Search results for: real wages

Authors: Jian-Heng Wu, Bor-Shen Lin

Abstract:

The temperature-salinity relationship is one of the most important characteristics used for identifying water masses in marine research. Temperature-salinity characteristics, however, may change dynamically with respect to the geographic location and is quite sensitive to the depth at the same location. When depth is taken into consideration, however, it is not easy to compare the characteristics of different water masses efficiently for a wide range of areas of the ocean. In this paper, the Gaussian mixture model was proposed to analyze the temperature-salinity-depth characteristics of water masses, based on which comparison between water masses may be conducted. Gaussian mixture model could model the distribution of a random vector and is formulated as the weighting sum for a set of multivariate normal distributions. The temperature-salinity-depth data for different locations are first used to train a set of Gaussian mixture models individually. The distance between two Gaussian mixture models can then be defined as the weighting sum of pairwise Bhattacharyya distances among the Gaussian distributions. Consequently, the distance between two water masses may be measured fast, which allows the automatic and efficient comparison of the water masses for a wide range area. The proposed approach not only can approximate the distribution of temperature, salinity, and depth directly without the prior knowledge for assuming the regression family, but may restrict the complexity by controlling the number of mixtures when the amounts of samples are unevenly distributed. In addition, it is critical for knowledge discovery in marine research to represent, manage and share the temperature-salinity-depth characteristics flexibly and responsively. The proposed approach has been applied to a real-time visualization system of ocean data, which may facilitate the comparison of water masses by aggregating the data without degrading the discriminating capabilities. This system provides an interface for querying geographic locations with similar temperature-salinity-depth characteristics interactively and for tracking specific patterns of water masses, such as the Kuroshio near Taiwan or those in the South China Sea.

Keywords: water mass, Gaussian mixture model, data visualization, system framework

Procedia PDF Downloads 142

Authors: Sunglim Lee, Susumu Fujii, Koji Okamura

Abstract:

Smart grid is a new approach for electric power grid that uses information and communications technology to control the electric power grid. Smart grid provides real-time control of the electric power grid, controlling the direction of power flow or time of the flow. Control devices are installed on the power lines of the electric power grid to implement smart grid. The number of the control devices should be determined, in relation with the area one control device covers and the cost associated with the control devices. One approach to determine the number of the control devices is to use the data on the surplus power generated by home solar generators. In current implementations, the surplus power is sent all the way to the power plant, which may cause power loss. To reduce the power loss, the surplus power may be sent to a control device and sent to where the power is needed from the control device. Under assumption that the control devices are installed on a lattice of equal size squares, our goal is to figure out the optimal spacing between the control devices, where the power sharing area (the area covered by one control device) is kept small to avoid power loss, and at the same time the power sharing area is big enough to have no surplus power wasted. To achieve this goal, a simulation using landscape ecology method is conducted on a sample area. First an aerial photograph of the land of interest is turned into a mosaic map where each area is colored according to the ratio of the amount of power production to the amount of power consumption in the area. The amount of power consumption is estimated according to the characteristics of the buildings in the area. The power production is calculated by the sum of the area of the roofs shown in the aerial photograph and assuming that solar panels are installed on all the roofs. The mosaic map is colored in three colors, each color representing producer, consumer, and neither. We started with a mosaic map with 100 m grid size, and the grid size is grown until there is no red grid. One control device is installed on each grid, so that the grid is the area which the control device covers. As the result of this simulation we got 350 m as the optimal spacing between the control devices that makes effective use of the surplus power for the sample area.

Keywords: landscape ecology, IT, smart grid, aerial photograph, simulation

Procedia PDF Downloads 443

Authors: Binh T. T. Nguyen, Zhenyu Li, Eric Yap, Yi Zhang, Ai-Qun Liu

Abstract:

Silicon-photonic-sensor system is an emerging class of analytical technologies that use evanescent field wave to sensitively measure the slight difference in the surrounding environment. The wavelength shift induced by local refractive index change is used as an indicator in the system. These devices can be served as sensors for a wide variety of chemical or biomolecular detection in clinical and environmental fields. In our study, a system including a silicon-based micro-ring resonator, microfluidic channel, and optical processing is designed, fabricated for biomolecule detection. The system is demonstrated to detect Clostridium botulinum type A neurotoxin (BoNT) in different water sources. BoNT is one of the most toxic substances known and relatively easily obtained from a cultured bacteria source. The toxin is extremely lethal with LD50 of about 0.1µg/70kg intravenously, 1µg/ 70 kg by inhalation, and 70µg/kg orally. These factors make botulinum neurotoxins primary candidates as bioterrorism or biothreat agents. It is required to have a sensing system which can detect BoNT in a short time, high sensitive and automatic. For BoNT detection, silicon-based micro-ring resonator is modified with a linker for the immobilization of the anti-botulinum capture antibody. The enzymatic reaction is employed to increase the signal hence gains sensitivity. As a result, a detection limit to 30 pg/mL is achieved by our silicon-photonic sensor within a short period of 80 min. The sensor also shows high specificity versus the other type of botulinum. In the future, by designing the multifunctional waveguide array with fully automatic control system, it is simple to simultaneously detect multi-biomaterials at a low concentration within a short period. The system has a great potential to apply for online, real-time and high sensitivity for the label-free bimolecular rapid detection.

Keywords: biotoxin, photonic, ring resonator, sensor

Procedia PDF Downloads 116

Authors: Ali Bayram, Remzi Yiğiter

Abstract:

Objective: Alzheimer's disease (AD), the most common cause of dementia, is a progressive neurodegenerative disease. At present, diagnosis of AD is rather late in the disease. Therefore, we attempted to find peripheral biomarkers for the early diagnosis of AD. Herein, we conducted a study to investigate the unc-51 like autophagy activating kinase-1 (ULK1) mRNA expression levels in human peripheral blood mononuclear cells from patients with Alzheimer's disease. Method: To determine whether ULK1 gene expression are altered in AD patients, we measured their gene expression in human peripheral blood cell in 50 patients with AD and 50 age and gender matched healthy controls by quantitative real-time PCR technique. Results: We found that both ULK1 gene expression in peripheral blood cell were significantly decreased in patients with AD as compared with controls (p <0.05). Lower levels of ULK1 gene expression were significantly associated with the increased risk for AD. Conclusions: Serine/threonine-protein kinase involved in autophagy in response to starvation. Acts upstream of phosphatidylinositol 3-kinase PIK3C3 to regulate the formation of autophagophores, the precursors of autophagosomes. Part of regulatory feedback loops in autophagy: acts both as a downstream effector and negative regulator of mammalian target of rapamycin complex 1 (mTORC1) via interaction with RPTOR. Activated via phosphorylation by AMPK and also acts as a regulator of AMPK by mediating phosphorylation of AMPK subunits PRKAA1, PRKAB2, and PRKAG1, leading to negatively regulate AMPK activity. May phosphorylate ATG13/KIAA0652 and RPTOR; however such data need additional evidences. Plays a role early in neuronal differentiation and is required for granule cell axon formation. Alzheimer is the most common neurodegenerative disease. Our results provide useful information that the ULK1 gene expression is decreased in the neurodegeneration and AD patients with, indicating their possible systemic involvement in AD.

