Search results for: input output linearization

Authors: Emmanuel Ogala

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Cloud computing has been envisioned as the next-generation architecture of Information Technology (IT) enterprise. In contrast to traditional solutions where IT services are under physical, logical and personnel controls, cloud computing moves the application software and databases to the large data centres, where the management of the data and services may not be fully trustworthy. This is due to the fact that the systems are opened to the whole world and as people tries to have access into the system, many people also are there trying day-in day-out on having unauthorized access into the system. This research contributes to the improvement of cloud computing security for better operation. The work is motivated by two problems: first, the observed easy access to cloud computing resources and complexity of attacks to vital cloud computing data system NIC requires that dynamic security mechanism evolves to stay capable of preventing illegitimate access. Second; lack of good methodology for performance test and evaluation of biometric security algorithms for securing records in cloud computing environment. The aim of this research was to evaluate the performance of an integrated security system (ISS) for securing exams records in cloud computing environment. In this research, we designed and implemented an ISS consisting of three security mechanisms of biometric (fingerprint), auto-PIN and password into one stream of access control and used for securing examination records in Kogi State University, Anyigba. Conclusively, the system we built has been able to overcome guessing abilities of hackers who guesses people password or pin. We are certain about this because the added security system (fingerprint) needs the presence of the user of the software before a login access can be granted. This is based on the placement of his finger on the fingerprint biometrics scanner for capturing and verification purpose for user’s authenticity confirmation. The study adopted the conceptual of quantitative design. Object oriented and design methodology was adopted. In the analysis and design, PHP, HTML5, CSS, Visual Studio Java Script, and web 2.0 technologies were used to implement the model of ISS for cloud computing environment. Note; PHP, HTML5, CSS were used in conjunction with visual Studio front end engine design tools and MySQL + Access 7.0 were used for the backend engine and Java Script was used for object arrangement and also validation of user input for security check. Finally, the performance of the developed framework was evaluated by comparing with two other existing security systems (Auto-PIN and password) within the school and the results showed that the developed approach (fingerprint) allows overcoming the two main weaknesses of the existing systems and will work perfectly well if fully implemented.

Keywords: performance evaluation, fingerprint, auto-pin, password-based, security systems, cloud computing environment

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Authors: Akindele Ojo, Olanike Ojo, Agatha Oseghale

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The empirical study examined the allocative efficiency of small holder tuber crop farmers in North central, Nigeria. Data used for the study were obtained from primary source using a multi-stage sampling technique with structured questionnaires administered to 300 randomly selected tuber crop farmers from the study area. Descriptive statistics, data envelopment analysis and Tobit regression model were used to analyze the data. The DEA result on the classification of the farmers into efficient and inefficient farmers showed that 17.67% of the sampled tuber crop farmers in the study area were operating at frontier and optimum level of production with mean allocative efficiency of 1.00. This shows that 82.33% of the farmers in the study area can still improve on their level of efficiency through better utilization of available resources, given the current state of technology. The results of the Tobit model for factors influencing allocative inefficiency in the study area showed that as the year of farming experience, level of education, cooperative society membership, extension contacts, credit access and farm size increased in the study area, the allocative inefficiency of the farmers decreased. The results on effects of the significant determinants of allocative inefficiency at various distribution levels revealed that allocative efficiency increased from 22% to 34% as the farmer acquired more farming experience. The allocative efficiency index of farmers that belonged to cooperative society was 0.23 while their counterparts without cooperative society had index value of 0.21. The result also showed that allocative efficiency increased from 0.43 as farmer acquired high formal education and decreased to 0.16 with farmers with non-formal education. The efficiency level in the allocation of resources increased with more contact with extension services as the allocative efficeincy index increased from 0.16 to 0.31 with frequency of extension contact increasing from zero contact to maximum of twenty contacts per annum. These results confirm that increase in year of farming experience, level of education, cooperative society membership, extension contacts, credit access and farm size leads to increases efficiency. The results further show that the age of the farmers had 32% input to the efficiency but reduces to an average of 15%, as the farmer grows old. It is therefore recommended that enhanced research, extension delivery and farm advisory services should be put in place for farmers who did not attain optimum frontier level to learn how to attain the remaining 74.39% level of allocative efficiency through a better production practices from the robustly efficient farms. This will go a long way to increase the efficiency level of the farmers in the study area.

Keywords: allocative efficiency, DEA, Tobit regression, tuber crop

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Authors: Deisy Becerra, Edwar Perez, Nicolas Rios, Miguel Asuaje

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Progressing Cavity Pump (PCP) is a type of positive displacement pump that is being awarded greater importance as capable artificial lift equipment in the heavy oil field. The most commonly PCP used is driven single lobe pump that consists of a single external helical rotor turning eccentrically inside a double internal helical stator. This type of pump was analyzed by the experimental and Computational Fluid Dynamic (CFD) approach from the DCAB031 model located in a closed-loop arrangement. Experimental measurements were taken to determine the pressure rise and flow rate with a flow control valve installed at the outlet of the pump. The flowrate handled was measured by a FLOMEC-OM025 oval gear flowmeter. For each flowrate considered, the pump’s rotational speed and power input were controlled using an Invertek Optidrive E3 frequency driver. Once a steady-state operation was attained, pressure rise measurements were taken with a Sper Scientific wide range digital pressure meter. In this study, water and three Newtonian oils of different viscosities were tested at different rotational speeds. The CFD model implementation was developed on Star- CCM+ using an Overset Mesh that includes the relative motion between rotor and stator, which is one of the main contributions of the present work. The simulations are capable of providing detailed information about the pressure and velocity fields inside the device in laminar and unsteady regimens. The simulations have a good agreement with the experimental data due to Mean Squared Error (MSE) in under 21%, and the Grid Convergence Index (GCI) was calculated for the validation of the mesh, obtaining a value of 2.5%. In this case, three different rotational speeds were evaluated (200, 300, 400 rpm), and it is possible to show a directly proportional relationship between the rotational speed of the rotor and the flow rate calculated. The maximum production rates for the different speeds for water were 3.8 GPM, 4.3 GPM, and 6.1 GPM; also, for the oil tested were 1.8 GPM, 2.5 GPM, 3.8 GPM, respectively. Likewise, an inversely proportional relationship between the viscosity of the fluid and pump performance was observed, since the viscous oils showed the lowest pressure increase and the lowest volumetric flow pumped, with a degradation around of 30% of the pressure rise, between performance curves. Finally, the Productivity Index (PI) remained approximately constant for the different speeds evaluated; however, between fluids exist a diminution due to the viscosity.

Keywords: computational fluid dynamic, CFD, Newtonian fluids, overset mesh, PCP pressure rise

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Authors: S. M. Giripunje, Mohit Kumar

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Acoustic energy that exists in our everyday life and environment have been overlooked as a green energy that can be extracted, generated, and consumed without any significant negative impact to the environment. The harvested energy can be used to enable new technology like wireless sensor networks. Technological developments in the realization of truly autonomous MEMS devices and energy storage systems have made acoustic energy harvesting (AEH) an increasingly viable technology. AEH is the process of converting high and continuous acoustic waves from the environment into electrical energy by using an acoustic transducer or resonator. AEH is not popular as other types of energy harvesting methods since sound waves have lower energy density and such energy can only be harvested in very noisy environment. However, the energy requirements for certain applications are also correspondingly low and also there is a necessity to observe the noise to reduce noise pollution. So the ability to reclaim acoustic energy and store it in a usable electrical form enables a novel means of supplying power to relatively low power devices. A quarter-wavelength straight-tube acoustic resonator as an acoustic energy harvester is introduced with polyvinylidene fluoride (PVDF) and PVDF doped with ZnO nanoparticles, piezoelectric cantilever beams placed inside the resonator. When the resonator is excited by an incident acoustic wave at its first acoustic eigen frequency, an amplified acoustic resonant standing wave is developed inside the resonator. The acoustic pressure gradient of the amplified standing wave then drives the vibration motion of the PVDF piezoelectric beams, generating electricity due to the direct piezoelectric effect. In order to maximize the amount of the harvested energy, each PVDF and PVDF-ZnO piezoelectric beam has been designed to have the same structural eigen frequency as the acoustic eigen frequency of the resonator. With a single PVDF beam placed inside the resonator, the harvested voltage and power become the maximum near the resonator tube open inlet where the largest acoustic pressure gradient vibrates the PVDF beam. As the beam is moved to the resonator tube closed end, the voltage and power gradually decrease due to the decreased acoustic pressure gradient. Multiple piezoelectric beams PVDF and PVDF-ZnO have been placed inside the resonator with two different configurations: the aligned and zigzag configurations. With the zigzag configuration which has the more open path for acoustic air particle motions, the significant increases in the harvested voltage and power have been observed. Due to the interruption of acoustic air particle motion caused by the beams, it is found that placing PVDF beams near the closed tube end is not beneficial. The total output voltage of the piezoelectric beams increases linearly as the incident sound pressure increases. This study therefore reveals that the proposed technique used to harvest sound wave energy has great potential of converting free energy into useful energy.

