Search results for: product image

Authors: Nutnicha Wongpadungkiat, Suwit Siriwatanayotin, Aluck Thipayarat, Punchira Vongsawasdi, Chotika Viriyarattanasak

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Chicken products are major export product of Thailand. With a dramatically increasing consumption of chicken product in the world, there are abundant wastes from chicken meat processing industry. Recently, much research in the development of value-added products from chicken meat industry has focused on the production of protein hydrolysate, utilized as food ingredients for human diet and animal feed. The present study aimed to determine the effect of thermal pre-treatment on functional properties of chicken protein hydrolysate. Chicken breasts were heated at 40, 60, 80 and 100ºC prior to hydrolysis by Alcalase at 60ºC, pH 8 for 4 hr. The hydrolysate was freeze-dried, and subsequently used for assessment of its functional properties molecular weight by gel electrophoresis (SDS-PAGE). The obtained results show that increasing the pre-treatment temperature increased oil holding capacity and emulsion stability while decreasing antioxidant activity and water holding capacity. The SDS-PAGE analysis showed the evidence of protein aggregation in the hydrolysate treated at the higher pre-treatment temperature. These results suggest the connection between molecular weight of the hydrolysate and its functional properties.

Keywords: chicken protein hydrolysate, enzymatic hydrolysis, thermal pretreatment, functional properties

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Authors: Akshay Dirisala

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Humans had developed a highly organized and efficient civilization to live in by improving the basic needs of humans like housing, transportation, and utilities. These developments have made a huge impact on major environmental factors. Air pollution is one prominent environmental factor that needs to be addressed to maintain a sustainable and healthier lifestyle. Textiles have always been at the forefront of helping humans shield from environmental conditions. With the growth in the field of electronic textiles, we now have the capability of monitoring the atmosphere in real time to understand and analyze the environment that a particular person is mostly spending their time at. Integrating textiles with the particulate matter sensors that measure air quality and pollutants that have a direct impact on human health will help to understand what type of air we are breathing. This research idea aims to develop a textile product and a process of collecting the pollutants through particulate matter sensors, which are equipped inside a smart textile product and store the data to develop a machine learning model to analyze the health conditions of the person wearing the garment and periodically notifying them not only will help to be cautious of airborne diseases but will help to regulate the diseases and could also help to take care of skin conditions.

Keywords: air pollution, e-textiles, particulate matter sensors, environment, machine learning models

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Authors: Michael K. Adu, Boniface K. Alese, Olumide S. Ogunnusi

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This paper brings to fore the inherent advantages in application of mobile agents to procure software products rather than downloading software content on the Internet. It proposes a system whereby the products come on compact disk with mobile agent as deliverable. The client/user purchases a software product, but must connect to the remote server of the software developer before installation. The user provides an activation code that activates mobile agent which is part of the software product on compact disk. The validity of the activation code is checked on connection at the developer’s end to ascertain authenticity and prevent piracy. The system is implemented by downloading two different software products as compare with installing same products on compact disk with mobile agent’s application. Downloading software contents from developer’s database as in the traditional method requires a continuously open connection between the client and the developer’s end, a fixed network is not economically or technically feasible. Mobile agent after being dispatched into the network becomes independent of the creating process and can operate asynchronously and autonomously. It can reconnect later after completing its task and return for result delivery. Response Time and Network Load are very minimal with application of Mobile agent.

Keywords: software products, software developer, internet, activation code, mobile agent

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Authors: Kanika Sharma, Shaila Bahl, Birendra Singh, Pratik Kumar, S. P. Lochab, A. Pandey

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In the present investigation, initially nano-particles of CaF2 were prepared by the chemical co-precipitation method and later the prepared salt was activated by thulium (0.1 mol%) using the combustion technique. The final product was characterized and confirmed by X-Ray diffraction (XRD) and transmission electron microscopy (TEM). Further, the thermoluminescence (TL) properties of the nanophosphor were studied by irradiating it with 1.25 MeV of gamma radiation and 65 MeV of carbon (C6+) ion beam. For gamma rays, two prominent TL peaks were observed with a low temperature peak at around 1070C and a high temperature peak at around 1570C. Furthermore, the nanophosphor maintained a linear TL response for the entire range of studied doses i.e. 10 Gy to 2000 Gy for both the temperature peaks. Moreover, when the nanophosphor was irradiated with 65 MeV of C6+ ion beam the shape and structure of the glow curves remained spectacularly similar and the nanophosphor displayed a linear TL response for the full range of studied fluences i.e. 5*1010 ions/cm2 to 1 *1012 ions/ cm2. Finally, various tests like reproducibility test and batch homogeneity were also carried out to define the final product. Thus, co-precipitation method followed by combustion technique was successful in effectively producing dosimetric grade CaF2:Tm for dosimetry of gamma as well as carbon (C6+) beam.