Keywords: Alzheimer’s sisease, ULK1, mRNA expression, RT-PCR

Procedia PDF Downloads 396

Authors: Antonios Paraskevas, Michael Madas

Abstract:

For a university to maintain its international competitiveness in education, it is essential to recruit qualitative academic staff as it constitutes its most valuable asset. This selection demonstrates a significant role in achieving strategic objectives, particularly by emphasizing a firm commitment to the exceptional student experience and innovative teaching and learning practices of high quality. In this vein, the appropriate selection of academic staff establishes a very important factor of competitiveness, efficiency and reputation of an academic institute. Within this framework, our work demonstrates a comprehensive methodological concept that emphasizes the multi-criteria nature of the problem and how decision-makers could utilize our approach in order to proceed to the appropriate judgment. The conceptual framework introduced in this paper is built upon a hybrid neutrosophic method based on the Neutrosophic Analytical Hierarchy Process (N-AHP), which uses the theory of neutrosophy sets and is considered suitable in terms of a significant degree of ambiguity and indeterminacy observed in the decision-making process. To this end, our framework extends the N-AHP by incorporating the Neutrosophic Delphi Method (N-DM). By applying the N-DM, we can take into consideration the importance of each decision-maker and their preferences per evaluation criterion. To the best of our knowledge, the proposed model is the first which applies the Neutrosophic Delphi Method in the selection of academic staff. As a case study, it was decided to use our method for a real problem of academic personnel selection, having as the main goal to enhance the algorithm proposed in previous scholars’ work, and thus taking care of the inherent ineffectiveness which becomes apparent in traditional multi-criteria decision-making methods when dealing with situations alike. As a further result, we prove that our method demonstrates greater applicability and reliability when compared to other decision models.

Keywords: multi-criteria decision making methods, analytical hierarchy process, delphi method, personnel recruitment, neutrosophic set theory

Procedia PDF Downloads 116

Authors: King Kumire

Abstract:

The Outer Space Treaty and the Moon Treaty have been the backbone of space law. However, scientists, engineers, and policymakers have been silent about how human settlement on celestial bodies would change the legal dimensions of space law. Indeed, these legal space regimes should have a prescription on how galactic courts should deal with the aspect of space property ownership. On this planet earth, one can vindicate his own assets. In extraterrestrial environments, this is not the case because space law is fatigued by terrestrial body sovereignty, which must be upheld. However, the recent commercialization of microgravity environments requires property ownership laws to be enacted. Space activities have mutated to the extent that it is almost possible to build communities in space. The discussions on the moon village concept will be mentioned as well to give clarity on the subject to the audience. It should be stated that launchers can now explore the cosmos with space tourists. The world is also busy doing feasibility studies on how to implement space mining projects. These activities indisputably show that the research is important because it will not only expose how the cosmic world is constrained by existing legal frameworks, but it will provide a remedy for how the inevitable dilemma of property rights can be resolved through the formulation of multilateral and all-inclusive policies. The discussion will model various aspects of terrestrial property rights and the associated remedies against what can be applicable and customized for use in extraterrestrial environments. Transfer of ownership in space is also another area of interest as the researcher shall try to distinguish between envisaged personal and real rights in the new frontier vis-a-vis mainland transfer transactions. The writer imagines the extent to which the concepts of servitudes, accession, prescription and commixes, and other property templates can act as a starting point when cosmic probers move forward with the revision of orbital law. The article seeks to reconcile these ownership constraints by working towards the development of a living space common law which is elastic and embroidered by sustainable recommendations. A balance between transplanting terrestrial laws to the galactic arena and the need to enact new ones which will complement the existing space treaties will be meticulously pivoted.

Keywords: rights, commercialisation, ownership, sovereignty

Procedia PDF Downloads 136

Authors: Oluwafemi Samuel Oyamakin

Abstract:

The forest in Nigeria is currently estimated to extend to around 9.6 million hectares, but used to expand over central and southern Nigeria decades ago. The forest estate is shrinking due to long-term human exploitation for agricultural development, fuel wood demand, uncontrolled forest harvesting and urbanization, amongst other factors, compounded by population growth in rural areas. Nigeria has lost more than 50% of its forest cover since 1990 and currently less than 10% of the country is forested. The current deforestation rate is estimated at 3.7%, which is one of the highest in the world. Reducing Emissions from Deforestation and forest Degradation plus conservation, sustainable management of forests and enhancement of forest carbon stocks constituted what is referred to as REDD+. This study evaluated some of the existing way of computing carbon stocks using eight indigenous tree species like Mansonia, Shorea, Bombax, Terminalia superba, Khaya grandifolia, Khaya senegalenses, Pines and Gmelina arborea. While these components are the essential elements of REDD+ programme, they can be brought under a broader framework of systems analysis designed to arrive at optimal solutions for future predictions through statistical distribution pattern of carbon sequestrated by various species of tree. Available data on height and diameter of trees in Ibadan were studied and their respective potentials of carbon sequestration level were assessed and subjected to tests so as to determine the best statistical distribution that would describe the carbon sequestration pattern of trees. The result of this study suggests a reasonable statistical distribution for carbons sequestered in simulation studies and hence, allow planners and government in determining resources forecast for sustainable development especially where experiments with real-life systems are infeasible. Sustainable management of forest can then be achieved by projecting future condition of forests under different management regimes thereby supporting conservation and REDD+ programmes in Nigeria.