Keywords: acoustic energy, acoustic resonator, energy harvester, eigenfrequency, polyvinylidene fluoride (PVDF)

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Authors: Juliette MacDonald, Jun Li, Wenji Xiang, Mingwei Zhao

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Shanghai International College of Fashion and Innovation (SCF) was created as a result of a collaborative partnership agreement between the University of Edinburgh and Donghua University. The College provides two programmes: Fashion Innovation and Fashion Interior Design and the overarching curriculum has the intention of developing innovation and creativity within an international learning, teaching, knowledge exchange and research context. The research problem presented here focuses on the multi-national/cultural faculty in the team, the challenges arising from difficulties in communication and the associated limitations of management frameworks. The teaching faculty at SCF are drawn from China, Finland, Korea, Singapore and the UK with input from Flying Faculty from Fashion and Interior Design, Edinburgh College of Art (ECA), for 5 weeks each semester. Rather than fully replicating the administrative and pedagogical style of one or other of the institutions within this joint partnership the aim from the outset was to create a third way which acknowledges the quality assurance requirements of both Donghua and Edinburgh, the academic and technical needs of the students and provides relevant development and support for all the SCF-based staff and Flying Academics. It has been well acknowledged by those who are involved in teaching across cultures that there is often a culture shock associated with transnational education but that the experience of being involved in the delivery of a curriculum at a Joint Institution can also be very rewarding for staff and students. It became clear at SCF that if a third way might be achieved which encourages innovative approaches to fashion education whilst balancing the expectations of Chinese and western concepts of education and the aims of two institutions, then it was going to be necessary to construct a framework which developed close working relationships for the entire teaching team, so not only between academics and students but also between technicians and administrators at ECA and SCF. The attempts at co-construction and integration are built on the sharing of cultural and educational experiences and knowledge as well as provision of opportunities for reflection on the pedagogical purpose of the curriculum and its delivery. Methods on evaluating the effectiveness of these aims include a series of surveys and interviews and analysis of data drawn from teaching projects delivered to the students along with graduate successes from the last five years, since SCF first opened its doors. This paper will provide examples of best practice developed by SCF which have helped guide the faculty and embed common core values and aims of co-construction regulations and management, whilst building a pro-active TNE (Trans-National Education) team which enhances the learning experience for staff and students alike.

Keywords: cultural co-construction, educational team management, multi-cultural challenges, TNE integration for teaching teams

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Authors: R. S. Giraddi, C. M. Poleshi

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Organic cultivation of crops is gaining importance consumer awareness towards pesticide residue free foodstuffs is increasing globally. This is also because of high costs of synthetic fertilizers and pesticides, making the conventional farming non-remunerative. In India, organic manures (such as vermicompost) are an important input in organic agriculture.  Though vermicompost obtained through earthworm and microbe-mediated processes is known to comprise most of the crop nutrients, but they are in small amounts thus necessitating enrichment of nutrients so that crop nourishment is complete. Another characteristic of organic manures is that the pest infestations are kept under check due to induced resistance put up by the crop plants. In the present investigation, deoiled neem cake containing azadirachtin, copper ore tailings (COT), a source of micro-nutrients and microbial consortia were added for enrichment of vermicompost. Neem cake is a by-product obtained during the process of oil extraction from neem plant seeds. Three enriched vermicompost blends were prepared using vermicompost (at 70, 65 and 60%), deoiled neem cake (25, 30 and 35%), microbial consortia and COTwastes (5%). Enriched vermicompost was thoroughly mixed, moistened (25+5%), packed and incubated for 15 days at room temperature. In the crop response studies, the field trials on chili (Capsicum annum var. longum) and soybean, (Glycine max cv JS 335) were conducted during Kharif 2015 at the Main Agricultural Research Station, UAS, Dharwad-Karnataka, India. The vermicompost blend enriched with neem cake (known to possess higher amounts of nutrients) and vermicompost were applied to the crops and at two dosages and at two intervals of crop cycle (at sowing and 30 days after sowing) as per the treatment plan along with 50% recommended dose of fertilizer (RDF). 10 plants selected randomly in each plot were studied for pest density and plant damage. At maturity, crops were harvested, and the yields were recorded as per the treatments, and the data were analyzed using appropriate statistical tools and procedures. In the crops, chili and soybean, crop nourishment with neem enriched vermicompost reduced insect density and plant damage significantly compared to other treatments. These treatments registered as much yield (16.7 to 19.9 q/ha) as that realized in conventional chemical control (18.2 q/ha) in soybean, while 72 to 77 q/ha of green chili was harvested in the same treatments, being comparable to the chemical control (74 q/ha). The yield superiority of the treatments was of the order neem enriched vermicompost>conventional chemical control>neem cake>vermicompost>untreated control.  The significant features of the result are that it reduces use of inorganic manures by 50% and synthetic chemical insecticides by 100%.

Keywords: humic acid, azadirachtin, vermicompost, insect-pest

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Authors: James Rigor Camacho, Wansu Lim

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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

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Authors: Funda Erdem Şahnali, Ş. Özgür Atayılmaz, Tolga N. Aynur

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Almost all of the domestic refrigerators operate on the principle of the vapor compression refrigeration cycle and removal of heat from the refrigerator cabinets is done via one of the two methods: natural convection or forced convection. In this study, airflow and temperature distributions inside a 375L no-frost type larder cabinet, in which cooling is provided by forced convection, are evaluated both experimentally and numerically. Airflow rate, compressor capacity and temperature distribution in the cooling chamber are known to be some of the most important factors that affect the cooling performance and energy consumption of a refrigerator. The objective of this study is to evaluate the original temperature distribution in the larder cabinet, and investigate for better temperature distribution solutions throughout the refrigerator domain via system optimizations that could provide uniform temperature distribution. The flow visualization and airflow velocity measurements inside the original refrigerator are performed via Stereoscopic Particle Image Velocimetry (SPIV). In addition, airflow and temperature distributions are investigated numerically with Ansys Fluent. In order to study the heat transfer inside the aforementioned refrigerator, forced convection theories covering the following cases are applied: closed rectangular cavity representing heat transfer inside the refrigerating compartment. The cavity volume has been represented with finite volume elements and is solved computationally with appropriate momentum and energy equations (Navier-Stokes equations). The 3D model is analyzed as transient, with k-ε turbulence model and SIMPLE pressure-velocity coupling for turbulent flow situation. The results obtained with the 3D numerical simulations are in quite good agreement with the experimental airflow measurements using the SPIV technique. After Computational Fluid Dynamics (CFD) analysis of the baseline case, the effects of three parameters: compressor capacity, fan rotational speed and type of shelf (glass or wire) are studied on the energy consumption; pull down time, temperature distributions in the cabinet. For each case, energy consumption based on experimental results is calculated. After the analysis, the main effective parameters for temperature distribution inside a cabin and energy consumption based on CFD simulation are determined and simulation results are supplied for Design of Experiments (DOE) as input data for optimization. The best configuration with minimum energy consumption that provides minimum temperature difference between the shelves inside the cabinet is determined.