Keywords: gamma radiation, ion beam, nanocrystalline, radiation dosimetry

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Authors: Shankaran Sitarama

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New Product Development involves team members coming together and working in teams to come up with innovative solutions to problems, resulting in new products. Thus, a core attribute of a successful NPD team is their creativity and innovation. They need to be creative as a group, generating a breadth of ideas and innovative solutions that solve or address the problem they are targeting and meet the user’s needs. They also need to be very efficient in their teamwork as they work through the various stages of the development of these ideas, resulting in a POC (proof-of-concept) implementation or a prototype of the product. There are two distinctive traits that the teams need to have, one is ideational creativity, and the other is effective and efficient teamworking. There are multiple types of tensions that each of these traits cause in the teams, and these tensions reflect in the team dynamics. Ideational conflicts arising out of debates and deliberations increase the collective knowledge and affect the team creativity positively. However, the same trait of challenging each other’s viewpoints might lead the team members to be disruptive, resulting in interpersonal tensions, which in turn lead to less than efficient teamwork. Teams that foster and effectively manage these creative tensions are successful, and teams that are not able to manage these tensions show poor team performance. In this paper, it explore these tensions as they result in the team communication social network and propose a Creative Tension Balance index along the lines of Degree of Balance in social networks that has the potential to highlight the successful (and unsuccessful) NPD teams. Team communication reflects the team dynamics among team members and is the data set for analysis. The emails between the members of the NPD teams are processed through a semantic analysis algorithm (LSA) to analyze the content of communication and a semantic similarity analysis to arrive at a social network graph that depicts the communication amongst team members based on the content of communication. This social network is subjected to traditional social network analysis methods to arrive at some established metrics and structural balance analysis metrics. Traditional structural balance is extended to include team interaction pattern metrics to arrive at a creative tension balance metric that effectively captures the creative tensions and tension balance in teams. This CTB (Creative Tension Balance) metric truly captures the signatures of successful and unsuccessful (dissonant) NPD teams. The dataset for this research study includes 23 NPD teams spread out over multiple semesters and computes this CTB metric and uses it to identify the most successful and unsuccessful teams by classifying these teams into low, high and medium performing teams. The results are correlated to the team reflections (for team dynamics and interaction patterns), the team self-evaluation feedback surveys (for teamwork metrics) and team performance through a comprehensive team grade (for high and low performing team signatures).

Keywords: team dynamics, social network analysis, new product development teamwork, structural balance, NPD teams

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Authors: Christopher B. Obida, George A. Blackburn, James D. Whyatt, Kirk T. Semple

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In many regions of the world, especially in developing countries, river network data are outdated or completely absent, yet such information is critical for supporting important functions such as flood mitigation efforts, land use and transportation planning, and the management of water resources. In this study, a method was developed for delineating river networks using Sentinel 1 imagery. Unsupervised classification was applied to multi-temporal Sentinel 1 data to discriminate water bodies from other land covers then the outputs were combined to generate a single persistent water bodies product. A thinning algorithm was then used to delineate river centre lines, which were converted into vector features and built into a topologically structured geometric network. The complex river system of the Niger Delta was used to compare the performance of the Sentinel-based method against alternative freely available water body products from United States Geological Survey, European Space Agency and OpenStreetMap and a river network derived from a Shuttle Rader Topography Mission Digital Elevation Model. From both raster-based and vector-based accuracy assessments, it was found that the Sentinel-based river network products were superior to the comparator data sets by a substantial margin. The geometric river network that was constructed permitted a flow routing analysis which is important for a variety of environmental management and planning applications. The extracted network will potentially be applied for modelling dispersion of hydrocarbon pollutants in Ogoniland, a part of the Niger Delta. The approach developed in this study holds considerable potential for generating up to date, detailed river network data for the many countries where such data are deficient.

Keywords: Sentinel 1, image processing, river delineation, large scale mapping, data comparison, geometric network

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Authors: Vishal Kumar Singh

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Bioprocess development is a time-constrained activity aimed at harnessing the full potential of culture performance in an ambience that is not natural to cells. Even with the use of chemically defined media and feeds, a significant amount of time is devoted in identifying the apt operating parameters. In addition, the scale-up of these processes is often accompanied by loss of antibody titer and product quality, which further delays the commercialization of the drug product. In such a scenario, the investigation of this disparity of culture performance is done by further experimentation at a smaller scale that is representative of at-scale production bioreactors. These scale-down model developments are also time-intensive. In this study, a computation fluid dynamics-based multi-objective scaling approach has been illustrated to speed up the process transfer. For the implementation of this approach, a transient multiphase water-air system has been studied in Ansys CFX to visualize the air bubble distribution and volumetric mass transfer coefficient (kLa) profiles, followed by the design of experiment based parametric optimization approach to define the operational space. The proposed approach is completely in silico and requires minimum experimentation, thereby rendering a high throughput to the overall process development.

Keywords: bioprocess development, scale up, scale down, computation fluid dynamics, multi-objective, Ansys CFX, design of experiment

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Authors: Ahmet Karagoz, Irfan Karagoz

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Synthetic Aperture Radar (SAR) is a radar mechanism that can be integrated into manned and unmanned aerial vehicles to create high-resolution images in all weather conditions, regardless of day and night. In this study, SAR images of military vehicles with different azimuth and descent angles are pre-processed at the first stage. The main purpose here is to reduce the high speckle noise found in SAR images. For this, the Wiener adaptive filter, the mean filter, and the median filters are used to reduce the amount of speckle noise in the images without causing loss of data. During the image segmentation phase, pixel values are ordered so that the target vehicle region is separated from other regions containing unnecessary information. The target image is parsed with the brightest 20% pixel value of 255 and the other pixel values of 0. In addition, by using appropriate parameters of statistical region merging algorithm, segmentation comparison is performed. In the step of feature extraction, the feature vectors belonging to the vehicles are obtained by using Gabor filters with different orientation, frequency and angle values. A number of Gabor filters are created by changing the orientation, frequency and angle parameters of the Gabor filters to extract important features of the images that form the distinctive parts. Finally, images are classified by sparse representation method. In the study, l₁ norm analysis of sparse representation is used. A joint database of the feature vectors generated by the target images of military vehicle types is obtained side by side and this database is transformed into the matrix form. In order to classify the vehicles in a similar way, the test images of each vehicle is converted to the vector form and l₁ norm analysis of the sparse representation method is applied through the existing database matrix form. As a result, correct recognition has been performed by matching the target images of military vehicles with the test images by means of the sparse representation method. 97% classification success of SAR images of different military vehicle types is obtained.