Keywords: REDD+, carbon, climate change, height and diameter

Procedia PDF Downloads 165

Authors: Oliver T. Gore

Abstract:

Social inequalities and inequity of outcomes in higher education (HE) persist in South Africa despite the government introducing policy that seeks to address social injustices brought about by previous apartheid policies. In addressing these social injustices, HE policy conceptualises inequalities under the concept of historical ‘disadvantage’ which is understood to be primarily race-based. The study adds on to the existing knowledge on inequalities through developing the dimensions of (dis)advantage, which have the potential to inform the South African HE policy on providing equal opportunities amongst diverse students to participate and succeed in their studies. Drawing from the capabilities approach, this study argues that (dis)advantage can be richly understood in terms of students’ capabilities, functionings and agency as opposed to a sole focus on race. The study argues that limited freedoms, lack of effective opportunities, and reduced agency for students to turn university resources into real achievements such as personal development, economic skills and social responsibility amounts to disadvantage, while the converse is also true. The study draws from qualitative interview data with honours students, university staff and Student Representative Council members from five different university departments at one South African university. This presentation uses results from 20 students and reveals what their university experiences tell us regarding students’ unfreedoms in relation to: the inability to make decisions, poor schooling backgrounds, inadequate finances, emotional stress, lack of social support, inability to understand the language of instruction, lack of safe transport and accommodation issues. Despite these unfreedoms, the data shows that the students aspired and persevered with their studies. Using theory and empirical data in conversation, the paper shows that there is a need to nuance the definition of (dis)advantage, particularly by focusing on how different forms of disadvantage intersect with each other.

Keywords: capabilities approach, (dis)advantage, higher education, social justice

Procedia PDF Downloads 140

Authors: Gayathri Nagarajan, L. D. Dhinesh Babu

Abstract:

Health care is one of the prominent industries that generate voluminous data thereby finding the need of machine learning techniques with big data solutions for efficient processing and prediction. Missing data, incomplete data, real time streaming data, sensitive data, privacy, heterogeneity are few of the common challenges to be addressed for efficient processing and mining of health care data. In comparison with other applications, accuracy and fast processing are of higher importance for health care applications as they are related to the human life directly. Though there are many machine learning techniques and big data solutions used for efficient processing and prediction in health care data, different techniques and different frameworks are proved to be effective for different applications largely depending on the characteristics of the datasets. In this paper, we present a framework that uses ensemble machine learning technique gradient boosted trees for data classification in health care big data. The framework is built on Spark platform which is fast in comparison with other traditional frameworks. Unlike other works that focus on a single technique, our work presents a comparison of six different machine learning techniques along with gradient boosted trees on datasets of different characteristics. Five benchmark health care datasets are considered for experimentation, and the results of different machine learning techniques are discussed in comparison with gradient boosted trees. The metric chosen for comparison is misclassification error rate and the run time of the algorithms. The goal of this paper is to i) Compare the performance of gradient boosted trees with other machine learning techniques in Spark platform specifically for health care big data and ii) Discuss the results from the experiments conducted on datasets of different characteristics thereby drawing inference and conclusion. The experimental results show that the accuracy is largely dependent on the characteristics of the datasets for other machine learning techniques whereas gradient boosting trees yields reasonably stable results in terms of accuracy without largely depending on the dataset characteristics.

Keywords: big data analytics, ensemble machine learning, gradient boosted trees, Spark platform

Procedia PDF Downloads 237

Authors: Canan Duzan

Abstract:

For most language learners, mastery of the speaking skill is the proof of the mastery of the foreign language. On the other hand, the speaking skill is considered as the most difficult aspect of language learning to develop for both learners and teachers. Especially in countries like Turkey where exposure to the target language is minimum and resources and opportunities provided for language practice are scarce, teaching and learning to speak the language become a real struggle for teachers and learners alike. Data collected from students, instructors, faculty members and the business sector in needs analysis studies conducted previously at Middle East Technical University (METU) consistently revealed the need for addressing the problem of lack of confidence in speaking English. Action was taken during the design of the only EAP speaking course offered in Modern Languages Department since lack of confidence is considered to be a serious barrier for effective communication and causes learners to suffer from insecurity, uncertainty and fear. “Confidence building” served as the guiding principle in the syllabus design, nature of the tasks created for the course and the assessment procedures to help learners become more confident speakers of English. In order to see the effectiveness of the decisions made during the design phase of the course and whether students become more confident speakers upon completion of the course, a case study was carried out with 100 students at METU. A questionnaire including both Likert-Scale and open-ended items were administered to students to collect data and this data were analyzed using the SPSS program. Group interviews were also carried out to gain more insight into the effectiveness of the course in terms of building speaking confidence. This presentation will explore the specific actions taken to develop students’ confidence based on the findings of program evaluation studies and to what extent the students believe these actions to be effective in improving their confidence. The unique design of this course and strategies adopted for confidence building are highly applicable in other EAP contexts and may yield similar positive results.

Keywords: confidence, EAP, speaking, strategy

Procedia PDF Downloads 400

Authors: Robin Ferguson

Abstract:

The context which this paper explores is the provision of Technical Vocational Education and Training (TVET) of southern African workers at sea on local and foreign vessels using a blended learning approach. The pedagogical challenge of providing quality education in this context is that multiple African and foreign languages and cultural norms are found amongst the all-male crew; and there are widely differing levels of education, low levels of digital literacy and limited connectivity. The methodology used is a nested case study. The study describes the mechanisms used to provide ongoing, real-time workplace TVET on two foreign vessels. Some training was done in person when the vessels came into port, however, the majority of the TVET was achieved from shore to ship using a combination of commonly available Google and Microsoft Apps and WhatsApp. Voice, video and text in multiple languages were used to accommodate different learning styles. The learning was supported by the development of learning networks using social media. This paper also reflects on the shore-based organisational change processes required to support sea learning. The conceptual framework used is the Theory of Practice Architectures (TPA) as is provides a site-ontological perspective of the sayings/thinkings, doings and relatings of this workplace training which is multiplanar as it plays out at sea and ashore, in-person and on-line. Using TPA, the overarching practice architectures and supporting structures which confound or enable these learning practices are revealed. The contribution which this paper makes is an insight into an innovative vocational pedagogy which promotes ICT-mediated learning amongst workers who suffer from low levels of literacies and limited ICT-access and who work and live in remote places. It is a pedagogy of possibility which crosses the digital divide.