Keywords: air distribution, CFD, DOE, energy consumption, experimental, larder cabinet, refrigeration, uniform temperature

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Authors: Pedro G. Morouço

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One utmost challenge in Tissue Engineering is the production of 3D constructs capable of mimicking the functional hierarchy of native tissues. This is well stated for osteochondral tissue due to the complex mechanical functional unit based on the junction of articular cartilage and bone. Thus, the aim of the present study was to develop a new additive manufacturing system coupling micro-extrusion with hydrogels printing. An integrated system was developed with 2 main features: (i) the printing of up to three distinct hydrogels; (ii) in coordination with the printing of a thermoplastic structural support. The hydrogel printing module was projected with a ‘revolver-like’ system, where the hydrogel selection was made by a rotating mechanism. The hydrogel deposition was then controlled by pressured air input. The use of specific components approved for medical use was incorporated in the material dispensing system (Nordson EDF Optimum® fluid dispensing system). The thermoplastic extrusion modulus enabled the control of required extrusion temperature through electric resistances in the polymer reservoir and the extrusion system. After testing and upgrades, a hydrogel modulus with 3 syringes (3cm3 capacity each), with a pressure range of 0-2.5bar, a rotational speed of 0-5rpm, and working with needles from 200-800µm was obtained. This modulus was successfully coupled to the extrusion system that presented a temperature up to 300˚C, a pressure range of 0-12bar, and working with nozzles from 200-500µm. The applied motor could provide a velocity range 0-2000mm/min. Although, there are distinct printing requirements for hydrogels and polymers, the novel system could develop hybrid scaffolds, combining the 2 moduli. The morphological analysis showed high reliability (n=5) between the theoretical and obtained filament and pore size (350µm and 300µm vs. 342±4µm and 302±3µm, p>0.05, respectively) of the polymer; and multi-material 3D constructs were successfully obtained. Human tissues present very distinct and complex structures regarding their mechanical properties, organization, composition and dimensions. For osteochondral regenerative medicine, a multiphasic scaffold is required as subchondral bone and overlying cartilage must regenerate at the same time. Thus, a scaffold with 3 layers (bone, intermediate and cartilage parts) can be a promising approach. The developed system may give a suitable solution to construct those hybrid scaffolds with enhanced properties. The present novel system is a step-forward regarding osteochondral tissue engineering due to its ability to generate layered mechanically stable implants through the double-printing of hydrogels with thermoplastics.

Keywords: 3D bioprinting, bone regeneration, cartilage regeneration, regenerative medicine, tissue engineering

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Authors: Aziz Ikhlef

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Most of multi-slices Computed Tomography (CT) scanners are built with detectors composed of scintillator - photodiodes arrays. The photodiodes arrays are mainly based on front-illuminated technology for detectors under 64 slices and on back-illuminated photodiode for systems of 64 slices or more. The designs based on back-illuminated photodiodes were being investigated for CT machines to overcome the challenge of the higher number of runs and connection required in front-illuminated diodes. In backlit diodes, the electronic noise has already been improved because of the reduction of the load capacitance due to the routing reduction. This is translated by a better image quality in low signal application, improving low dose imaging in large patient population. With the fast development of multi-detector-rows CT (MDCT) scanners and the increasing number of examinations, the clinical community has raised significant concerns on radiation dose received by the patient in both medical and regulatory community. In order to reduce individual exposure and in response to the recommendations of the International Commission on Radiological Protection (ICRP) which suggests that all exposures should be kept as low as reasonably achievable (ALARA), every manufacturer is trying to implement strategies and solutions to optimize dose efficiency and image quality based on x-ray emission and scanning parameters. The added demands on the CT detector performance also comes from the increased utilization of spectral CT or dual-energy CT in which projection data of two different tube potentials are collected. One of the approaches utilizes a technology called fast-kVp switching in which the tube voltage is switched between 80 kVp and 140 kVp in fraction of a millisecond. To reduce the cross-contamination of signals, the scintillator based detector temporal response has to be extremely fast to minimize the residual signal from previous samples. In addition, this paper will present an overview of detector technologies and image chain improvement which have been investigated in the last few years to improve the signal-noise ratio and the dose efficiency CT scanners in regular examinations and in energy discrimination techniques. Several parameters of the image chain in general and in the detector technology contribute in the optimization of the final image quality. We will go through the properties of the post-patient collimation to improve the scatter-to-primary ratio, the scintillator material properties such as light output, afterglow, primary speed, crosstalk to improve the spectral imaging, the photodiode design characteristics and the data acquisition system (DAS) to optimize for crosstalk, noise and temporal/spatial resolution.

Keywords: computed tomography, X-ray detector, medical imaging, image quality, artifacts

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Authors: Afifa Mohammed, Gloria Pignatta, Mattheos Santamouris, Evangelia Topriska

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Climate change is one of the global challenges that is exacerbated by the rapid growth of urbanizations. Urban Heat Island (UHI) phenomenon can be considered as an effect of the urbanization and it is responsible together with the Climate change of the overheating of urban cities and downtowns. The purpose of this paper is to quantify and perform analysis of UHI Intensity in Dubai, United Arab Emirates (UAE), through checking the relationship between the UHI and different meteorological parameters (e.g., temperature, winds speed, winds direction). Climate data were collected from three meteorological stations in Dubai (e.g., Dubai Airport - Station 1, Al-Maktoum Airport - Station 2 and Saih Al-Salem - Station 3) for a period of five years (e.g., 2014 – 2018) based upon hourly rates, and following clustering technique as one of the methodology tools of measurements. The collected data of each station were divided into six clusters upon the winds directions, either from the seaside or from the desert side, or from the coastal side which is in between both aforementioned winds sources, to investigate the relationship between temperature degrees and winds speed values through UHI measurements for Dubai Airport - Station 1 compared with the same of Al-Maktoum Airport - Station 2. In this case, the UHI value is determined by the temperature difference of both stations, where Station 1 is considered as located in an urban area and Station 2 is considered as located in a suburban area. The same UHI calculations has been applied for Al-Maktoum Airport - Station 2 and Saih Salem - Station 3 where Station 2 is considered as located in an urban area and Station 3 is considered as located in a suburban area. The performed analysis aims to investigate the relation between the two environmental parameters (e.g., Temperature and Winds Speed) and the Urban Heat Island (UHI) intensity when the wind comes from the seaside, from the desert, and the remaining directions. The analysis shows that the correlation between the temperatures with both UHI intensity (e.g., temperature difference between Dubai Airport - Station 1 and Saih Al-Salem - Station 3 and between Al-Maktoum Airport - Station 2 and Saih Al-Salem - Station 3 (through station 1 & 2) is strong and has a negative relationship when the wind is coming from the seaside comparing between the two stations 1 and 2, while the relationship is almost zero (no relation) when the wind is coming from the desert side. The relation is independent between the two parameters, e.g., temperature and UHI, on Station 2, during the same procedures, the correlation between the urban heat island UHI phenomenon and wind speed is weak for both stations when wind direction is coming from the seaside comparing the station 1 and 2, while it was found that there’s no relationship between urban heat island phenomenon and wind speed when wind direction is coming from desert side. The conclusion could be summarized saying that the wind coming from the seaside or from the desert side have a different effect on UHI, which is strongly affected by meteorological parameters. The output of this study will enable more determination of UHI phenomenon under desert climate, which will help to inform about the UHI phenomenon and intensity and extract recommendations in two main categories such as planning of new cities and designing of buildings.