Keywords: automatic target recognition, sparse representation, image classification, SAR images

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Authors: Adam M. Pitz, Gillian L. Phillipson, Jayant E. Khanolkar, Andrew M. Middleton

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New emerging evidence suggests that the nose is the predominant route for entry of the SARS-CoV-2 virus into the host. A virucidal suspension test (conforming in principle to the European Standard EN14476) was conducted to determine whether a commercial liquid gel intranasal spray containing 1% of the mucoadhesive hydroxypropyl methylcellulose (HPMC) could inhibit the cellular infectivity of the SARS-CoV-2 coronavirus. Virus was added to the test product samples and to controls in a 1:8 ratio and mixed with one part bovine serum albumin as an interfering substance. The test samples were pre-equilibrated to 34 ± 2°C (representing the temperature of the nasopharynx) with the temperature maintained at 34 ± 2°C for virus contact times of 1, 5 and 10 minutes. Neutralized aliquots were inoculated onto host cells (Vero E6 cells, ATCC CRL-1586). The host cells were then incubated at 36 ± 2°C for a period of 7 days. The residual infectious virus in both test and controls was detected by viral-induced cytopathic effect. The 50% tissue culture infective dose per mL (TCID50/mL) was determined using the Spearman-Karber method with results reported as the reduction of the virus titer due to treatment with test product, expressed as log10. The controls confirmed the validity of the results with no cytotoxicity or viral interference observed in the neutralized test product samples. The HPMC formulation reduced SARS-CoV-2 titer, expressed as log10TCID50, by 2.30 ( ± 0.17), 2.60 ( ± 0.19), and 3.88 ( ± 0.19) with the respective contact times of 1, 5 and 10 minutes. The results demonstrate that this 1% HPMC gel formulation can reduce the cellular infectivity of the SARS-CoV-2 virus with an increasing viral inhibition observed with increasing exposure time. This 1% HMPC gel is well tolerated and can reside, when delivered via nasal spray, for up to one hour in the nasal cavity. We conclude that this intranasal gel spray with 1% HPMC repeat-dosed every few hours may offer an effective preventive or early intervention solution to limit the transmission and impact of the SARS-CoV-2 coronavirus.

Keywords: hydroxypropyl methylcellulose, mucoadhesive nasal spray, respiratory viruses, SARS-CoV-2

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Authors: Raana Babadi Fathipour

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Ice cream is a nutritious dairy product that, given its constituent materials and high nutritional value, is a suitable growth medium for the growth of various food microorganisms. The contamination of this product with pathogenic microorganisms may cause food poisoning and infections, and so could be harmful to human health. The foremost critical pathogenic microscopic organisms of ice cream incorporate Escherichia coli, Staphylococcus aureus, Bacillus cereus, Enterobacteriaceae, coliforms, Listeria monocytogenes and Enterococcus. Biosensor technology, albeit a recent addition to the dairy industry, has proven its worth in other fields, such as medical devices. Through numerous studies, the advantages of employing biosensors have consistently emerged. These incredible tools present expeditious and straightforward means while specifically targeting analytes. Thus, they bring forth unparalleled solutions that bolster ongoing advancements within dairy products and processes. This review delves into the latest developments in the realm of biosensors and evaluates the diverse techniques of bio-recognition and transduction in terms of their benefits, drawbacks, and relevance to traditional ice cream. Furthermore, the obstacles that impede the progress of these approaches in meeting the growing need for swift and real-time quality control of milk products, particularly ice cream, are also expounded upon.

Keywords: traditional ice cream, Escherichia coli, Staphylococcus aureus, biosensors

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Authors: Mulatu Kassie Birhanu

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Electro-oxidation of glycerol is an important process to convert the less price glycerol into other expensive (essential) and energy-rich chemicals. In this study, nickel was electro-deposited on laboratory-made carbon ceramic electrode (CCE) substrate using electrochemical techniques that is cyclic voltammetry (CV) to prepare an electro-catalyst (Ni/CCE) for electro-oxidation of glycerol. Carbon ceramic electrode was prepared from graphite and methyl tri-methoxy silane (MTMOS) through the processes called hydrolysis and condensation with methanol in acidic media (HCl) by a sol-gel technique. Physico-chemical characterization of bare CCE and modified (deposited) CCE (Ni/CCE) was measured and evaluated by Fourier Transform Infrared spectroscopy (FTIR), Scanning Electron Microscopy (SEM) and X-ray diffraction (XRD). Electro-oxidation of glycerol was performed in 0.1 M glycerol in alkaline media (0.5 M NaOH). High-Performance Liquid Chromatography (HPLC) technique was used to identify and determine the concentration of glycerol, reaction intermediates and oxidized products of glycerol after its electro-oxidation is performed. The conversion (%) of electro-oxidation of glycerol during 9-hour oxidation was 73% and 36% at 1.8V and 1.6V vs. RHE, respectively. Formate, oxalate, glycolate and glycerate are the main oxidation products of glycerol with selectivity (%) of 75%, 8.6%, 1.1% and 0.95 % at 1.8 V vs. RHE and 55.4%, 2.2%, 1.0% and 0.6% at 1.6 V vs. RHE respectively. The result indicates that formate is the main product in the electro-oxidation of glycerol on Ni/CCE using the indicated applied potentials.

Keywords: carbon-ceramic electrode, electrodeposition, electro-oxidation, Methyltrimethoxysilane

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Authors: Andrew Fox, Tao Zhang, Yuanhong Zhao, Qingping Yang

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The furniture manufacturing industry has been slow in general to adopt the latest manufacturing technologies, historically relying heavily upon specialised conventional machinery. This approach not only requires high levels of specialist process knowledge, training, and capital investment but also suffers from significant subtractive manufacturing waste and high logistics costs due to the requirement for centralised manufacturing, with high levels of furniture product not re-cycled or re-used. This paper aims to address the problems by introducing suitable digital manufacturing technologies to create step changes in furniture manufacturing design, as the traditional design practices have been reported as building in 80% of environmental impact. In this paper, a 3D printing robot for furniture manufacturing is reported. The 3D printing robot mainly comprises a KUKA industrial robot, an Arduino microprocessor, and a self-assembled screw fed extruder. Compared to traditional 3D printer, the 3D printing robot has larger motion range and can be easily upgraded to enlarge the maximum size of the printed object. Generative design is also investigated in this paper, aiming to establish a combined design methodology that allows assessment of goals, constraints, materials, and manufacturing processes simultaneously. ‘Matrixing’ for part amalgamation and product performance optimisation is enabled. The generative design goals of integrated waste reduction increased manufacturing efficiency, optimised product performance, and reduced environmental impact institute a truly lean and innovative future design methodology. In addition, there is massive future potential to leverage Single Minute Exchange of Die (SMED) theory through generative design post-processing of geometry for robot manufacture, resulting in ‘mass customised’ furniture with virtually no setup requirements. These generatively designed products can be manufactured using the robot based additive manufacturing. Essentially, the 3D printing robot is already functional; some initial goals have been achieved and are also presented in this paper.