Keywords: theory of practice architecture, microsoft, google, whatsapp, vocational pedagogy, mariners, distributed workplaces

Procedia PDF Downloads 80

Authors: Keng H. Kong, Louis C. Tan, Wing L. Aw, Kay Y. Tay

Abstract:

Background: Fatigue is a common problem in patients with Parkinson's disease, with reported prevalence of up to 70%. Fatigue can be disabling and has adverse effects on patients' quality of life. There is currently no satisfactory treatment of fatigue. Acupuncture is effective in the treatment of fatigue, especially that related to cancer. Its role in Parkinson's disease-related fatigue is uncertain. Aims: To evaluate the clinical efficacy of acupuncture treatment in Parkinson's disease-related fatigue. Hypothesis: We hypothesize that acupuncture is effective in alleviating Parkinson's disease-related fatigue. Design: A single center, randomized, controlled study with two parallel arms. Participants: Forty participants with idiopathic Parkinson's disease will be enrolled. Interventions: Participants will be randomized to receive verum (real) acupuncture or placebo acupuncture. The retractable non-invasive sham needle will be used in the placebo group. The intervention will be administered twice a week for five weeks. Main outcome measures: The primary outcome will be the change in general fatigue score of the multidimensional fatigue inventory at week 5. Secondary outcome measures include other subscales of the multidimensional fatigue inventory, movement disorders society-unified Parkinson's disease rating scale, Parkinson's disease questionnaire-39 and geriatric depression scale. All outcome measures will be assessed at baseline (week 0), completion of intervention (week 5) and 4 weeks after completion of intervention (week 9). Results: To date, 23 participants have been recruited and nine have completed the study. The mean age is 63.5±14.2 years, mean duration of Parkinson’s disease is 6.4±1.8 years and mean MDS-UPDRS score is 8.3±2.8. The mean general fatigue score of the multidimensional fatigue inventory is 13.5±4.6. No significant adverse event related to acupuncture is noted. Potential significance: If the results are as expected, this study will provide preliminary scientific evidence for the efficacy of acupuncture in Parkinson's Disease-related fatigue, and opens the door for a larger multicentre trial to be performed. In the longer term, it may lead to the integration of acupuncture in the care of patients with Parkinson's disease.

Keywords: acupuncture, fatigue, Parkinson's disease, trial

Procedia PDF Downloads 304

Authors: Khalid Iqbal, Saima Altaf, M. Akram, Muhammad Abdur Rafaye, Saeed Ahmad Buzdar

Abstract:

Objective: Verification of patient-specific intensity modulated radiation therapy (IMRT) plans using different 2-D detectors has become increasingly popular due to their ease of use and immediate readout of the results. The purpose of this study was to test and compare various 2-D detectors for dosimetric quality assurance (QA) of intensity-modulated radiotherapy (IMRT) with the vision to find alternative QA methods. Material and Methods: Twenty IMRT patients (12 of brain and 8 of the prostate) were planned on Eclipse treatment planning system using Varian Clinac DHX on both energies 6MV and 15MV. Verification plans of all such patients were also made and delivered to Map check2, EPID (Electronic portal imaging device) and Gafchromic EBT3. Gamma index analyses were performed using different criteria to evaluate and compare the dosimetric results. Results: Statistical analysis shows the passing rate of 99.55%, 97.23% and 92.9% for 6MV and 99.53%, 98.3% and 94.85% for 15 MV energy using a criteria of ±5% of 3mm, ±3% of 3mm and ±3% of 2mm respectively for brain, whereas using ±5% of 3mm and ±3% of 3mm gamma evaluation criteria, the passing rate is 94.55% and 90.45% for 6MV and 95.25%9 and 95% for 15 MV energy for the case of prostate using EBT3 film. Map check 2 results shows the passing rates of 98.17%, 97.68% and 86.78% for 6MV energy and 94.87%,97.46% and 88.31% for 15 MV energy respectively for brain using a criteria of ±5% of 3mm, ±3% of 3mm and ±3% of 2mm, whereas using ±5% of 3mm and ±3% of 3mm gamma evaluation criteria gives the passing rate of 97.7% and 96.4% for 6MV and 98.75%9 and 98.05% for 15 MV energy for the case of prostate. EPID 6 MV and gamma analysis shows the passing rate of 99.56%, 98.63% and 98.4% for the brain, 100% and 99.9% for prostate using the same criteria as for map check 2 and EBT 3 film. Conclusion: The results demonstrate excellent passing rates were obtained for all dosimeter when compared with the planar dose distributions for 6 MV IMRT fields as well as for 15 MV. EPID results are better than EBT3 films and map check 2 because it is likely that part of this difference is real, and part is due to manhandling and different treatment set up verification which contributes dose distribution difference. Overall all three dosimeter exhibits results within limits according to AAPM report.120.

Keywords: gafchromic EBT3, radiochromic film dosimetry, IMRT verification, EPID

Procedia PDF Downloads 419

Authors: Mehrdad Abkenari, Orod Zarrinkafsh, Mohsen Ramezan Shirazi

Abstract:

Construction projects initiate in complicated dynamic environments and, due to the close relationships between project parameters and the unknown outer environment, they are faced with several uncertainties and risks. Success in time, cost and quality in large scale construction projects is uncertain in consequence of technological constraints, large number of stakeholders, too much time required, great capital requirements and poor definition of the extent and scope of the project. Projects that are faced with such environments and uncertainties can be well managed through utilization of the concept of risk management in project’s life cycle. Although the concept of risk is dependent on the opinion and idea of management, it suggests the risks of not achieving the project objectives as well. Furthermore, project’s risk analysis discusses the risks of development of inappropriate reactions. Since evaluation and prioritization of construction projects has been a difficult task, the network structure is considered to be an appropriate approach to analyze complex systems; therefore, we have used this structure for analyzing and modeling the issue. On the other hand, we face inadequacy of data in deterministic circumstances, and additionally the expert’s opinions are usually mathematically vague and are introduced in the form of linguistic variables instead of numerical expression. Owing to the fact that fuzzy logic is used for expressing the vagueness and uncertainty, formulation of expert’s opinion in the form of fuzzy numbers can be an appropriate approach. In other words, the evaluation and prioritization of construction projects on the basis of risk factors in real world is a complicated issue with lots of ambiguous qualitative characteristics. In this study, evaluated and prioritization the risk parameters and factors with fuzzy logy method by combination of three method DEMATEL (Decision Making Trial and Evaluation), ANP (Analytic Network Process) and TOPSIS (Technique for Order-Preference by Similarity Ideal Solution) on Construction Management.