Keywords: meteorological data, subtropical desert climate, urban climate, urban heat island (UHI)

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Authors: Marcel Heimar Ribeiro Utiyama, Fernanda Caveiro Correia, Dario Henrique Alliprandini

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The importance of the correct allocation of improvement programs is of growing interest in recent years. Due to their limited resources, companies must ensure that their financial resources are directed to the correct workstations in order to be the most effective and survive facing the strong competition. However, to our best knowledge, the literature about allocation of improvement programs does not analyze in depth this problem when the flow shop process has two capacity constrained resources. This is a research gap which is deeply studied in this work. The purpose of this work is to identify the best strategy to allocate improvement programs in a flow shop with two capacity constrained resources. Data were collected from a flow shop process with seven workstations in an industrial control and automation company, which process 13.690 units on average per month. The data were used to conduct a simulation with the System Dynamics-Factory Physics model. The main variables considered, due to their importance on lead time reduction, were the mean time between failures and the mean time to repair. The lead time reduction was the output measure of the simulations. Ten different strategies were created: (i) focused time to repair improvement, (ii) focused time between failures improvement, (iii) distributed time to repair improvement, (iv) distributed time between failures improvement, (v) focused time to repair and time between failures improvement, (vi) distributed time to repair and between failures improvement, (vii) hybrid time to repair improvement, (viii) hybrid time between failures improvements, (ix) time to repair improvement strategy towards the two capacity constrained resources, (x) time between failures improvement strategy towards the two capacity constrained resources. The ten strategies tested are variations of the three main strategies for improvement programs named focused, distributed and hybrid. Several comparisons among the effect of the ten strategies in lead time reduction were performed. The results indicated that for the flow shop analyzed, the focused strategies delivered the best results. When it is not possible to perform a large investment on the capacity constrained resources, companies should use hybrid approaches. An important contribution to the academy is the hybrid approach, which proposes a new way to direct the efforts of improvements. In addition, the study in a flow shop with two strong capacity constrained resources (more than 95% of utilization) is an important contribution to the literature. Another important contribution is the problem of allocation with two CCRs and the possibility of having floating capacity constrained resources. The results provided the best improvement strategies considering the different strategies of allocation of improvement programs and different positions of the capacity constrained resources. Finally, it is possible to state that both strategies, hybrid time to repair improvement and hybrid time between failures improvement, delivered best results compared to the respective distributed strategies. The main limitations of this study are mainly regarding the flow shop analyzed. Future work can further investigate different flow shop configurations like a varying number of workstations, different number of products or even different positions of the two capacity constrained resources.

Keywords: allocation of improvement programs, capacity constrained resource, hybrid strategy, lead time, mean time to repair, mean time between failures

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Authors: E. S. Martens, E. E. Onwuliri

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Over the past three decades, Nigeria’s film industry has become a global powerhouse, releasing hundreds of films annually and even monthly. Nollywood, a portmanteau of Nigeria and Hollywood as well as Bollywood that was coined by New York Times journalist Norimitsu Onishi in 2002, came to mark the plenitude of filmmaking happening in Lagos from the early 1990s onwards. Following the success of the 1992 straight-to-VHS film Living in Bondage, the Nigerian film industry experienced a popular home video boom that gained a huge following in Nigeria, across Africa, and among the global African diaspora. In fact, with an estimated worth of $6.4 billion as of 2021, Nollywood is nowadays considered the world’s second-largest film industry and even the largest in terms of output and popularity. Producing about 2,500 films annually and reaching an estimated audience of over 200 million people worldwide, Nollywood has not only seemingly surpassed Hollywood but also Bollywood with regard to production and consumption size. Due to its commercial success and cultural impact from the early 2010s, Nollywood has often been heralded as a potential driver of Africa’s tourism industry. In its 2012 Global Trends Report, the World Travel Market forecasted an increase in GDP in Africa due to tourism in Nollywood filming locations. Additionally, it was expected that the rising popularity of Nollywood would significantly contribute to growth in the leisure sector, drawing both film enthusiasts and business travelers intrigued by the expanding significance of the Nigerian film industry. Still, despite much talk about the potential impact of Nollywood on Nigerian tourism in the past 10 years or so, relatively little is known about Nollywood’s association with film tourism and the existing connections between Nigeria’s film and tourism industries more generally. Already well over a decade ago, it was observed that there is still a lack of research examining the extent to which film tourism related to Nollywood in Africa has been generated – and to date, this is still largely the case. This paper, then, seeks to discuss the reported connections between Nollywood and tourism and to review the efforts and opportunities related to Nollywood film tourism as suggested in Nigeria’s public domain. Based on a content analysis of over 50 newspaper articles and other online available materials, such as websites, blogs and forums, this paper explores the practices and discourses surrounding Nollywood connections with tourism in Nigeria and across Africa over the past ten years. The analysis shows that, despite these high expectations, film tourism related to Nollywood has remained limited. Despite growing government attention and support to Nollywood and its potential for tourism, most state initiatives in this direction have not (yet) materialize – and it very much remains to be seen to what extent ‘Destination Nollywood’ is really able to come to fruition as long as the structural issues underlying the development of Nigerian film (and) tourism are not sufficiently addressed.

Keywords: film tourism, Nigerian cinema, Nollywood, tourist destination

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Authors: Byron Baron

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Malta is a Mediterranean archipelago presenting a combination of environmental conditions which are less suitable for agriculture. This has resulted in a heavy dependence on agricultural chemicals, as well as over-extraction of groundwater, compounded by concomitant destruction of natural habitat surrounding the land areas used for agriculture. Such prolonged intensive land use has resulted in even greater degradation of Maltese soils. This study was thus designed with the goal of assessing the viability of implementing a sustainable agricultural system based on permaculture practices compared to the traditional local practices applied for intensive farming. The permaculture model was implemented over a period of two years for a number of locally-grown staple crops. The tangible targets included improved soil health, reduced water consumption, increased reliance on renewable energy, increased wild plant and insect diversity, and sustained crop yield. To achieve this in the permaculture test area, numerous practices were introduced. In line with permaculture principles land, tillage was reduced, only natural fertilisers were used, no herbicides or pesticides were used, irrigation was linked to a desalination system with sensors for monitoring soil parameters, mulching was practiced, and a photovoltaic system was installed. Furthermore, areas for wild plants were increased and controlled only by trimming, not mowing. A variety of environmental parameters were measured at regular intervals as well as crop yield (in kilos of produce) in order to quantify if any improvements in crop output and environmental conditions were obtained. The results obtained show a very slight improvement in overall soil health due to the brevity of the test period. Water consumption was reduced by over 50% with no apparent losses or ill effects on the crops. Renewable energy was sufficient to provide all electric power on-site, so apart from the initial investment costs, there were no limitations. Moreover, surrounding the commercial crops with borders of wild plants whilst only taking up less than 15% of the total land area assisted pollination, increased animal visitors, and did not give rise to any pest infestations. The conclusion from this study was that whilst results are promising, more detailed and long-term studies are required to understand the full extent of the implications brought about by such a transition, which hints towards the untapped potential of investing in the available resources on the island with the goal of improving the balance between economic prosperity and ecological sustainability.