Keywords: additive manufacturing, generative design, robot, sustainability

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Authors: Andrew Fox, Qingping Yang, Yuanhong Zhao, Tao Zhang

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Furniture is a very significant subdivision of architecture and its inherent interior design activities. The furniture industry has developed from an artisan-driven craft industry, whose forerunners saw themselves manifested in their crafts and treasured a sense of pride in the creativity of their designs, these days largely reduced to an anonymous collective mass-produced output. Although a very conservative industry, there is great potential for the implementation of collaborative digital technologies allowing a reconfigured artisan experience to be reawakened in a new and exciting form. The furniture manufacturing industry, in general, has been slow to adopt new methodologies for a design using artificial and rule-based generative design. This tardiness has meant the loss of potential to enhance its capabilities in producing sustainable, flexible, and mass customizable ‘right first-time’ designs. This paper aims to demonstrate the concept methodology for the creation of alternative and inspiring aesthetic structures for robot-based additive manufacturing (RBAM). These technologies can enable the economic creation of previously unachievable structures, which traditionally would not have been commercially economic to manufacture. The integration of these technologies with the computing power of generative design provides the tools for practitioners to create concepts which are well beyond the insight of even the most accomplished traditional design teams. This paper aims to address the problem by introducing generative design methodologies employing the Autodesk Fusion 360 platform. Examination of the alternative methods for its use has the potential to significantly reduce the estimated 80% contribution to environmental impact at the initial design phase. Though predominantly a design methodology, generative design combined with RBAM has the potential to leverage many lean manufacturing and quality assurance benefits, enhancing the efficiency and agility of modern furniture manufacturing. Through a case study examination of a furniture artifact, the results will be compared to a traditionally designed and manufactured product employing the Ecochain Mobius product life cycle analysis (LCA) platform. This will highlight the benefits of both generative design and robot-based additive manufacturing from an environmental impact and manufacturing efficiency standpoint. These step changes in design methodology and environmental assessment have the potential to revolutionise the design to manufacturing workflow, giving momentum to the concept of conceiving a pre-industrial model of manufacturing, with the global demand for a circular economy and bespoke sustainable design at its heart.

Keywords: robot, manufacturing, generative design, sustainability, circular econonmy, product life cycle assessment, furniture

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Authors: Tsietsi J. Pilusa, Tumisang G. Seodigeng

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This study evaluates the benefits of advanced waste management practices in unlocking waste-to-energy opportunities within the solid waste industry. The key drivers of sustainable waste management practices, specifically with respect to packaging waste-to-energy technology options are discussed. The success of a waste-to-energy system depends significantly on the appropriateness of available technologies, including those that are well established as well as those that are less so. There are hard and soft interventions to be considered when packaging an integrated waste treatment solution. Technology compatibility with variation in feedstock (waste) quality and quantities remains a key factor. These factors influence the technology reliability in terms of production efficiencies and product consistency, which in turn, drives the supply and demand network. Waste treatment technologies rely on the waste material as feedstock; the feedstock varies in quality and quantities depending on several factors; hence, the technology fails, as a result. It is critical to design an advanced waste treatment technology in an integrated approach to minimize the possibility of technology failure due to unpredictable feedstock quality, quantities, conversion efficiencies, and inconsistent product yield or quality. An integrated waste-to-energy approach offers a secure system design that considers sustainable waste management practices.

Keywords: emerging markets, evaluation tool, interventions, waste treatment technologies

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Authors: Hanen Khanchel, Karim Ben Kahla

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Pharmaceutical companies are facing competition. Indeed, the price differences between competing products can be such that it becomes difficult to compensate them by differences in value added. The conditions of competition are no longer homogeneous for the players involved. The price of a product is a given that puts a company and its customer face to face. However, price fixing obliges the company to consider internal factors relating to production costs and external factors such as customer attitudes, the existence of regulations and the structure of the market on which the firm evolved. In setting the selling price, the company must first take into account internal factors relating to its costs: costs of production fall into two categories, fixed costs and variable costs that depend on the quantities produced. The company cannot consider selling below what it costs the product. It, therefore, calculates the unit cost of production to which it adds the unit cost of distribution, enabling it to know the unit cost of production of the product. The company adds its margin and thus determines its selling price. The margin is used to remunerate the capital providers and to finance the activity of the company and its investments. Production costs are related to the quantities produced: large-scale production generally reduces the unit cost of production, which is an asset for companies with mass production markets. This shows that small and medium-sized companies with limited market segments need to make greater efforts to ensure their profit margins. As a result, and faced with high and low market prices for raw materials and increasing staff costs, the company must seek to optimize its production time in order to reduce loads and eliminate waste. Then, the customer pays only value added. Thus, and based on this principle we decided to create a project that deals with the problem of waste in our company, and having as objectives the reduction of production costs and improvement of performance indicators. This paper presents the implementation of the Value Stream Mapping (VSM) project in a pharmaceutical company. It is structured as follows: 1) determination of the family of products, 2) drawing of the current state, 3) drawing of the future state, 4) action plan and implementation.

Keywords: VSM, waste, production time, kaizen, cartography, improvement

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Authors: Shaik Ayesha Fathima, Shaik Noor Jahan, Duvvada Rajeswara Rao

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Earth's environment and its evolution can be seen through satellite images in near real-time. Through satellite imagery, remote sensing data provide crucial information that can be used for a variety of applications, including image fusion, change detection, land cover classification, agriculture, mining, disaster mitigation, and monitoring climate change. The objective of this project is to propose a method for classifying satellite images according to multiple predefined land cover classes. The proposed approach involves collecting data in image format. The data is then pre-processed using data pre-processing techniques. The processed data is fed into the proposed algorithm and the obtained result is analyzed. Some of the algorithms used in satellite imagery classification are U-Net, Random Forest, Deep Labv3, CNN, ANN, Resnet etc. In this project, we are using the DeepLabv3 (Atrous convolution) algorithm for land cover classification. The dataset used is the deep globe land cover classification dataset. DeepLabv3 is a semantic segmentation system that uses atrous convolution to capture multi-scale context by adopting multiple atrous rates in cascade or in parallel to determine the scale of segments.

