Search results for: product image

Authors: Anne Theresa Eidhoff, Sarah E. Stief, Markus Voeth, Sarah Gundlach

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With digitalization increasingly changing the rules of competition, firms face the need to adapt and assimilate digital technologies in order to remain competitive. Firms can choose from various possibilities to integrate digital technologies including the option to embed digital technologies aiming to innovate products or to develop digital products. However, the question of which specific factors influence a firm’s decision to pursue digital product innovation remains unanswered in research. By adopting the Technology-Organization-Environment (TOE)-framework we have designed a qualitative exploratory study including eleven German practitioners to investigate relevant contingency factors. Our results indicate that the most critical factors for a company’s decision to pursue digital product innovation can be found in the technological and environmental dimensions, namely customers, competitive pressure, technological change, as well as digitalization fit. 

Keywords: digital innovation, digitalization, product innovation, TOE-framework

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Authors: Vitor Carneiro, Augusto Barata Da Rocha, Barbara Rangel, Jorge Lino Alves

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In the European Union countries, Small and Medium-Sized Enterprises (SME’s) have an important contribution to economic activity and to the Gross Domestic Product (GDP). The implementation of design practices in SME’s is often a difficult task due to resources limitations. Unlike large companies, their product development and innovation processes frequentlylack adequate planning and systematic procedures. Design management interest has grown exponentially in recent years, but as it is a recent topic there is an absence of systematic methodologies to implement design management in SME’s with little or no design experience. This work presents a contribution to improve and optimize the process of design integration and management in SME’s. A review analysis is presented to select relevant articles on the subject, review and classify the main published contributions. Based on the selected articles content it was possible to identify five main themes related to the subject under analysis: Design Function Organization, Design Management Integration, Design Management Capabilities, Managing Design Projects, and Tools and Methods. Design management is discussed from different perspectives depending on the focus on which it is placed, whether in a design or management perspective, leading to different visions and definitions: from a more upstream strand at the intersection of design and the organization's strategic management (strategic design management) to a more downstream strand related to project management and design process (design management operational). The review analysis of the selected articles allowed the identification of a high level of complexity of connections and parameters in the design management during the product development process in the context of SME’s. Within each group of the five main themes, several sub-themes, directly or indirectly related, should be considered.Sub-connections also occur between sub-themes of different themes creating a complex and intricate web of connections. This complexity of connections is often the main obstacle to conduct design management and product development efficiently. This work proposes a formulation of a systematic methodological approach to optimize the integrated project and the management and control of the product development process among SME's. The implementation of this formulation will improve the integration of design management in the product development and innovation process in SME’s.

Keywords: design management, product development, product innovation, SME’s.

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Authors: Tudor Barbu

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An automatic moment-based texture segmentation approach is proposed in this paper. First, we describe the related work in this computer vision domain. Our texture feature extraction, the first part of the texture recognition process, produces a set of moment-based feature vectors. For each image pixel, a texture feature vector is computed as a sequence of area moments. Second, an automatic pixel classification approach is proposed. The feature vectors are clustered using some unsupervised classification algorithm, the optimal number of clusters being determined using a measure based on validation indexes. From the resulted pixel classes one determines easily the desired texture regions of the image.

Keywords: image segmentation, moment-based, texture analysis, automatic classification, validation indexes

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Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

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Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, Unmanned Aerial Vehicle (UAV), uniform, random, kriging

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Authors: Pimploi Tirastittam, Phutthiwat Waiyawuththanapoom, Manop Tirastittam

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Traceability system is one of the tools which can ensure the product’s confident of the consumer as it can trace the product back to its origin and can reduce the operation cost of recall. Nowadays, there are so many technologies which can be applied to the traceability system and also able to increase the efficiency of the system such as QR Code, barcode, GS1 and GTIN. As the result, this research is aimed to study and design the information technology pattern that suits for the traceability of Thailand’s orchid because Thailand’s orchid is the popular export product for Japan, USA, China, Netherlands and Italy. This study will enhance the value of Thailand’s orchid and able to prevent the unexpected event of the defects or damaged product. The traceability pattern was received IOC test from 12 experts from 4 fields of study which are traceability field, information technology field, information communication technology field and orchid export field. The result of the in-depth interview and questionnaire showed that the technology which most compatibility with the traceability system is the QR code. The mean of the score was 4.25 and the standard deviation was 0.5 as the QR code is the new technology and user-friendly. The traceability system should start from the farm to the consumer in the consuming country as the traceability system will enhance the quality level of the product and increase the value of its as well. The other outcome from this research is the supply chain model of Thailand’s Orchid along with the system architecture and working system diagram.