Keywords: agronomic measures, ecological amplification, sustainability, permaculture

Procedia PDF Downloads 82

Authors: Erik Vassøy Olsen, Hirpa G. Lemu

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Inspired by the Formula-1 competition, IMechE (Institute of Mechanical Engineers) and Formula SAE (Society of Mechanical Engineers) organize annual competitions for University and College students worldwide to compete with a single-seat race car they have designed and built. The design of the chassis or the frame is a key component of the competition because the weight and stiffness properties are directly related with the performance of the car and the safety of the driver. In addition, a reduced weight of the chassis has a direct influence on the design of other components in the car. Among others, it improves the power to weight ratio and the aerodynamic performance. As the power output of the engine or the battery installed in the car is limited to 80 kW, increasing the power to weight ratio demands reduction of the weight of the chassis, which represents the major part of the weight of the car. In order to reduce the weight of the car, ION Racing team from the University of Stavanger, Norway, opted for a monocoque design. To ensure fulfilment of the above-mentioned requirements of the chassis, the monocoque design should provide sufficient torsional stiffness and absorb the impact energy in case of a possible collision. The study reported in this article is based on the requirements for Formula Student competition. As part of this study, diverse mechanical tests were conducted to determine the mechanical properties and performances of the monocoque design. Upon a comprehensive theoretical study of the mechanical properties of sandwich composite materials and the requirements of monocoque design in the competition rules, diverse tests were conducted including 3-point bending test, perimeter shear test and test for absorbed energy. The test panels were homemade and prepared with an equivalent size of the side impact zone of the monocoque, i.e. 275 mm x 500 mm so that the obtained results from the tests can be representative. Different layups of the test panels with identical core material and the same number of layers of carbon fibre were tested and compared. Influence of the core material thickness was also studied. Furthermore, analytical calculations and numerical analysis were conducted to check compliance to the stated rules for Structural Equivalency with steel grade SAE/AISI 1010. The test results were also compared with calculated results with respect to bending and torsional stiffness, energy absorption, buckling, etc. The obtained results demonstrate that the material composition and strength of the composite material selected for the monocoque design has equivalent structural properties as a welded frame and thus comply with the competition requirements. The developed analytical calculation algorithms and relations will be useful for future monocoque designs with different lay-ups and compositions.

Keywords: composite material, Formula student, ION racing, monocoque design, structural equivalence

Procedia PDF Downloads 483

Authors: Gabriel Ugalahi, Dominic S. Nyitamen

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This project seeks to improve Wi-Fi reception by utilizing the properties of directional microstrip patch antennae. Where there is a dense population of Wi-Fi signal, several signal sources transmitting on the same frequency band and indeed channel constitutes interference to each other. The time it takes for request to be received, resolved and response given between a user and the resource provider is increased considerably. By deploying a directional patch antenna with a narrow bandwidth, the range of frequency received is reduced and should help in limiting the reception of signal from unwanted sources. A rectangular microstrip patch antenna (RMPA) is designed to operate at the Industrial Scientific and Medical (ISM) band (2.4GHz) commonly used in Wi-Fi network deployment. The dimensions of the antenna are calculated and these dimensions are used to generate a model on Advanced Design System (ADS), a microwave simulator. Simulation results are then analyzed and necessary optimization is carried out to further enhance the radiation quality so as to achieve desired results. Impedance matching at 50Ω is also obtained by using the inset feed method. Final antenna dimensions obtained after simulation and optimization are then used to implement practical construction on an FR-4 double sided copper clad printed circuit board (PCB) through a chemical etching process using ferric chloride (Fe2Cl). Simulation results show an RMPA operating at a centre frequency of 2.4GHz with a bandwidth of 40MHz. A voltage standing wave ratio (VSWR) of 1.0725 is recorded on a return loss of -29.112dB at input port showing an appreciable match in impedance to a source of 50Ω. In addition, a gain of 3.23dBi and directivity of 6.4dBi is observed during far-field analysis. On deployment, signal reception from wireless devices is improved due to antenna gain. A test source with a received signal strength indication (RSSI) of -80dBm without antenna installed on the receiver was improved to an RSSI of -61dBm. In addition, the directional radiation property of the RMPA prioritizes signals by pointing in the direction of a preferred signal source thus, reducing interference from undesired signal sources. This was observed during testing as rotation of the antenna on its axis resulted to the gain of signal in-front of the patch and fading of signals away from the front.

Keywords: advanced design system (ADS), inset feed, received signal strength indicator (RSSI), rectangular microstrip patch antenna (RMPA), voltage standing wave ratio (VSWR), wireless fidelity (Wi-Fi)

Procedia PDF Downloads 197

Authors: M. Beusink, E. W. C. Coenen

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The increased application of novel structural materials, such as high grade asphalt, concrete and laminated composites, has sparked the need for a better understanding of the often complex, non-linear mechanical behavior of such materials. The effective macroscopic mechanical response is generally dependent on the applied load path. Moreover, it is also significantly influenced by the microstructure of the material, e.g. embedded fibers, voids and/or grain morphology. At present, multiscale techniques are widely adopted to assess micro-macro interactions in a numerically efficient way. Computational homogenization techniques have been successfully applied over a wide range of engineering cases, e.g. cases involving first order and second order continua, thin shells and cohesive zone models. Most of these homogenization methods rely on Representative Volume Elements (RVE), which model the relevant microstructural details in a confined volume. Imposed through kinematical constraints or boundary conditions, a RVE can be subjected to a microscopic load sequence. This provides the RVE's effective stress-strain response, which can serve as constitutive input for macroscale analyses. Simultaneously, such a study of a RVE gives insight into fine scale phenomena such as microstructural damage and its evolution. It has been reported by several authors that the type of boundary conditions applied to the RVE affect the resulting homogenized stress-strain response. As a consequence, dedicated boundary conditions have been proposed to appropriately deal with this concern. For the specific case of a planar assumption for the analyzed structure, e.g. plane strain, axisymmetric or plane stress, this assumption needs to be addressed consistently in all considered scales. Although in many multiscale studies a planar condition has been employed, the related impact on the multiscale solution has not been explicitly investigated. This work therefore focuses on the influence of the planar assumption for multiscale modeling. In particular the plane stress case is highlighted, by proposing three different implementation strategies which are compatible with a first-order computational homogenization framework. The first method consists of applying classical plane stress theory at the microscale, whereas with the second method a generalized plane stress condition is assumed at the RVE level. For the third method, the plane stress condition is applied at the macroscale by requiring that the resulting macroscopic out-of-plane forces are equal to zero. These strategies are assessed through a numerical study of a thin walled structure and the resulting effective macroscale stress-strain response is compared. It is shown that there is a clear influence of the length scale at which the planar condition is applied.

Keywords: first-order computational homogenization, planar analysis, multiscale, microstrucutures

Procedia PDF Downloads 209

Authors: Mahmood Iqbal, Khalid Nawab, Tachibana Satoshi

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Farmer Field School (FFS) is constantly aims to assist farmers to determine and learn about field ecology and integrated crop management. The study was conducted to examine the change in productivity of tomato crop in the study area; to determine increase in per acre yield of the crop, and find out reduction in per acre input cost. A study of tomato crop was conducted in ten villages namely Jabban, Bijligar Colony, Palonow, Heroshah, Zara Maira, Deghar Ghar, Sidra Jour, Anar Thangi, Miangano Korona and Wartair of district Malakand. From each village 15 respondents were selected randomly on the basis of identical allocation making sample size of 150 respondents. The research was based on primary as well as secondary data. Primary data was collected from farmers while secondary data were taken from Agriculture Extension Department Dargai, District Malakand. Interview schedule was planned and each farmer was interviewed personally. The study was based on comparison of cost, yield and income of tomato before and after FFS. Paired t-test and Statistical Package for Social Sciences (SPSS) was used for analysis; outcome of the study show that integrated pest management project has brought a positive change in the attitude of farmers of the project area through FFS approach. In district Malakand 66.0% of the respondents were between the age group of 31-50 years, 11.3% of respondents had primary level of education, 12.7% of middle level, 28.7% metric level, 3.3% of intermediate level and 2.0% of graduate level of education while 42.0% of respondents were illiterate and have no education. Average land holding size of farmers was 6.47 acres, cost of seed, crop protection from insect pest and crop protection from diseases was reduced by Rs. 210.67, Rs. 2584.43 and Rs. 3044.16 respectively, the cost of fertilizers and cost of farm yard manure was increased by Rs.1548.87 and Rs. 1151.40 respectively while tomato yield was increased by 1585.03 kg/acre from 7663.87 to 9248.90 kg/acre. The role of FFS initiate by integrated pest management project through department of agriculture extension for the development of agriculture was worth mentioning. It has brought enhancement in crop yield of tomato and their income through FFS approach. On the basis of results of the research studies, integrated pest management project should spread their developmental activities for maximum participation of the complete rural masses through participatory FFS approach.