Keywords: fuzzy logy, risk, prioritization, assessment

Procedia PDF Downloads 593

Authors: Piyanee Khumpao

Abstract:

Under the Thai Penal Code and Customs Act, sex toys are criminalized and completely prohibited through the legal interpretation as obscene objects by law enforcement, despite there is no explicit legal sanction against them. The purpose of preventing people from accessing sex toys is to preserve public morals. However, sex toys are still available, exposed, and sold publicly in main cities throughout Thailand. They are easily observed by people of any age. This paper argues that sexuality is human nature and human right. Human deserves sexual pleasure as long as getting sexual pleasure does not inflict any harm on others. Using sex toys in private (individually and/or as a couple with mutual consent) does not constitute any harm nor degrade public moral. Therefore, the complete ban of sex toys shall be lifted and decriminalized. Nevertheless, the economic analysis illustrates that criminalization and prohibition of sex toys would lead to its black market – higher price and lower quantity. Although it is socially desirable to have fewer sex toys in the market, there will usually be high demand for them because sexual pleasure is natural and, hence, people have a lower price elasticity of demand for such things, including pornography. Thus, its deterrent effect is not very effective. Moreover, sex toys vendors still always exist because higher price incentivizes them to act illegally and may gain benefits from selling low-quality sex toys. Consequently, consumers do not have a choice to select high-quality sex toys at a reasonable price. Then, they are forced to purchase low quality sex toys at a higher price. They also may suffer from health issues as well as other harms from its dangerous/toxic substances since lower quality products are manufactured poorly to save costs. A law and economics approach supports the decriminalization of sex toys in Thailand. Other measures to control its availability shall be adopted to protect the vulnerable, such as children. Options are i) zoning or regulation on-premises selling sex toys as in Singapore, Japan, and China, ii) regulations of sex toys as medical apparatus like in the state of Alabama, and iii) the prevention of sex toys exposure in the real (physical) appearance (i.e., allowing virtual exposure of sex toys) like in India.

Keywords: human nature, law and economics approach, sex toys, sexual pleasure

Procedia PDF Downloads 127

Authors: Mohd Imtiaz S, Saurabh Jain, Pothiraj K.

Abstract:

In today’s highly competitive passenger vehicle market, comfortable driving experience is one of the key parameters significantly weighed by the customer. Smooth ride and handling of the vehicle with exceptionally reliable wheel end solution is a paramount requirement in passenger Sports Utility Vehicle (SUV) vehicles subjected to challenging terrains and loads with rigid rear drive axle configuration. Traditional wheel-end bearing systems in passenger segment rigid rear drive axle utilizes the semi-floating layout, which imparts vertical bending loads and torsion to the axle shafts. The wheel-end bearing is usually a Single or Double Row Deep-Groove Ball Bearing (DRDGBB) or Double Row Angular Contact Ball Bearing (DRACBB). This solution is cost effective and simple in architecture. However, it lacks effectiveness against the heavy loads subjected to a SUV vehicle, especially the axial trust at high-speed cornering. This paper describes the solution of Double Row Taper Roller Bearing (DRTRB) wheel-end for a SUV vehicle in the rigid rear drive axle and improvement in terms of maximizing its load carrying capacity along with better reliability in terms of axial thrust in high-speed cornering. It describes the advantage of geometry of DRTRB over DRDGBB and DRACBB highlighting contact and load flow. The paper also highlights the vehicle level considerations affecting the B10 life of the bearing system for better selection of the DRTRB wheel-ends systems. This paper also describes real time vehicle level results along with theoretical improvements.

Keywords: axial thrust, b10 life, deep-groove ball bearing, taper roller bearing, semi-floating layout.

Procedia PDF Downloads 73

Authors: Yi-Fan Lin, Peter P. Howley, Frank A. Tuyl

Abstract:

Quality measurement and reporting systems are used in healthcare internationally. In Australia, the Australian Council on Healthcare Standards records and reports hundreds of clinical indicators (CIs) nationally across the healthcare system. These CIs are measures of performance in the clinical setting, and are used as a screening tool to help assess whether a standard of care is being met. Existing analysis and reporting of these CIs incorporate Bayesian methods to address sampling variation; however, such assessments are retrospective in nature, reporting upon the previous six or twelve months of data. The use of Bayesian methods within statistical process control for monitoring systems is an important pursuit to support more timely decision-making. Our research has developed and assessed a new graphical monitoring tool, similar to a control chart, based on the beta-binomial posterior predictive (BBPP) distribution to facilitate the real-time assessment of health care organizational performance via CIs. The BBPP charts have been compared with the traditional Bernoulli CUSUM (BC) chart by simulation. The more traditional “central” and “highest posterior density” (HPD) interval approaches were each considered to define the limits, and the multiple charts were compared via in-control and out-of-control average run lengths (ARLs), assuming that the parameter representing the underlying CI rate (proportion of cases with an event of interest) required estimation. Preliminary results have identified that the BBPP chart with HPD-based control limits provides better out-of-control run length performance than the central interval-based and BC charts. Further, the BC chart’s performance may be improved by using Bayesian parameter estimation of the underlying CI rate.

Keywords: average run length (ARL), bernoulli cusum (BC) chart, beta binomial posterior predictive (BBPP) distribution, clinical indicator (CI), healthcare organization (HCO), highest posterior density (HPD) interval

Procedia PDF Downloads 200

Authors: Lancelot Boulet, Pierre Benard, Ghislain Lartigue, Vincent Moureau, Nicolas Chauvet, Sheddia Didorally

Abstract:

International aeronautic standards demand a fire certification for engines that demonstrate their resistance. This demonstration relies on tests performed with prototype engines in the late stages of the development. Hardest tests require to place a kerosene standardized flame in front of the engine casing during a given time with imposed temperature and heat flux. The purpose of this work is to provide a better characterization of a kerosene/air certification burner in order to minimize the risks of test failure. A first Large-Eddy Simulation (LES) study of the certification burner permitted to model and simulate this burner, including both adiabatic and Conjugate Heat Transfer (CHT) computations. Carried out on unstructured grids with 40 million tetrahedral cells, using the finite-volume YALES2 code, spray combustion, forced convection on walls and conduction in the solid parts of the burner were coupled to achieve a detailed description of heat transfer. It highlighted the fact that conduction inside the solid has a real impact on the flame topology and the combustion regime. However, in the absence of radiative heat transfer, unrealistic temperature of the equipment was obtained. The aim of the present study is to include the radiative heat transfer in order to reach the same temperature given by experimental measurements. First, various test-cases are conducted to validate the coupling between the different heat solvers. Then, adiabatic case, CHT case, as well as CHT including radiative transfer are studied and compared. The LES model is finally applied to investigate the heat transfer in a flame impaction configuration. The aim is to progress on fire test modeling so as to reach a good confidence level as far as success of the certification test is concerned.

