas and bare areas have a very low supply of services. On the other hand, fourteen out of twenty-nine services were selected by experts and stakeholders as the most relevant for the regions. The spatial distribution of ES has shown that the Andean Range and part of the Coastal Range have the highest ES supply capacity, mostly regulation and maintenance and cultural ES. This performance is related to the presence of native forests, water bodies, and wetlands in those zones. This study provides specific information about the most relevant ES in Biobio and Nuble according to the opinion of local stakeholders and the spatial identification of areas with a high capacity to provide services. These findings could be helpful as a reference by planners and policymakers to develop landscape management strategies oriented to preserve the supply of services in both regions.

Keywords: ecosystem services, expert judgment, mapping, multi-criteria decision making, prioritization

Procedia PDF Downloads 126

Authors: Wooyoung Jung, Ghang Lee

Abstract:

This paper paper reports the worldwide status of building information modeling (BIM) adoption from the perspectives of the engagement level, the Hype Cycle model, the technology diffusion model, and BIM-uses. An online survey was distributed, and 156 experts from six continents responded. Overall, North America was the most advanced continent, followed by Oceania and Europe. Countries in Asia perceived their phase mainly as slope of enlightenment (mature) in the Hype Cycle model. In the technology diffusion model, the main BIM-users worldwide were “early majority” (third phase), but those in the Middle East/Africa and South America were “early adopters” (second phase). In addition, the more advanced the country, the more number of BIM services employed in general. In summary, North America, Europe, Oceania, and Asia were advancing rapidly toward the mature stage of BIM, whereas the Middle East/Africa and South America were still in the early phase. The simple indexes used in this study may be used to track the worldwide status of BIM adoption in long-term surveys.

Keywords: BIM adoption, BIM services, hype cycle model, technology diffusion model

Procedia PDF Downloads 557

Authors: Salma Krafessi

Abstract:

The financial markets have a multifaceted, intricate environment, and enormous volumes of data are produced every day. To find investment possibilities, possible fraudulent activity, and market oddities, accurate anomaly identification in this data is essential. Conventional methods for detecting anomalies frequently fail to capture the complex organization of financial data. In order to improve the identification of abnormalities in financial time series data, this study presents Tucker Decomposition as a reliable multi-way analysis approach. We start by gathering closing prices for the S&P 500 index across a number of decades. The information is converted to a three-dimensional tensor format, which contains internal characteristics and temporal sequences in a sliding window structure. The tensor is then broken down using Tucker Decomposition into a core tensor and matching factor matrices, allowing latent patterns and relationships in the data to be captured. A possible sign of abnormalities is the reconstruction error from Tucker's Decomposition. We are able to identify large deviations that indicate unusual behavior by setting a statistical threshold. A thorough examination that contrasts the Tucker-based method with traditional anomaly detection approaches validates our methodology. The outcomes demonstrate the superiority of Tucker's Decomposition in identifying intricate and subtle abnormalities that are otherwise missed. This work opens the door for more research into multi-way data analysis approaches across a range of disciplines and emphasizes the value of tensor-based methods in financial analysis.

Keywords: tucker decomposition, financial markets, financial engineering, artificial intelligence, decomposition models

Procedia PDF Downloads 69

Authors: Mokoena Oratilwe Penwell, Seeletse Solly Matshonisa

Abstract:

The demand for quality products is a vital factor determining the success of a producing company, and the reality of this demand influences customer satisfaction. In Sefako Makgatho Health Sciences University (SMU), concerns over the quality of food being sold have been raised by mostly students and staff who are primary consumers of food being sold by the cafeteria. Suspicions of food poisoning and the occurrence of diarrhea-related to food from the cafeteria, amongst others, have been raised. However, minimal measures have been taken to resolve the issue of food quality. New service providers have been appointed, and still, the same trends are being observed, the quality of food seems to depreciate continuously. This paper uses multi-attribute failure mode analysis (MAFMA) for failure detection and minimization on the machines used for food production by SMU catering company before being sold to both staff, and students so as to improve production plant reliability, and performance. Analytical Hierarchy Process (AHP) will be used for the severity ranking of the weight criterions and development of the hierarchical structure for the cafeteria company. Amongst other potential issues detected, maintenance of the machines and equipment used for food preparations was of concern. Also, the staff lacked sufficient hospitality skills, supervision, and management in the cafeteria needed greater attention to mitigate some of the failures occurring in the food production plant.