Keywords: area calculation, atrous convolution, deep globe land cover classification, deepLabv3, land cover classification, resnet 50

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Authors: Eleonora Sofilda, Ria Amalia, Muhammad Zilal Hamzah

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Foreign direct investment is one of the sources of financing or capital that important for a country, especially for developing countries. This investment also provides a great contribution to development through the transfer of assets, management improving, and transfer of technology in enhancing the economy of a country. In the other side currently in ASEAN countries emerge the interesting phenomenon where some big producers are re-locate their basic production among those countries. This research is aimed to analyze the factors that affect capital inflows of foreign direct investment into the 6 ASEAN countries (Indonesia, Malaysia, Singapore, Thailand, Philippines, and Vietnam) in period 2004-2012. This study uses panel data analysis to determine the factors that affect of foreign direct investment in 6 ASEAN. The factors that affect of foreign direct investment (FDI) are the gross domestic product (GDP), global competitiveness (GCI), interest rate, exchange rate and trade openness (TO). Result of panel data analysis show that three independent variables (GCI, GDP, and TO) have a significant effect to the FDI in 6 ASEAN Countries.

Keywords: foreign direct investment, the gross domestic product, global competitiveness, interest rate, exchange rate, trade openness, panel data analysis

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Authors: Stephen Tullis, M. David DiDonato, Hong Sung Park

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Rowing boats (shells) are often steered by a small rudder operated by one of the backward-facing rowers; the attention required of that athlete then slightly decreases the power that that athlete can provide. Reducing the steering distraction would then increase the overall boat speed. Races are straight 2000 m courses with each boat in a 13.5 m wide lane marked by small (~15 cm) widely-spaced (~10 m) buoys, and the boat trajectory is affected by both cross-currents and winds. An optical buoy recognition and tracking system has been developed that provides the boat’s location and orientation with respect to the lane edges. This information is provided to the steering athlete as either: a simple overlay on a video display, or fed to a simplified autopilot system giving steering directions to the athlete or directly controlling the rudder. The system is then effectively a “lane-assist” device but with small, widely-spaced lane markers viewed from a very shallow angle due to constraints on camera height. The image is captured with a lightweight 1080p webcam, and most of the image analysis is done in OpenCV. The colour RGB-image is converted to a grayscale using the difference of the red and blue channels, which provides good contrast between the red/yellow buoys and the water, sky, land background and white reflections and noise. Buoy detection is done with thresholding within a tight mask applied to the image. Robust linear regression using Tukey’s biweight estimator of the previously detected buoy locations is used to develop the mask; this avoids the false detection of noise such as waves (reflections) and, in particular, buoys in other lanes. The robust regression also provides the current lane edges in the camera frame that are used to calculate the displacement of the boat from the lane centre (lane location), and its yaw angle. The interception of the detected lane edges provides a lane vanishing point, and yaw angle can be calculated simply based on the displacement of this vanishing point from the camera axis and the image plane distance. Lane location is simply based on the lateral displacement of the vanishing point from any horizontal cut through the lane edges. The boat lane position and yaw are currently fed what is essentially a stripped down marine auto-pilot system. Currently, only the lane location is used in a PID controller of a rudder actuator with integrator anti-windup to deal with saturation of the rudder angle. Low Kp and Kd values decrease unnecessarily fast return to lane centrelines and response to noise, and limiters can be used to avoid lane departure and disqualification. Yaw is not used as a control input, as cross-winds and currents can cause a straight course with considerable yaw or crab angle. Mapping of the controller with rudder angle “overall effectiveness” has not been finalized - very large rudder angles stall and have decreased turning moments, but at less extreme angles the increased rudder drag slows the boat and upsets boat balance. The full system has many features similar to automotive lane-assist systems, but with the added constraints of the lane markers, camera positioning, control response and noise increasing the challenge.

Keywords: auto-pilot, lane-assist, marine, optical, rowing

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Authors: Gajendra Kumar Mourya, Dinesh Bhatia, Akash Handique, Sunita Warjri, Syed Achaab Amir

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Nowadays, Medical imaging has become an integral part of modern healthcare. Abdominal CT images are an invaluable mean for abdominal organ investigation and have been widely studied in the recent years. Diagnosis of liver pathologies is one of the major areas of current interests in the field of medical image processing and is still an open problem. To deeply study and diagnose the liver, segmentation of liver is done to identify which part of the liver is mostly affected. Manual segmentation of the liver in CT images is time-consuming and suffers from inter- and intra-observer differences. However, automatic or semi-automatic computer aided segmentation of the Liver is a challenging task due to inter-patient Liver shape and size variability. In this paper, we present a technique for automatic segmenting the liver from CT images using Random Forest Classifier. Random forests or random decision forests are an ensemble learning method for classification that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes of the individual trees. After comparing with various other techniques, it was found that Random Forest Classifier provide a better segmentation results with respect to accuracy and speed. We have done the validation of our results using various techniques and it shows above 89% accuracy in all the cases.