Keywords: conjugate heat transfer, fire resistance test, large-eddy simulation, radiative transfer, turbulent combustion

Procedia PDF Downloads 220

Authors: Michel T. Leger, Shawn Martin

Abstract:

Leading an ecologically responsible lifestyle represents a difficult challenge. Though research in environmental education does point to an increase in the intention to act more responsibly towards the environment, this intent does not seem to translate to concrete ecological action. This mixed methods collective case study explores the adoption of ecological actions in the family, a context of socio-ecological transformation rarely examined in the scientific literature. More specifically, it takes into account the popular use of social media today to explore the potential role social media, namely Facebook, in promoting environmental action. In other words, for families who are intent on adopting an ecologically friendly lifestyle, could the use of Facebook positively affect the way family members relate to the environment and bring about real change in their daily household actions? To answer this question, twenty-one families living in an urban setting were recruited and then divided them into two distinct groups. The first group of families attempted to lower their household electrical bill as part of a private Facebook group, while the other aimed to do the same, but without the directed use of social media. For both groups, we recorded the amount of kilowatt-hours used during the project as well as the amount used for the same months the previous year, adjusting for temperature variations. Exit interviews were also conducted with each family in order to try to understand the processes of eco-citizenship development in the context of family. Results seem to suggest that both virtual social networks and one-on-one support can help to increase environmental awareness in participating family. Interestingly, families from the Facebook group seemed to demonstrate a higher degree of environmental engagement, and younger family members in this group were more active in the processes of collective behavioral change.

Keywords: environmental education, family-based eco-citizenship, social media, case study

Procedia PDF Downloads 150

Authors: Ibrahim Khan, Waqas Khalid

Abstract:

The Healthcare sector is known to consume a higher proportion of total energy consumption in the HVAC market owing to an excessive cooling and heating requirement in maintaining human thermal comfort in indoor conditions, catering to patients undergoing treatment in hospital wards, rooms, and intensive care units. The indoor thermal comfort conditions in selected hospitals of Islamabad, Pakistan, were measured on a real-time basis with the collection of first-hand experimental data using calibrated sensors measuring Ambient Temperature, Wet Bulb Globe Temperature, Relative Humidity, Air Velocity, Light Intensity and CO2 levels. The Experimental data recorded was analyzed in conjunction with the Thermal Comfort Questionnaire Surveys, where the participants, including patients, doctors, nurses, and hospital staff, were assessed based on their thermal sensation, acceptability, preference, and comfort responses. The Recorded Dataset, including experimental and survey-based responses, was further analyzed in the development of a correlation between operative temperature, operative relative humidity, and other measured operative parameters with the predicted mean vote and adaptive predicted mean vote, with the adaptive temperature and adaptive relative humidity estimated using the seasonal data set gathered for both summer – hot and dry, and hot and humid as well as winter – cold and dry, and cold and humid climate conditions. The Machine Learning Logistic Regression Algorithm was incorporated to train the operative experimental data parameters and develop a correlation between patient sensations and the thermal environmental parameters for which a new ML-based adaptive thermal comfort model was proposed and developed in our study. Finally, the accuracy of our model was determined using the K-fold cross-validation.

Keywords: predicted mean vote, thermal comfort, energy management, logistic regression, machine learning

Procedia PDF Downloads 62

Authors: Mikael Soini, Kari Björn

Abstract:

Metropolia University of Applied Sciences (MUAS) Information and Communication Technology (ICT) Degree Programme provides full-time Bachelor-level undergraduate studies. ICT Degree Programme has seven different major options; this paper focuses on Health Technology. In Health Technology, a significant curriculum change in 2014 enabled transition from fragmented curriculum including dozens of courses to a new integrated curriculum built around three 30 ECTS themes. This paper focuses especially on the second theme called Customer Oriented Software Applications. From students’ point of view, the goal of this theme is to get familiar with existing health related ICT solutions and systems, understand business around health technology, recognize social and healthcare operating principles and services, and identify customers and users and their special needs and perspectives. This also acts as a background for health related web application development. Built web application is tested, developed and evaluated with real users utilizing versatile user centred development methods. This paper presents experiences obtained from the first implementation of Customer Oriented Software Applications theme. Student feedback was gathered with two questionnaires, one in the middle of the theme and other at the end of the theme. Questionnaires had qualitative and quantitative parts. Similar questionnaire was implemented in the first theme; this paper evaluates how the theme-based integrated curriculum has progressed in Health Technology major by comparing results between theme 1 and 2. In general, students were satisfied for the implementation, timing and synchronization of the courses, and the amount of work. However there is still room for development. Student feedback and teachers’ observations have been and will be used to develop the content and operating principles of the themes and whole curriculum.

Keywords: engineering education, integrated curriculum, learning and teaching methods, learning experience

Procedia PDF Downloads 320

Authors: Nazi Pharsadanishvili, Anastasia Kitiashvili

Abstract:

The importance of studying the social-psychological features of people living in poverty is often emphasized in international research. Building a multidimensional economic framework for reducing poverty grounded in people’s experiences and values is the main goal of famous Poverty Research Centers (such as Oxford Poverty and Human Development Initiative, Abdul Latif Jameel Poverty Action Lab). The aims of the proposed research are to investigate the following characteristics of socially vulnerable people living in Georgia: 1) The features of the perceived stigma of poverty; 2) economic system justification and social justice beliefs; 3) Perceived social mobility and actual attempts at upward social mobility. Qualitative research was conducted to address the indicated research goals and descriptive research questions. Conducting in-depth interviews was considered to be the most appropriate method to capture the vivid feelings and experiences of people living in poverty. 17 respondents (registered in the unified database of socially vulnerable families) participated in in-depth interviews. According to the research results, socially vulnerable people living in Georgia perceive stigma targeted toward them. Two sub-dimensions were identified in perceived stigma: experienced stigma and internalized stigma. Experienced stigma reflects the instances of being discriminated and perceptions of negative treatment from other members of society. Internalized stigma covers negative personal emotions, the feelings of shame, the fear of future stigmatization, and self-isolation. The attitudes and justifications of the existing economic system affect people’s attempts to cope with poverty. Complex analysis of those results is important during the planning and implementing of social welfare reforms. Particularly, it is important to implement poverty stigma reduction mechanisms and help socially vulnerable people to see real perspectives on upward social mobility.