Keywords: MAFMA, food quality, maintenance, supervision

Procedia PDF Downloads 135

Authors: Yifu Ding, Vijay Avinash, Malcolm McCulloch

Abstract:

As the proliferation of decentralized energy systems, the UK power system allows small-scale entities such as microgrids (MGs) to tender multiple energy services including energy arbitrage and frequency responses (FRs). However, its operation requires the balance between the uncertain renewable generations and loads in real-time and has to fulfill their provision requirements of contract services continuously during the time window agreed, otherwise it will be penalized for the under-delivered provision. To hedge against risks due to uncertainties and maximize the economic benefits, we propose a stochastic model predictive control (SMPC) framework to optimize its operation for the multi-service provision. Distinguished from previous works, we include a detailed economic-degradation model of the lithium-ion battery to quantify the costs of different service provisions, as well as accurately describe the changing dynamics of the battery. Considering a branch of load and generation scenarios and the battery aging, we formulate a risk-averse cost function using conditional value at risk (CVaR). It aims to achieve the maximum expected net revenue and avoids severe losses. The framework will be performed on a case study of a PV-battery grid-tied microgrid in the UK with real-life data. To highlight its performance, the framework will be compared with the case without the degradation model and the deterministic formulation.

Keywords: model predictive control (MPC), battery degradation, frequency response, microgrids

Procedia PDF Downloads 122

Authors: Vakamalla Teja Reddy, Narasimha Mangadoddy

Abstract:

Hydrocyclones are used to separate particles into different size fractions in the mineral processing, chemical and metallurgical industries. High speed video imaging, Laser Doppler Anemometry (LDA), X-ray and Gamma ray tomography are previously used to measure the two-phase flow characteristics in the cyclone. However, investigation of solids flow characteristics inside the cyclone is often impeded by the nature of the process due to slurry opaqueness and solid metal wall vessels. In this work, a dual-plane high speed Electrical resistance tomography (ERT) is used to measure hydrocyclone internal flow dynamics in situ. Experiments are carried out in 3 inch hydrocyclone for feed solid concentrations varying in the range of 0-50%. ERT data analysis through the optimized FEM mesh size and reconstruction algorithms on air-core and solid concentration tomograms is assessed. Results are presented in terms of the air-core diameter and solids volume fraction contours using Maxwell’s equation for various hydrocyclone operational parameters. It is confirmed by ERT that the air core occupied area and wall solids conductivity levels decreases with increasing the feed solids concentration. Algebraic slip mixture based multi-phase computational fluid dynamics (CFD) model is used to predict the air-core size and the solid concentrations in the hydrocyclone. Validation of air-core size and mean solid volume fractions by ERT measurements with the CFD simulations is attempted.

Keywords: air-core, electrical resistance tomography, hydrocyclone, multi-phase CFD

Procedia PDF Downloads 379

Authors: Kaushalendra K. Khadanga, Lee Hee Hyol

Abstract:

Passenger comfort has been paramount in the design of suspension systems of high speed cars. To analyze the effect of vibration on vehicle ride quality, a vertical model of a six degree of freedom railway passenger vehicle, with front and rear suspension, is built. It includes car body flexible effects and vertical rigid modes. A second order linear shaping filter is constructed to model Gaussian white noise into random rail excitation. The temporal correlation between the front and rear wheels is given by a second order Pade approximation. The complete track and the vehicle model are then designed. An active secondary suspension system based on a Linear Quadratic Gaussian (LQG) optimal control method is designed. The results show that the LQG control method reduces the vertical acceleration, pitching acceleration and vertical bending vibration of the car body as compared to the passive system.