Keywords: CT images, image validation, random forest, segmentation

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Authors: Rusne Kregzdaite

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The value of the cultural sector stems from the symbolic exploration that differentiates cultural organisations from other product or service organisations. As a result, the cultural sector has a dual impact on the socio-economic system: the economic value (expressed in terms of market relations) created influences the dynamics of the country's financial indicators, while the cultural (non-market) value indirectly contributes to the welfare of the state through changes in societal values, creativity transformations and cultural needs of the country. Measurement of indirect (cultural value) impacts is difficult, but in the case of the cultural sector (especially when it comes to economically inefficient state-funded culture), it helps to reveal the essential characteristics of the sector. The study aims to analyze the value of cultural organisations that are invisible in market processes and to base it on quantified calculations. This was be done by analyzing the usefulness of the consumer, incorporating not only the price paid but also the social and cultural decision-making factors that determine the spectator's choice (time dedicated for a visit, additional costs, content, previous experiences, corporate image). This may reflect the consumer's real choice to consume (all the costs he incurs may be considered the financial equivalent of his experience with the cultural establishment). The research methodology was tested by analyzing the performing arts sector and applying methods to the Lithuanian national drama theatre case. The empirical research consisted of a survey (more than 800 participants) of Lithuanian national drama theatre visitors to different performances. The willingness to pay and travel costs methods were used. Analysis of different performances lets identifies the factor that increases willingness to pay for the performance and affects theatre attendance. The research stresses the importance of cultural value and social perspective of the cultural sector and relates it to the discussions of public funding of culture.

Keywords: cultural economics, performing arts, willingness to pay, travel cost analysis, performing arts management

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Authors: Zhuang Hou, Xiaolei Cao

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The general public and medical professionals recognized the importance of accurately measuring and storing blood oxygen levels and heart rate during the COVID-19 pandemic. The demand for accurate contactless devices was motivated by the need for cross-infection reduction and the shortage of conventional oximeters, partially due to the global supply chain issue. This paper evaluated a contactless mini program HealthyPai’s heart rate (HR) and oxygen saturation (SpO2) measurements compared with other wearable devices. In the HR study of 185 samples (81 in the laboratory environment, 104 in the real-life environment), the mean absolute error (MAE) ± standard deviation was 1.4827 ± 1.7452 in the lab, 6.9231 ± 5.6426 in the real-life setting. In the SpO2 study of 24 samples, the MAE ± standard deviation of the measurement was 1.0375 ± 0.7745. Our results validated that HealthyPai utilizing the Integrated Image Deep Learning Solution (IIDLS) framework, can accurately measure HR and SpO2, providing the test quality at least comparable to other FDA-approved wearable devices in the market and surpassing the consumer-grade and research-grade wearable standards.

Keywords: remote photoplethysmography, heart rate, oxygen saturation, contactless measurement, mini program

Procedia PDF Downloads 131

Authors: Iris Vural Gursel, Jonathan Moncada, Ernst Worrell, Andrea Ramirez

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In order to achieve the transition from a fossil to bio-based economy, biomass needs to replace fossil resources in meeting the world’s energy and chemical needs. This calls for development of biorefinery systems allowing cost-efficient conversion of biomass to chemicals. In biorefinery systems, feedstock is converted to key intermediates called platforms which are converted to wide range of marketable products. The C6 sugars platform stands out due to its unique versatility as precursor for multiple valuable products. Among the different potential routes from C6 sugars to bio-based chemicals, 1,3-butadiene and ε-caprolactam appear to be of great interest. Butadiene is an important chemical for the production of synthetic rubbers, while caprolactam is used in production of nylon-6. In this study, ex-ante techno-economic performance of 1,3-butadiene and ε-caprolactam routes from C6 sugars were assessed. The aim is to provide insight from an early stage of development into the potential of these new technologies, and the bottlenecks and key cost-drivers. Two cases for each product line were analyzed to take into consideration the effect of possible changes on the overall performance of both butadiene and caprolactam production. Conceptual process design for the processes was developed using Aspen Plus based on currently available data from laboratory experiments. Then, operating and capital costs were estimated and an economic assessment was carried out using Net Present Value (NPV) as indicator. Finally, sensitivity analyses on processing capacity and prices was done to take into account possible variations. Results indicate that both processes perform similarly from an energy intensity point of view ranging between 34-50 MJ per kg of main product. However, in terms of processing yield (kg of product per kg of C6 sugar), caprolactam shows higher yield by a factor 1.6-3.6 compared to butadiene. For butadiene production, with the economic parameters used in this study, for both cases studied, a negative NPV (-642 and -647 M€) was attained indicating economic infeasibility. For the caprolactam production, one of the cases also showed economic infeasibility (-229 M€), but the case with the higher caprolactam yield resulted in a positive NPV (67 M€). Sensitivity analysis indicated that the economic performance of caprolactam production can be improved with the increase in capacity (higher C6 sugars intake) reflecting benefits of the economies of scale. Furthermore, humins valorization for heat and power production was considered and found to have a positive effect. Butadiene production was found sensitive to the price of feedstock C6 sugars and product butadiene. However, even at 100% variation of the two parameters, butadiene production remained economically infeasible. Overall, the caprolactam production line shows higher economic potential in comparison to that of butadiene. The results are useful in guiding experimental research and providing direction for further development of bio-based chemicals.

Keywords: bio-based chemicals, biorefinery, C6 sugars, economic analysis, process modelling

Procedia PDF Downloads 150

Authors: Moumen Abdelhafidh, Stribu Bogdan, Laboureur Delphine, Gallant Johan, Hendrick Patrick

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This study is part of an ongoing effort to improve the understanding of phenomena occurring during the intermediate ballistic phase, such as muzzle flows. A thorough comprehension of muzzle flow fields is essential for optimizing muzzle device and projectile design. This flow characterization has heretofore been almost entirely limited to local and intrusive measurement techniques such as pressure measurements using pencil probes. Consequently, the body of quantitative experimental data is limited, so is the number of numerical codes validated in this field. The objective of the work presented here is to demonstrate the applicability of the Particle Image Velocimetry (PIV) technique in the challenging environment of the propellant flow of a .300 blackout weapon to provide accurate velocity measurements. The key points of a successful PIV measurement are the selection of the particle tracer, their seeding technique, and their tracking characteristics. We have experimentally investigated the aforementioned points by evaluating the resistance, gas dispersion, laser light reflection as well as the response to a step change across the Mach disk for five different solid tracers using two seeding methods. To this end, an experimental setup has been performed and consisted of a PIV system, the combustion chamber pressure measurement, classical high-speed schlieren visualization, and an aerosol spectrometer. The latter is used to determine the particle size distribution in the muzzle flow. The experimental results demonstrated the ability of PIV to accurately resolve the salient features of the propellant flow, such as the under the expanded jet and vortex rings, as well as the instantaneous velocity field with maximum centreline velocities of more than 1000 m/s. Besides, naturally present unburned particles in the gas and solid ZrO₂ particles with a nominal size of 100 nm, when coated on the propellant powder, are suitable as tracers. However, the TiO₂ particles intended to act as a tracer, surprisingly not only melted but also functioned as a combustion accelerator and decreased the number of particles in the propellant gas.