Keywords: agriculture, Farmers field schools, extension education, tomato

Procedia PDF Downloads 589

Authors: Malek Miladi, Miguel Vegara, Maria Perez-Infantes, Khaled Mohamed Ramadan, Antonio Ruiz-Canales, Damaris Nunez-Gomez

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Coffee is the second consumed commodity worldwide, yet it also generates colossal waste. Proper management of coffee waste is proposed by converting them into products with higher added value to achieve sustainability of the economic and ecological footprint and protect the environment. Based on this, a study looking at the recovery of coffee waste is becoming more relevant in recent decades. Spent coffee grounds (SCG's) resulted from brewing coffee represents the major waste produced among all coffee industry. The fact that SCGs has no economic value be abundant in nature and industry, do not compete with agriculture and especially its high oil content (between 7-15% from its total dry matter weight depending on the coffee varieties, Arabica or Robusta), encourages its use as a sustainable feedstock for bio-oil production. The bio-oil extraction is a crucial step towards biodiesel production by the transesterification process. However, conventional methods used for oil extraction are not recommended due to their high consumption of energy, time, and generation of toxic volatile organic solvents. Thus, finding a sustainable, economical, and efficient extraction technique is crucial to scale up the process and to ensure more environment-friendly production. Under this perspective, the aim of this work was the statistical study to know an efficient strategy for oil extraction by n-hexane using indirect sonication. The coffee waste mixed Arabica and Robusta, which was used in this work. The temperature effect, sonication time, and solvent-to-solid ratio on the oil yield were statistically investigated as dependent variables by Central Composite Rotatable Design (CCRD) 23. The results were analyzed using STATISTICA 7 StatSoft software. The CCRD showed the significance of all the variables tested (P < 0.05) on the process output. The validation of the model by analysis of variance (ANOVA) showed good adjustment for the results obtained for a 95% confidence interval, and also, the predicted values graph vs. experimental values confirmed the satisfactory correlation between the model results. Besides, the identification of the optimum experimental conditions was based on the study of the surface response graphs (2-D and 3-D) and the critical statistical values. Based on the CCDR results, 29 ºC, 56.6 min, and solvent-to-solid ratio 16 were the better experimental conditions defined statistically for coffee waste oil extraction using n-hexane as solvent. In these conditions, the oil yield was >9% in all cases. The results confirmed the efficiency of using an ultrasound bath in extracting oil as a more economical, green, and efficient way when compared to the Soxhlet method.

Keywords: coffee waste, optimization, oil yield, statistical planning

Procedia PDF Downloads 96

Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

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Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, student engagement

Procedia PDF Downloads 73

Authors: Palak Sadhwani, Susie Pryor

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This paper investigates interprofessional collaboration (IPC) in the context of entrepreneurship education. Collaboration has been found to enhance problem solving, leverage expertise, improve resource allocation, and create organizational efficiencies. However, research suggests that successful collaboration is hampered by individual and organizational characteristics. IPC occurs when two or more professionals work together to solve a problem or achieve a common objective. The necessity for this form of collaboration is particularly prevalent in cross-disciplinary fields. In this study, we utilize social exchange theory (SET) to examine IPC in the context of an entrepreneurship living learning community (LLC) at a large university in the Western United States. Specifically, we explore these research questions: How are rules or norms established that govern the collaboration process? How are resources valued and distributed? How are relationships developed and managed among and between parties? LLCs are defined as groups of students who live together in on-campus housing and share similar academic or special interests. In 2007, the Association of American Colleges and Universities named living communities a high impact practice (HIP) because of their capacity to enhance and give coherence to undergraduate education. The entrepreneurship LLC in this study was designed to offer first year college students the opportunity to live and learn with like-minded students from diverse backgrounds. While the university offers other LLC environments, the target residents for this LLC are less easily identified and are less apparently homogenous than residents of other LLCs on campus (e.g., Black Scholars, LatinX, Women in Science and Education), creating unique challenges. The LLC is a collaboration between the university’s College of Business & Public Administration and the Department of Housing and Residential Education (DHRE). Both parties are contributing staff, technology, living and learning spaces, and other student resources. This paper reports the results an ethnographic case study which chronicles the start-up challenges associated with the co-creation of the LLC. SET provides a general framework for examining how resources are valued and exchanged. In this study, SET offers insights into the processes through which parties negotiate tensions resulting from approaching this shared project from very different perspectives and cultures in a novel project environment. These tensions occur due to a variety of factors, including team formation and management, allocation of resources, and differing output expectations. The results are useful to both scholars and practitioners of entrepreneurship education and organizational management. They suggest probably points of conflict and potential paths towards reconciliation.

Keywords: case study, ethnography, interprofessional collaboration, social exchange theory

Procedia PDF Downloads 121

Authors: Aysen Celen Ozturk, Hatice Dulger

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University may be defined as a teaching institution consisting of faculties, institutes, colleges, and units that have undergraduate and graduate education, scientific research and publications. It has scientific autonomy and public legal personality. Today, universities are not only the institutions in which students and lecturers experience education, training and scientific work. They also offer social, cultural and artistic activities that strengthen the link with the city. This also incorporates all city users into the campus borders. Thus, universities contribute to social and individual development of the country by providing science, art, socio-cultural development, communication and socialization with people of different cultural and social backgrounds. Moreover, universities provide an active social life, where the young population is the majority. This enables the sense of belonging to the users to develop, to increase the interaction between academicians and students, and to increase the learning / producing community by continuing academic sharing environments outside the classrooms. For this reason, besides academic spaces in university campuses, the users also need closed and open spaces where they can socialize, spend time together and relax. Public open spaces are the most important social spaces that individuals meet, express themselves and share. Individuals belonging to different socio-cultural structures and ethnic groups maintain their social experiences with the physical environment they are in, the outdoors, and their actions and sharing in these spaces. While university campuses are being designed for their individual and social development roles, user needs must be determined correctly and design should be realized in this direction. While considering that requirements may change over time, user satisfaction should be questioned at certain periods and new arrangements should be made in existing applications in the direction of current demands. This study aims to determine the user requirements through the case of Eskişehir Osmangazi University, Meşelik Campus / Turkey. Post Occupancy Evaluation (POE) questionnaire, cognitive mapping and deep interview methods are used in the research process. All these methods show that the students, academicians and other officials in the Meşelik Campus of Eskişehir Osmangazi University find way finding elements insufficient and are in need of efficient landscape design and social spaces. This study is important in terms of determining the needs of the users as a design input. This will help improving the quality of common space in Eskişehir Osmangazi University and in other similar universities.

Keywords: university campuses, public open space, user requirement, post occupancy evaluation

Procedia PDF Downloads 225

Authors: Amin Salighehdar, Ziwen Ye, Mingzhe Liu, Ionut Florescu, Alan F. Blumberg

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Storm surge is an abnormal water level caused by a storm. Accurate prediction of a storm surge is a challenging problem. Researchers developed various ensemble modeling techniques to combine several individual forecasts to produce an overall presumably better forecast. There exist some simple ensemble modeling techniques in literature. For instance, Model Output Statistics (MOS), and running mean-bias removal are widely used techniques in storm surge prediction domain. However, these methods have some drawbacks. For instance, MOS is based on multiple linear regression and it needs a long period of training data. To overcome the shortcomings of these simple methods, researchers propose some advanced methods. For instance, ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast. This application creates a better forecast of sea level using a combination of several instances of the Bayesian Model Averaging (BMA). An ensemble dressing method is based on identifying best member forecast and using it for prediction. Our contribution in this paper can be summarized as follows. First, we investigate whether the ensemble models perform better than any single forecast. Therefore, we need to identify the single best forecast. We present a methodology based on a simple Bayesian selection method to select the best single forecast. Second, we present several new and simple ways to construct ensemble models. We use correlation and standard deviation as weights in combining different forecast models. Third, we use these ensembles and compare with several existing models in literature to forecast storm surge level. We then investigate whether developing a complex ensemble model is indeed needed. To achieve this goal, we use a simple average (one of the simplest and widely used ensemble model) as benchmark. Predicting the peak level of Surge during a storm as well as the precise time at which this peak level takes place is crucial, thus we develop a statistical platform to compare the performance of various ensemble methods. This statistical analysis is based on root mean square error of the ensemble forecast during the testing period and on the magnitude and timing of the forecasted peak surge compared to the actual time and peak. In this work, we analyze four hurricanes: hurricanes Irene and Lee in 2011, hurricane Sandy in 2012, and hurricane Joaquin in 2015. Since hurricane Irene developed at the end of August 2011 and hurricane Lee started just after Irene at the beginning of September 2011, in this study we consider them as a single contiguous hurricane event. The data set used for this study is generated by the New York Harbor Observing and Prediction System (NYHOPS). We find that even the simplest possible way of creating an ensemble produces results superior to any single forecast. We also show that the ensemble models we propose generally have better performance compared to the simple average ensemble technique.