Keywords: active suspension, bending vibration, railway vehicle, vibration control

Procedia PDF Downloads 260

Authors: Maryam Beiranvand

Abstract:

Multi-drug resistance in various microorganisms has increased globally in many healthcare facilities. Less effective antimicrobial activity of drug therapies for infection control becomes trouble. Since 1980, no new type of antimicrobial drug has been identified, even though combinations of antibiotic drugs have been discovered almost every decade. Between 1981 and 2006, over 70% of novel pharmaceuticals and chemical agents came from natural sources. Microorganisms have yielded almost 22,000 natural compounds. The identification of antimicrobial components from endophytes bacteria could help overcome the threat posed by multi-drug resistant strains. The project aims to analyze and identify antimicrobial peptides isolated from entophytic bacteria and their activity against multidrug-resistant Gram-negative bacteria in South Korea. Endophytic Paenibacillus polymyxa. 4G3 isolated from the plant, Gynura procumbery exhibited considerable antimicrobial activity against Methicillin-resistant Staphylococcus aureus, and Escherichia coli. The Rapid Annotations using Subsystems Technology showed that the total size of the draft genome was 5,739,603bp, containing 5178 genes with 45.8% G+C content. Genome annotation using antiSMASH version 6.0.0 was performed, which predicted the most common types of non-ribosomal peptide synthetase (NRPS) and polyketide synthase (PKS). In this study, diethyl aminoethyl cellulose (DEAEC) resin was used as the first step in purifying for unknown peptides, and then the target protein was identified using hydrophilic and hydrophobic solutions, optimal pH, and step-by-step tests for antimicrobial activity. This crude was subjected to C18 chromatography and elution with 0, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100% methanol, respectively. Only the fraction eluted with 20% -60% methanol demonstrated good antimicrobial activity against MDR E. coli. The concentration of the active fragment was measured by the Brad-ford test, and Protein A280 - Thermo Fisher Scientific at the end by examining the SDS PAGE Resolving Gel, 10% Acrylamide and purity were confirmed. Our study showed that, based on the combined results of the analysis and purification. P polymyxa. 4G3 has a high potential exists for producing novel functions of polymyxin E and bacitracin against bacterial pathogens.

Keywords: endophytic bacteria, antimicrobial activity, antimicrobial peptide, whole genome sequencing analysis, multi -drug resistance gram negative bacteria

Procedia PDF Downloads 77

Authors: Sormeh Sharifi, Wasim Saman, Alemu Alemu, David Whaley

Abstract:

Although various energy rating schemes and compulsory building codes are using around the world, there are increasing reports on overheating in energy efficient dwellings. Given that the cooling demand of buildings is rising globally because of the climate change, it is more likely that the overheating issue will be observed more. This paper studied the summer indoor temperature in eight air-conditioned multi-level houses in Adelaide which have complied with the Australian Nationwide Houses Energy Rating Scheme (NatHERS) minimum energy performance of 7.5 stars. Through monitored temperature, this study explores that overheating is experienced on 75.5% of top floors during cooling periods while the air-conditioners were running. This paper found that the energy efficiency regulations have significantly improved thermal comfort in low floors, but not on top floors, and the energy-efficient house is not necessarily adapted with the air temperature fluctuations particularly on top floors. Based on the results, this study suggests that the envelope of top floors for multi-level houses in South Australian context need new criteria to make the top floor more heat resistance in order to: preventing the overheating, reducing the summer pick electricity demand and providing thermal comfort. Some methods are used to improve the envelope of the eight case studies. The results demonstrate that improving roofs was the most effective part of the top floors envelope in terms of reducing the overheating.