Keywords: intermediate ballistic, muzzle flow fields, particle image velocimetry, propellant gas, particle size distribution, under expanded jet, solid particle tracers

Procedia PDF Downloads 160

Authors: Seynabou Toure, Oumar Diop, Kidiyo Kpalma, Amadou S. Maiga

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Color and texture are the two most determinant elements for perception and recognition of the objects in an image. For this reason, color and texture analysis find a large field of application, for example in image classification and segmentation. But, the pioneering work in texture analysis was conducted on grayscale images, thus discarding color information. Many grey-level texture descriptors have been proposed and successfully used in numerous domains for image classification: face recognition, industrial inspections, food science medical imaging among others. Taking into account color in the definition of these descriptors makes it possible to better characterize images. Color texture is thus the subject of recent work, and the analysis of color texture images is increasingly attracting interest in the scientific community. In optical remote sensing systems, sensors measure separately different parts of the electromagnetic spectrum; the visible ones and even those that are invisible to the human eye. The amounts of light reflected by the earth in spectral bands are then transformed into grayscale images. The primary natural colors Red (R) Green (G) and Blue (B) are then used in mixtures of different spectral bands in order to produce RGB images. Thus, good color texture discrimination can be achieved using RGB under controlled illumination conditions. Some previous works investigate the effect of using different color space for color texture classification. However, the selection of the best performing color space in land-sea segmentation is an open question. Its resolution may bring considerable improvements in certain applications like coastline detection, where the detection result is strongly dependent on the performance of the land-sea segmentation. The aim of this paper is to present the results of a study conducted on different color spaces in order to show the best-performing color space for land-sea segmentation. In this sense, an experimental analysis is carried out using five different color spaces (RGB, XYZ, Lab, HSV, YCbCr). For each color space, the Haar wavelet decomposition is used to extract different color texture features. These color texture features are then used for Fusion of Over Segmentation (FOOS) based classification; this allows segmentation of the land part from the sea one. By analyzing the different results of this study, the HSV color space is found as the best classification performance while using color and texture features; which is perfectly coherent with the results presented in the literature.

Keywords: classification, coastline, color, sea-land segmentation

Procedia PDF Downloads 242

Authors: U. Gunal, H. I. Turgut, H. Gurler, S. Kaya

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There are many ever-increasing and newly emerging problems with rapid population growth in the world. With the increase in people's quality of life in our daily life, acoustic comfort has become an important feature in the textile industry. In order to meet all these expectations in people's comfort areas and survive in challenging competitive conditions in the market without compromising the customer product quality expectations of textile manufacturers, it has become a necessity to bring functionality to the products. It is inevitable to research and develop materials and processes that will bring these functionalities to textile products. The noise we encounter almost everywhere in our daily life, in the street, at home and work, is one of the problems which textile industry is working on. It brings with it many health problems, both mentally and physically. Therefore, noise control studies become more of an issue. Besides, materials used in noise control are not sufficient to reduce the effect of the noise level. The fabrics used in acoustic studies in the textile industry do not show sufficient performance according to their weight and high cost. Thus, acoustic textile products can not be used in daily life. In the thesis study, the attributions used in the noise control and building acoustics studies in the literature were analyzed, and the product with the highest damping value that a textile material will have was designed, manufactured, and tested. Optimum values were obtained by using different material samples that may affect the performance of the acoustic material. Acoustic measurement methods should be applied to verify the acoustic performances shown by the parameters and the designed three-dimensional structure at different values. In the measurements made in the study, the device designed for determining the acoustic performance of the material for both the impedance tube according to the relevant standards and the different noise types in the study was used. In addition, sound records of noise types encountered in daily life are taken and applied to the acoustic absorbent fabric with the aid of the device, and the feasibility of the results and the commercial ability of the product are examined. MATLAB numerical computing programming language and libraries were used in the frequency and sound power analyses made in the study.

Keywords: acoustic, egg crate, fabric, textile

Procedia PDF Downloads 104

Authors: Mădălina Elena Mavrodin, Gabriela Andreea Despescu, Gheorghe Lăzăroiu

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Long term trend of global warming has brought a very deep interest in climate change, which is due most likely to increasing concentrations of anthropogenic greenhouse gases. 0f these, particular attention is paid to carbon dioxide, which has led in desire for obtaining carbon footprint products. Automotive industry is one of the world’s most important economic sectors with a great impact over the environment through all range of activities. Its impact over the environment has been studied, researcher trying as much as possible to reduce it and to offer environmental friendly solution for the using, but also manufacturing cars. In the global endeavour to meet the international commitments in order to reduce the greenhouse gas emissions, many companies integrate environmental issues into their management systems, with potential effects in their entire production chains. Several tools and calculators have been developed to measure the environmental impact of a product in the life cycle perspective of the whole product chain. There were a lot of ways to obtain the carbon footprint of driving a car, but the total carbon footprint of a car includes also the carbon footprint of all the components and accessories. In the automotive industry, one of the challenges is to calculate the carbon footprint of a car from ‘cradle to grave’; this meaning not only for driving the car, but also manufacturing it, so there can be an overview over the entire process of production.