Keywords: Bayesian learning, ensemble model, statistical analysis, storm surge prediction

Procedia PDF Downloads 290

Authors: Hossein Havaeji, Tony Wong, Thien-My Dao

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1. Research Problems and Research Objectives: Blockchain Technology-enabled Supply Chain System (BT-enabled SCS) is the system using BT to drive SCS transparency, security, durability, and process integrity as SCS data is not always visible, available, or trusted. The costs of operating BT in the SCS are a common problem in several organizations. The costs must be estimated as they can impact existing cost control strategies. To account for system and deployment costs, it is necessary to overcome the following hurdle. The problem is that the costs of developing and running a BT in SCS are not yet clear in most cases. Many industries aiming to use BT have special attention to the importance of BT installation cost which has a direct impact on the total costs of SCS. Predicting BT installation cost in SCS may help managers decide whether BT is to be an economic advantage. The purpose of the research is to identify some main BT installation cost components in SCS needed for deeper cost analysis. We then identify and categorize the main groups of cost components in more detail to utilize them in the prediction process. The second objective is to determine the suitable Supervised Learning technique in order to predict the costs of developing and running BT in SCS in a particular case study. The last aim is to investigate how the running BT cost can be involved in the total cost of SCS. 2. Work Performed: Applied successfully in various fields, Supervised Learning is a method to set the data frame, treat the data, and train/practice the method sort. It is a learning model directed to make predictions of an outcome measurement based on a set of unforeseen input data. The following steps must be conducted to search for the objectives of our subject. The first step is to make a literature review to identify the different cost components of BT installation in SCS. Based on the literature review, we should choose some Supervised Learning methods which are suitable for BT installation cost prediction in SCS. According to the literature review, some Supervised Learning algorithms which provide us with a powerful tool to classify BT installation components and predict BT installation cost are the Support Vector Regression (SVR) algorithm, Back Propagation (BP) neural network, and Artificial Neural Network (ANN). Choosing a case study to feed data into the models comes into the third step. Finally, we will propose the best predictive performance to find the minimum BT installation costs in SCS. 3. Expected Results and Conclusion: This study tends to propose a cost prediction of BT installation in SCS with the help of Supervised Learning algorithms. At first attempt, we will select a case study in the field of BT-enabled SCS, and then use some Supervised Learning algorithms to predict BT installation cost in SCS. We continue to find the best predictive performance for developing and running BT in SCS. Finally, the paper will be presented at the conference.

Keywords: blockchain technology, blockchain technology-enabled supply chain system, installation cost, supervised learning

Procedia PDF Downloads 103

Authors: Mehran Nozari-Asbemarz, Italo Pisano, Simin Arshi, Edmond Magner, James J. Leahy

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Integrating electrolytic synthesis with renewable energy makes it feasible to address urgent environmental and energy challenges. Conventional water electrolyzers concurrently produce H₂ and O₂, demanding additional procedures in gas separation to prevent contamination of H₂ with O₂. Moreover, the oxygen evolution reaction (OER), which is sluggish and has a low overall energy conversion efficiency, does not deliver a significant value product on the electrode surface. Compared to conventional water electrolysis, integrating electrolytic hydrogen generation from water with thermodynamically more advantageous aqueous organic oxidation processes can increase energy conversion efficiency and create value-added compounds instead of oxygen at the anode. One strategy is to use renewable and sustainable carbon sources from biomass, which has a large annual production capacity and presents a significant opportunity to supplement carbon sourced from fossil fuels. Numerous catalytic techniques have been researched in order to utilize biomass economically. Because of its safe operating conditions, excellent energy efficiency, and reasonable control over production rate and selectivity using electrochemical parameters, electrocatalytic upgrading stands out as an appealing choice among the numerous biomass refinery technologies. Therefore, we propose a broad framework for coupling H2 generation from water splitting with oxidative biomass upgrading processes. Four representative biomass targets were considered for oxidative upgrading that used a hierarchically porous CoFe-MOF/LDH @ Graphite Paper bifunctional electrocatalyst, including glucose, ethanol, benzyl, furfural, and 5-hydroxymethylfurfural (HMF). The potential required to support 50 mA cm-2 is considerably lower than (~ 380 mV) the potential for OER. All four compounds can be oxidized to yield liquid byproducts with economic benefit. The electrocatalytic oxidation of glucose to the value-added products, gluconic acid, glucuronic acid, and glucaric acid, was examined in detail. The cell potential for combined H₂ production and glucose oxidation was substantially lower than for water splitting (1.44 V(RHE) vs. 1.82 V(RHE) for 50 mA cm-2). In contrast, the oxidation byproduct at the anode was significantly more valuable than O₂, taking advantage of the more favorable glucose oxidation in comparison to the OER. Overall, such a combination of HER and oxidative biomass valorization using electrocatalysts prevents the production of potentially explosive H₂/O₂mixtures and produces high-value products at both electrodes with lower voltage input, thereby increasing the efficiency and activity of electrocatalytic conversion.

Keywords: biomass, electrocatalytic, glucose oxidation, hydrogen evolution

Procedia PDF Downloads 76

Authors: Andi Setiawan, Annisa Ulfah Pristya

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Indonesian rubber plant area reached 2.9 million hectares with productivity reached 1.38 million. High rubber productivity is directly proportional to the amount of waste produced rubber processing industry. Rubber industry would produce a negative impact on the rubber industry in the form of environmental pollution caused by waste that has not been treated optimally. Rubber industrial wastewater containing high-nitrogen compounds (nitrate and ammonia) and phosphate compounds which cause water pollution and odor problems due to the high ammonia content. On the other hand, demand for NPK fertilizers in Indonesia continues to increase from year to year and in need of ammonia and phosphate as raw material. Based on domestic demand, it takes a year to 400,000 tons of ammonia and Indonesia imports 200,000 tons of ammonia per year valued at IDR 4.2 trillion. As well, the lack of phosphoric acid to be imported from Jordan, Morocco, South Africa, the Philippines, and India as many as 225 thousand tons per year. During this time, the process of wastewater treatment is generally done with a rubber on the tank to contain the waste and then precipitated, filtered and the rest released into the environment. However, this method is inefficient and thus require high energy costs because through many stages before producing clean water that can be discharged into the river. On the other hand, Indonesia has the potential of pineapple fruit can be harvested throughout the year in all of Indonesia. In 2010, production reached 1,406,445 tons of pineapple in Indonesia or about 9.36 percent of the total fruit production in Indonesia. Increased productivity is directly proportional to the amount of pineapple waste pineapple leaves are kept continuous and usually just dumped in the ground or disposed of with other waste at the final disposal. Through Eco-Nanofiltration Membrane-Based Fiber Pineapple leaves Waste so that environmental problems can be solved efficiently. Nanofiltration is a process that uses pressure as a driving force that can be either convection or diffusion of each molecule. Nanofiltration membranes that can split water to nano size so as to separate the waste processed residual economic value that N and P were higher as a raw material for the manufacture of NPK fertilizer to overcome the crisis in Indonesia. The raw materials were used to manufacture Eco-Nanofiltration Membrane is cellulose from pineapple fiber which processed into cellulose acetate which is biodegradable and only requires a change of the membrane every 6 months. Expected output target is Green eco-technology so with nanofiltration membranes not only treat waste rubber industry in an effective, efficient and environmentally friendly but also lowers the cost of waste treatment compared to conventional methods.