Keywords: building code, climate change, energy-efficient building, energy rating, overheating, thermal comfort

Procedia PDF Downloads 220

Authors: Chaiyawat Musikapan, Ratchatin Chancharoen, Saknan Bongsebandhu-Phubhakdi

Abstract:

For many recent years, soft robotic fingers were used for supporting the patients who had survived the neurological diseases that resulted in muscular disorders and neural network damages, such as stroke and Parkinson’s disease, and inflammatory symptoms such as De Quervain and trigger finger. Generally, the major hand function is significant to manipulate objects in activities of daily living (ADL). In this work, we proposed the model of soft actuator that manufactured by full 3D printing without the molding process and one material for use. Furthermore, we designed the model with a technique of multi cavitation cells (MC-Cells). Then, we demonstrated the curvature bending, fluidic pressure and force that generated to the model for assistive finger flexor and hand grasping. Also, the soft actuators were characterized in mathematics solving by the length of chord and arc length. In addition, we used an adaptive push-button switch machine to measure the force in our experiment. Consequently, we evaluated biomechanics efficiency by the range of motion (ROM) that affected to metacarpophalangeal joint (MCP), proximal interphalangeal joint (PIP) and distal interphalangeal joint (DIP). Finally, the model achieved to exhibit the corresponding fluidic pressure with force and ROM to assist the finger flexor and hand grasping.

Keywords: biomechanics efficiency, curvature bending, hand functional assistance, multi cavitation cells (MC-Cells), range of motion (ROM)

Procedia PDF Downloads 260

Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

Abstract:

In this paper, we propose a novel inference algorithm for the multi-class Gaussian process classification model that can be used in the field of human behavior recognition. This algorithm can drive simultaneously both a posterior distribution of a latent function and estimators of hyper-parameters in a Gaussian process classification model with multi-class. Our algorithm is based on the Laplace approximation (LA) technique and variational EM framework. This is performed in two steps: called expectation and maximization steps. First, in the expectation step, using the Bayesian formula and LA technique, we derive approximately the posterior distribution of the latent function indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. Second, in the maximization step, using a derived posterior distribution of latent function, we compute the maximum likelihood estimator for hyper-parameters of a covariance matrix necessary to define prior distribution for latent function. These two steps iteratively repeat until a convergence condition satisfies. Moreover, we apply the proposed algorithm with human action classification problem using a public database, namely, the KTH human action data set. Experimental results reveal that the proposed algorithm shows good performance on this data set.

Keywords: bayesian rule, gaussian process classification model with multiclass, gaussian process prior, human action classification, laplace approximation, variational EM algorithm

Procedia PDF Downloads 334

Authors: Ravi Vishwanath, Saumya Kumaar, S. N. Omkar

Abstract:

Brain-computer interfacing (BCI) is a technology that is almost four decades old, and it was developed solely for the purpose of developing and enhancing the impact of neuroprosthetics. However, in the recent times, with the commercialization of non-invasive electroencephalogram (EEG) headsets, the technology has seen a wide variety of applications like home automation, wheelchair control, vehicle steering, etc. One of the latest developed applications is the mind-controlled quadrotor unmanned aerial vehicle. These applications, however, do not require a very high-speed response and give satisfactory results when standard classification methods like Support Vector Machine (SVM) and Multi-Layer Perceptron (MLPC). Issues are faced when there is a requirement for high-speed control in the case of fixed-wing unmanned aerial vehicles where such methods are rendered unreliable due to the low speed of classification. Such an application requires the system to classify data at high speeds in order to retain the controllability of the vehicle. This paper proposes a novel method of classification which uses a combination of Common Spatial Paradigm and Linear Discriminant Analysis that provides an improved classification accuracy in real time. A non-linear SVM based classification technique has also been discussed. Further, this paper discusses the implementation of the proposed method on a fixed-wing and VTOL unmanned aerial vehicles.

Keywords: brain-computer interface, classification, machine learning, unmanned aerial vehicles

Procedia PDF Downloads 283