Keywords: carbon footprint, global warming potential, greenhouse gases, manufacture, plastic air ducts

Procedia PDF Downloads 319

Authors: André C. Silva, Mariana R. Barros, Elenice M. S. Silva, Douglas. Y. Marinho, Diego F. Lopes, Débora N. Sousa, Raphael S. Tomáz

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Modern agriculture requires productivity, efficiency and quality. Therefore, there is need for agricultural limestone implementation that provides adequate amounts of calcium and magnesium carbonates in order to correct soil acidity. During the limestone process, fine particles (with average size under 400#) are generated. These particles do not have economic value in agricultural and metallurgical sectors due their size. When limestone is used for agriculture purposes, these fine particles can be easily transported by wind generated air pollution. Therefore, briquetting, a mineral processing technique, was used to mitigate this problem resulting in an agglomerated product suitable for agriculture use. Briquetting uses compressive pressure to agglomerate fine particles. It can be aided by agglutination agents, allowing adjustments in shape, size and mechanical parameters of the mass. Briquettes can generate extra profits for mineral industry, presenting as a distinct product for agriculture, and can reduce the environmental liabilities of the fine particles storage or disposition. The produced limestone briquettes were subjected to shatter and water action resistance tests. The results show that after six minutes completely submerged in water, the briquettes where fully diluted, a highly favorable result considering its use for soil acidity correction.

Keywords: agglomeration, briquetting, limestone, soil acidity correction

Procedia PDF Downloads 387

Authors: Shalaka Kadam, Dinesh Apte, Sagar Mainkar

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The life cycle of products is becoming shorter and shorter due to increased competition in market, shorter product development time and increased product diversity. Short life cycles are normal in retail industry, style business, entertainment media, and telecom and semiconductor industry. The subject of accurate forecasting for demand of short lifecycle products is of special enthusiasm for many researchers and organizations. Due to short life cycle of products the amount of historical data that is available for forecasting is very minimal or even absent when new or modified products are launched in market. The companies dealing with such products want to increase the accuracy in demand forecasting so that they can utilize the full potential of the market at the same time do not oversupply. This provides the challenge to develop a forecasting model that can forecast accurately while handling large variations in data and consider the complex relationships between various parameters of data. Many statistical models have been proposed in literature for forecasting time series data. Traditional time series forecasting models do not work well for short life cycles due to lack of historical data. Also artificial neural networks (ANN) models are very time consuming to perform forecasting. We have studied the existing models that are used for forecasting and their limitations. This work proposes an effective and powerful forecasting approach for short life cycle time series forecasting. We have proposed an approach which takes into consideration different scenarios related to data availability for short lifecycle products. We then suggest a methodology which combines statistical analysis with structured judgement. Also the defined approach can be applied across domains. We then describe the method of creating a profile from analogous products. This profile can then be used for forecasting products with historical data of analogous products. We have designed an application which combines data, analytics and domain knowledge using point-and-click technology. The forecasting results generated are compared using MAPE, MSE and RMSE error scores. Conclusion: Based on the results it is observed that no one approach is sufficient for short life-cycle forecasting and we need to combine two or more approaches for achieving the desired accuracy.

Keywords: forecast, short life cycle product, structured judgement, time series

Procedia PDF Downloads 356

Authors: Dimitrios I. Tselentis, Simon P. Washington

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Considerable literature has been focused over the last few decades on forecasting the consumer demand of Energy Efficient Vehicles (EEVs). These methodological issues range from how to capture recent purchase decisions in revealed choice studies and how to set up experiments in stated preference (SP) studies, and choice of analysis method for analyzing such data. This paper reviews the plethora of published studies on the field of forecasting demand of EEVs since 1980, and provides a review and annotated bibliography of that literature as it pertains to this particular demand forecasting problem. This detailed review addresses the literature not only to Transportation studies, but specifically to the problem and methodologies around forecasting to the time horizons of planning studies which may represent 10 to 20 year forecasts. The objectives of the paper are to identify where existing gaps in literature exist and to articulate where promising methodologies might guide longer term forecasting. One of the key findings of this review is that there are many common techniques used both in the field of new product demand forecasting and the field of predicting future demand for EEV. Apart from SP and RP methods, some of these new techniques that have emerged in the literature in the last few decades are survey related approaches, product diffusion models, time-series modelling, computational intelligence models and other holistic approaches.

Keywords: demand forecasting, Energy Efficient Vehicles (EEVs), forecasting methodologies review, methodological approaches

Procedia PDF Downloads 486

Authors: Abdelrahman Elsehsah

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Land Use and Land Cover (LULC) dynamics in Riyadh over a decade were comprehensively analyzed using the Google Earth Engine (GEE) platform. By harnessing the Landsat 8 Image collection and night-time light image collection from May to August for the years 2013 and 2023, we were able to generate insightful datasets capturing the changing landscape of the region. Our approach involved a Random Forest (RF) classification model that consistently displayed commendable precision scores above 92% for both years. A notable discovery from the study was the pronounced urban expansion, particularly around Riyadh city. Within a mere ten-year span, urbanization surged noticeably, affecting the broader ecological environment of the region. Interestingly, the northeastern part of Riyadh emerged as a focal point of this growth, signaling rapid urban growth of urban sprawl and development. A comparison between the two years indicates a 21.51% increase in built-up areas, revealing the transformative pace of urban sprawl. Contrastingly, vegetation cover patterns presented a more nuanced picture. While our initial hypothesis predicted a decline in vegetation, the actual findings depicted both vegetation reduction in certain pockets and new growth in others, resulting in an overall 25.89% increase. This intricate pattern might be attributed to shifting agricultural practices, afforestation efforts, or even satellite image timings not aligning with seasonal vegetation growth. The bare soil, predominant in the desert landscape of Riyadh, saw a marginal reduction of 0.37% over the decade, challenging our initial expectations. Urban and agricultural advancements in Saudi Arabia appear to have slightly reduced the expanse of barren terrains. This study, underpinned by a rigorous methodological framework, reveals the multifaceted land cover changes in Riyadh in response to urban development and environmental factors. The precise, data-driven insights provided by our analysis serve as invaluable tools for understanding urban growth trajectories, guiding urban planning, policy formulation, and sustainable development endeavors in the region.

Keywords: remote sensing, KSA, ArcGIS, spatio-temporal

Procedia PDF Downloads 27