Keywords: coping with poverty, economic system justification, perceived stigma of poverty, upward social mobility

Procedia PDF Downloads 188

Authors: Xiyue Wang, Shaoning Yan

Abstract:

Cities in China today is faced with an increasingly serious river ecological crisis accompanying with the development of urbanization: waterlogging on account of the fragmented urban natural hydrological system; the limited ecological function of the hydrological system caused by a destruction of water system and waterfront ecological environment. Additionally, the eco-hydrological processes of rivers are affected by various environmental factors, which are more complex in the context of urban environment. Therefore, efficient hydrological monitoring and analysis tools, accurate and visual hydrological and hydraulic models are becoming more important basis for decision-makers and an important way for landscape architects to solve urban hydrological problems, formulating sustainable and forward-looking schemes. The study mainly introduces the river and flood analysis model based on the platform of Autodesk Civil 3D. Taking the Luanhe River in Qian'an City of Hebei Province as an example, the 3D models of the landform, river, embankment, shoal, pond, underground stream and other land features were initially built, with which the water transfer simulation analysis, river floodplain analysis, and river ecology analysis were carried out, ultimately the real-time visualized simulation and analysis of rivers in various hypothetical scenarios were realized. Through the establishment of digital hydrological and hydraulic model, the hydraulic data can be accurately and intuitively simulated, which provides basis for rational water system and benign urban ecological system design. Though, the hydrological and hydraulic model based on Autodesk Civil3D own its boundedness: the interaction between the model and other data and software is unfavorable; the huge amount of 3D data and the lack of basic data restrict the accuracy and application range. The hydrological and hydraulic model based on Autodesk Civil3D platform provides more possibility to access convenient and intelligent tool for urban planning and monitoring, a solid basis for further urban research and design.

Keywords: visualization, hydrological and hydraulic model, Autodesk Civil 3D, urban river

Procedia PDF Downloads 296

Authors: Anshar Ajatasatru

Abstract:

The decline of coal prices over past years have been significantly increasing the awareness of effective mining operation. A viable step must be undertaken in becoming more cost competitive while striving for best mining practice especially at Melak Coal Mine in East Kalimantan, Indonesia. This paper aims to show how effective dozer push measurement method can be implemented as it is controlled by contract rate on the unit basis of USD ($) per bcm. The method emerges from an idea of daily dozer push activity that continually shifts the overburden until final target design by mine planning. Volume calculation is then performed by calculating volume of each time overburden is removed within determined distance using cut and fill method from a high precision GNSS system which is applied into dozer as a guidance to ensure the optimum result of overburden removal. Accumulation of daily to weekly dozer push volume is found 95 bcm which is multiplied by average sell rate of $ 0,95, thus the amount monthly revenue is $ 90,25. Furthermore, the payment mechanism is then based on push distance and push grade. The push distance interval will determine the rates that vary from $ 0,9 - $ 2,69 per bcm and are influenced by certain push slope grade from -25% until +25%. The amount payable rates for dozer push operation shall be specifically following currency adjustment and is to be added to the monthly overburden volume claim, therefore, the sell rate of overburden volume per bcm may fluctuate depends on the real time exchange rate of Jakarta Interbank Spot Dollar Rate (JISDOR). The result indicates that dozer push measurement can be one of the surface mining alternative since it has enabled to refine method of work, operating cost and productivity improvement apart from exposing risk of low rented equipment performance. In addition, payment mechanism of contract rate by dozer push operation scheduling will ultimately deliver clients by almost 45% cost reduction in the form of low and consistent cost.

Keywords: contract rate, cut-fill method, dozer push, overburden volume

Procedia PDF Downloads 315

Authors: Amirreza Fazely Hamedani, Muzzamil Aziz, Philipp Wieder, Ramin Yahyapour

Abstract:

Software-defined networking in recent years came into the sight of so many network designers as a successor to the traditional networking. Unlike traditional networks where control and data planes engage together within a single device in the network infrastructure such as switches and routers, the two planes are kept separated in software-defined networks (SDNs). All critical decisions about packet routing are made on the network controller, and the data level devices forward the packets based on these decisions. This type of network is vulnerable to DDoS attacks, degrading the overall functioning and performance of the network by continuously injecting the fake flows into it. This increases substantial burden on the controller side, and the result ultimately leads to the inaccessibility of the controller and the lack of network service to the legitimate users. Thus, the protection of this novel network architecture against denial of service attacks is essential. In the world of cybersecurity, attacks and new threats emerge every day. It is essential to have tools capable of managing and analyzing all this new information to detect possible attacks in real-time. These tools should provide a comprehensive solution to automatically detect, predict and prevent abnormalities in the network. Big data encompasses a wide range of studies, but it mainly refers to the massive amounts of structured and unstructured data that organizations deal with on a regular basis. On the other hand, it regards not only the volume of the data; but also that how data-driven information can be used to enhance decision-making processes, security, and the overall efficiency of a business. This paper presents an intelligent big data framework as a solution to handle illegitimate traffic burden on the SDN network created by the numerous DDoS attacks. The framework entails an efficient defence and monitoring mechanism against DDoS attacks by employing the state of the art machine learning techniques.

Keywords: apache spark, apache kafka, big data, DDoS attack, machine learning, SDN network

Procedia PDF Downloads 168

Authors: S. Jayasinghe, R. B. N. Dissanayake

Abstract:

Optimization modelling together with the Network models and Linear Programming techniques is a powerful tool in problem solving and decision making in real world applications. This study developed a mathematical model to optimize the net profit by minimizing the transportation cost. This model focuses the transportation among decentralized production plants to a centralized distribution centre and then the distribution among island wide agencies considering the customer satisfaction as a requirement. This company produces basically 9 types of food items with 82 different varieties and 4 types of non-food items with 34 different varieties. Among 6 production plants, 4 were located near the city of Mawanella and the other 2 were located in Galewala and Anuradhapura cities which are 80 km and 150 km away from Mawanella respectively. The warehouse located in the Mawanella was the main production plant and also the only distribution plant. This plant distributes manufactured products to 39 agencies island-wide. The average values and average amount of the goods for 6 consecutive months from May 2013 to October 2013 were collected and then average demand values were calculated. The following constraints are used as the necessary requirement to satisfy the optimum condition of the model; there was one source, 39 destinations and supply and demand for all the agencies are equal. Using transport cost for a kilometer, total transport cost was calculated. Then the model was formulated using distance and flow of the distribution. Network optimization and linear programming techniques were used to originate the model while excel solver is used in solving. Results showed that company requires total transport cost of Rs. 146, 943, 034.50 to fulfil the customers’ requirement for a month. This is very much less when compared with data without using the model. Model also proved that company can reduce their transportation cost by 6% when distributing to island-wide customers. Company generally satisfies their customers’ requirements by 85%. This satisfaction can be increased up to 97% by using this model. Therefore this model can be used by other similar companies in order to reduce the transportation cost.