Keywords: biodegradable, cellulose diacetate, fertilizers, pineapple, rubber

Procedia PDF Downloads 424

Authors: Martin Grootveld, Benita Percival, Sarah Moumtaz, Kerry L. Grootveld

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Objectives/Hypotheses: The adverse health effect potential of dietary lipid oxidation products (LOPs) has evoked much clinical interest. Therefore, we employed a ¹H NMR-linked Principal Component Regression (PCR) chemometrics modelling strategy to explore relationships between data matrices comprising (1) aldehydic LOP concentrations generated in culinary oils/fats when exposed to laboratory-simulated shallow frying practices, and (2) the prior saturated (SFA), monounsaturated (MUFA) and polyunsaturated fatty acid (PUFA) contents of such frying media (FM), together with their heating time-points at a standard frying temperature (180 ^oC). Methods: Corn, sunflower, extra virgin olive, rapeseed, linseed, canola, coconut and MUFA-rich algae frying oils, together with butter and lard, were heated according to laboratory-simulated shallow-frying episodes at 180 ^oC, and FM samples were collected at time-points of 0, 5, 10, 20, 30, 60, and 90 min. (n = 6 replicates per sample). Aldehydes were determined by ¹H NMR analysis (Bruker AV 400 MHz spectrometer). The first (dependent output variable) PCR data matrix comprised aldehyde concentration scores vectors (PC1* and PC2*), whilst the second (predictor) one incorporated those from the fatty acid content/heating time variables (PC1-PC4) and their first-order interactions. Results: Structurally complex trans,trans- and cis,trans-alka-2,4-dienals, 4,5-epxy-trans-2-alkenals and 4-hydroxy-/4-hydroperoxy-trans-2-alkenals (group I aldehydes predominantly arising from PUFA peroxidation) strongly and positively loaded on PC1*, whereas n-alkanals and trans-2-alkenals (group II aldehydes derived from both MUFA and PUFA hydroperoxides) strongly and positively loaded on PC2*. PCR analysis of these scores vectors (SVs) demonstrated that PCs 1 (positively-loaded linoleoylglycerols and [linoleoylglycerol]:[SFA] content ratio), 2 (positively-loaded oleoylglycerols and negatively-loaded SFAs), 3 (positively-loaded linolenoylglycerols and [PUFA]:[SFA] content ratios), and 4 (exclusively orthogonal sampling time-points) all powerfully contributed to aldehydic PC1* SVs (p 10^-3 to < 10^-9), as did all PC1-3 x PC4 interaction ones (p 10^-5 to < 10^-9). PC2* was also markedly dependent on all the above PC SVs (PC2 > PC1 and PC3), and the interactions of PC1 and PC2 with PC4 (p < 10^-9 in each case), but not the PC3 x PC4 contribution. Conclusions: NMR-linked PCR analysis is a valuable strategy for (1) modelling the generation of aldehydic LOPs in heated cooking oils and other FM, and (2) tracking their unsaturated fatty acid (UFA) triacylglycerol sources therein.

Keywords: frying oils, lipid oxidation products, frying episodes, chemometrics, principal component regression, NMR Analysis, cytotoxic/genotoxic aldehydes

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Authors: D. Serero, L. Couton, J. D. Parisse, R. Leroy

Abstract:

In urban planning, an increasing number of cities require wind analysis to verify comfort of public spaces and around buildings. These studies are made using computer fluid dynamic simulation (CFD). However, this technique is often based on wind information taken from meteorological stations located at several kilometers of the spot of analysis. The approximated input data on project surroundings produces unprecise results for this type of analysis. They can only be used to get general behavior of wind in a zone but not to evaluate precise wind speed. This paper presents another approach to this problem, based on collecting wind data and generating an urban wind cartography using connected ultrasound anemometers. They are wireless devices that send immediate data on wind to a remote server. Assembled in array, these devices generate geo-localized data on wind such as speed, temperature, pressure and allow us to compare wind behavior on a specific site or building. These Netatmo-type anemometers communicate by wifi with central equipment, which shares data acquired by a wide variety of devices such as wind speed, indoor and outdoor temperature, rainfall, and sunshine. Beside its precision, this method extracts geo-localized data on any type of site that can be feedback looped in the architectural design of a building or a public place. Furthermore, this method allows a precise calibration of a virtual wind tunnel using numerical aeraulic simulations (like STAR CCM + software) and then to develop the complete volumetric model of wind behavior over a roof area or an entire city block. The paper showcases connected ultrasonic anemometers, which were implanted for an 18 months survey on four study sites in the Grand Paris region. This case study focuses on Paris as an urban environment with multiple historical layers whose diversity of typology and buildings allows considering different ways of capturing wind energy. The objective of this approach is to categorize the different types of wind in urban areas. This, particularly the identification of the minimum and maximum wind spectrum, helps define the choice and performance of wind energy capturing devices that could be implanted there. The localization on the roof of a building, the type of wind, the altimetry of the device in relation to the levels of the roofs, the potential nuisances generated. The method allows identifying the characteristics of wind turbines in order to maximize their performance in an urban site with turbulent wind.

Keywords: computer fluid dynamic simulation in urban environment, wind energy harvesting devices, net-zero energy building, urban wind behavior simulation, advanced building skin design methodology

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Authors: Jaeyoung Lee

Abstract:

Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: edge network, embedded network, MMA, matrix multiplication accelerator, semantic segmentation network

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Authors: Zhicheng Han

Abstract:

This study examines the correlation between knowledge of formulaic language, working memory (WM), and phonological short-term memory (PSTM) in Chinese L2 learners of English. This study investigates if WM and PSTM correlate differently to the acquisition of formulaic language, which may be relevant for the discourse around the conceptualization of formulas. Connectionist approaches have lead scholars to argue that formulas are form-meaning connections stored whole, making PSTM significant in the acquisitional process as it pertains to the storage and retrieval of chunk information. Generativist scholars, on the other hand, argued for active participation of interlanguage grammar in the acquisition and use of formulaic language, where formulas are represented in the mind but retain the internal structure built around a lexical core. This would make WM, especially the processing component of WM an important cognitive factor since it plays a role in processing and holding information for further analysis and manipulation. The current study asked L1 Chinese learners of English enrolled in graduate programs in China to complete a preference raking task where they rank their preference for formulas, grammatical non-formulaic expressions, and ungrammatical phrases with and without the lexical core in academic contexts. Participants were asked to rank the options in order of the likeliness of them encountering these phrases in the test sentences within academic contexts. Participants’ syntactic proficiency is controlled with a cloze test and grammar test. Regression analysis found a significant relationship between the processing component of WM and preference of formulaic expressions in the preference ranking task while no significant correlation is found for PSTM or syntactic proficiency. The correlational analysis found that WM, PSTM, and the two proficiency test scores have significant covariates. However, WM and PSTM have different predictor values for participants’ preference for formulaic language. Both storage and processing components of WM are significantly correlated with the preference for formulaic expressions while PSTM is not. These findings are in favor of the role of interlanguage grammar and syntactic knowledge in the acquisition of formulaic expressions. The differing effects of WM and PSTM suggest that selective attention to and processing of the input beyond simple retention play a key role in successfully acquiring formulaic language. Similar correlational patterns were found for preferring the ungrammatical phrase with the lexical core of the formula over the ones without the lexical core, attesting to learners’ awareness of the lexical core around which formulas are constructed. These findings support the view that formulaic phrases retain internal syntactic structures that are recognized and processed by the learners.

Keywords: formulaic language, working memory, phonological short-term memory, academic language

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