Keywords: mathematical model, network optimization, linear programming

Procedia PDF Downloads 346

Authors: Suveen Kumar

Abstract:

Oral cancer (OC) is the sixth most death causing cancer in world which includes tumour of lips, floor of the mouth, tongue, palate, cheeks, sinuses, throat, etc. Conventionally, the techniques used for OC detection are toluidine blue staining, biopsy, liquid-based cytology, visual attachments, etc., however these are limited by their highly invasive nature, low sensitivity, time consumption, sophisticated instrument handling, sample processing and high cost. Therefore, we developed biosensing chips for non-invasive detection of OC via CYFRA-21-1 biomarker. CYFRA-21-1 (molecular weight: 40 kDa) is secreted in saliva of OC patients which is a non-invasive biological fluid with a cut-off value of 3.8 ng mL-1, above which the subjects will be suffering from oral cancer. Therefore, in first work, 3-aminopropyl triethoxy silane (APTES) functionalized zirconia (ZrO2) nanoparticles (APTES/nZrO2) were used to successfully detect CYFRA-21-1 in a linear detection range (LDR) of 2-16 ng mL-1 with sensitivity of 2.2 µA mL ng-1. Successively, APTES/nZrO2-RGO was employed to prevent agglomeration of ZrO2 by providing high surface area reduced graphene oxide (RGO) support and much wider LDR (2-22 ng mL-1) was obtained with remarkable limit of detection (LOD) as 0.12 ng mL-1. Further, APTES/nY2O3/ITO platform was used for oral cancer bioseneor development. The developed biosensor (BSA/anti-CYFRA-21-1/APTES/nY2O3/ITO) have wider LDR (0.01-50 ng mL-1) with remarkable limit of detection (LOD) as 0.01 ng mL-1. To improve the sensitivity of the biosensing platform, nanocomposite of yattria stabilized nanostructured zirconia-reduced graphene oxide (nYZR) based biosensor has been developed. The developed biosensing chip having ability to detect CYFRA-21-1 biomolecules in the range of 0.01-50 ng mL-1, LOD of 7.2 pg mL-1 with sensitivity of 200 µA mL ng-1. Further, the applicability of the fabricated biosensing chips were also checked through real sample (saliva) analysis of OC patients and the obtained results showed good correlation with the standard protein detection enzyme linked immunosorbent assay (ELISA) technique.

Keywords: non-invasive, oral cancer, nanomaterials, biosensor, biochip

Procedia PDF Downloads 125

Authors: Emmanuel Iyamuremye, Jean François Maniriho, Irenee Ndayambaje

Abstract:

Mathematics is the foundational enabling discipline that underpins science, technology, and engineering disciplines. Science, technology, engineering, and mathematics (STEM) subjects are foreseen as the engine for socio-economic transformation. Rwanda has done reforms in education aiming at empowering and preparing students for the real world job by providing career pathways in science, technology, engineering, and mathematics related fields. While that considered so, the performance in mathematics has remained deplorable in both formative and national examinations. Therefore, this paper aims at exploring the extent to which the engage, explore, explain, elaborate and evaluate (5Es) instructional model contributing towards students’ achievement in mathematics. The present study adopted the pre-test, post-test non-equivalent control group quasi-experimental design. The 5Es instructional model was applied to the experimental group while the control group received instruction with the conventional teaching method for eight weeks. One research-made instrument, mathematics achievement test (MAT), was used for data collection. A pre-test was given to students before the intervention to make sure that both groups have equivalent characteristics. At the end of the experimental period, the two groups have undergone a post-test to ascertain the contribution of the 5Es instructional model. Descriptive statistics and analysis of covariance (ANCOVA) were used for the analysis of the study. For determining the improvement in mathematics, Hakes methods of calculating gain were used to analyze the pre-test and post-test scores. Results showed that students exposed to 5Es instructional model achieved significantly better performance in mathematics than students instructed using the conventional teaching method. It was also found that 5Es instructional model made lessons more interesting, easy and created friendship among students. Thus, 5Es instructional model was recommended to be adopted as a close substitute to the conventional teaching method in teaching mathematics in lower secondary schools in Rwanda.

Keywords: 5Es instructional model, achievement, conventional teaching method, mathematics

Procedia PDF Downloads 102

Authors: María García-García, Esther Simancas-González, Said Balhadj, Carmen Silva-Robles, Driss Ferhane

Abstract:

Cooperation between the territories on both sides of the Strait of Gibraltar is an urgent reality. the south of Spain and northern Morocco share a common historical past and belong to a very similar geographical and ecological area. Economic, social and cultural relations make cooperation between the two countries’ (Spain and Morocco) a priority for the EU and both countries governments. Likewise, deepened changes happened in production systems and consumption patterns had seriously damaged and weakened the craftwork sector. The promotion of local crafts, and its economic value, and the cooperation with the north of Morocco has been an important issue for the Andalusian government in recent years. The main aim of this work is to understand the strengths and weaknesses of the Tangier - Tetuan region craftworks sector in order to develop accurate communication and promotion plans. From the knowledge of the real identity, the sector could be repositioned. Promotion and communication could be a spur to traditional sectors, such as crafts. Competitiveness requires "the culture of communication, the cooperation between different companies to build powerful territory brands and maintain the establishment confidence and effectiveness relationships among agencies and organizations". The lack of previous literature addressing how Tangier craftwork promote and communicate its value to their stakeholders, has conducted the study to an exploratory approach with a double dimension: internal, Tangier craftwork sector image, and external, Andalusia image of the sector in Tangier. Different interviews were conducted with Andalusian partners involved in the artisanal sector (9 master craftsmen and 3 institutions) and focus groups with 9 Tangiers craftsmen were developed. The result of these interviews and expert groups are reflected in a SWOT analysis which reveals a handcraft industry with a worrying wide-spread and undifferentiated identity and reluctance to innovation and new technologies.

Keywords: communication management, image, Moroccan crafts, Spain-Morocco cooperation

Procedia PDF Downloads 326

Authors: Taha Benarbia

Abstract:

The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

Procedia PDF Downloads 76