Keywords: exporting, information technology pattern, orchid, traceability

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Authors: Boukhatem Mohammed Belkaid, Lahdir Mourad

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In this paper, we propose a new encryption system for security issues meteorological images from Meteosat Second Generation (MSG), which generates 12 images every 15 minutes. The hybrid encryption scheme is based on AES and RSA algorithms to validate the three security services are authentication, integrity and confidentiality. Privacy is ensured by AES, authenticity is ensured by the RSA algorithm. Integrity is assured by the basic function of the correlation between adjacent pixels. Our system generates a unique password every 15 minutes that will be used to encrypt each frame of the MSG meteorological basis to strengthen and ensure his safety. Several metrics have been used for various tests of our analysis. For the integrity test, we noticed the efficiencies of our system and how the imprint cryptographic changes at reception if a change affects the image in the transmission channel.

Keywords: AES, RSA, integrity, confidentiality, authentication, satellite MSG, encryption, decryption, key, correlation

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Authors: Chalakorn Chitsaart, Suchada Rianmora, Noppawat Vongpiyasatit

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In order to reduce the transportation time and cost for direct interface between customer and manufacturer, the image processing technique has been introduced in this research where designing part and defining manufacturing process can be performed quickly. A3D virtual model is directly generated from a series of multi-view images of an object, and it can be modified, analyzed, and improved the structure, or function for the further implementations, such as computer-aided manufacturing (CAM). To estimate and quote the production cost, the user-friendly platform has been developed in this research where the appropriate manufacturing parameters and process detections have been identified and planned by CAM simulation.

Keywords: image processing technique, feature detections, surface registrations, capturing multi-view images, Production costs and Manufacturing processes

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Authors: R. Sumalatha, M. V. Subramanyam

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In medical image processing the quality of the image is degraded in the presence of noise. Especially in ultra sound imaging and Magnetic resonance imaging the data was corrupted by signal dependent noise known as salt and pepper noise. Removal of noise from the medical images is a critical issue for researchers. In this paper, a new type of technique Adaptive Spatial Mask Filter (ASMF) has been proposed. The proposed filter is used to increase the quality of MRI and ultra sound images. Experimental results show that the proposed filter outperforms the implementation of mean, median, adaptive median filters in terms of MSE and PSNR.

Keywords: salt and pepper noise, ASMF, PSNR, MSE

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Authors: Parth Shah

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The author examines the recent trend where business organizations are significantly reducing their developmental cycle times to stay competitive in today’s global marketspace. The author proposes a rapid systems engineering framework to address late design changes and allow for flexibility (i.e. to react to unexpected or late changes and its impacts) during the product development cycle using a Systems Engineering approach. A System Engineering approach is crucial in today’s product development to deliver complex products into the marketplace. Design changes can occur due to shortened timelines and also based on initial consumer feedback once a product or service is in the marketplace. The ability to react to change and address customer expectations in a responsive and cost-efficient manner is crucial for any organization to succeed. Past literature, research, and methods such as concurrent development, simultaneous engineering, knowledge management, component sharing, rapid product integration, tailored systems engineering processes, and studies on reducing product development cycles all suggest a research gap exist in specifically addressing late design changes due to the shortening of life cycle environments in increasingly competitive markets. The author’s research suggests that 1) product development cycles time scales are now measured in months instead of years, 2) more and more products have interdepended systems and environments that are fast-paced and resource critical, 3) product obsolesce is higher and more organizations are releasing products and services frequently, and 4) increasingly competitive markets are leading to customization based on consumer feedback. The author will quantify effectiveness with respect to success factors such as time-to-market, return-of-investment, life cycle time and flexibility in late design changes by complexity of product or service, number of late changes and ability to react and reduce late design changes.

Keywords: product development, rapid systems engineering, scalability, systems engineering, systems integration, systems life cycle

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Authors: M. Khajezadeh, M. Saied Fallah Niasar, S. Ali Asli, D. Davani Davari, M. Godarzi, Y. Asgari

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This study aims to explore the joint application of both Boston and Ansoff matrices in the operational development of the product. We conduct deep analysis, by utilizing the Artificial Neural Network, to predict the position of the product in the market while the company is interested in increasing its share. The data are gathered from two industries, called hygiene and detergent. In doing so, the effort is being made by investigating the behavior of top player companies and, recommend strategic orientations. In conclusion, this combination analysis is appropriate for operational development; as well, it plays an important role in providing the position of the product in the market for both hygiene and detergent industries. More importantly, it will elaborate on the company’s strategies to increase its market share related to a combination of the Boston Consulting Group (BCG) Matrix and Ansoff Matrix.

Keywords: artificial neural network, portfolio analysis, BCG matrix, Ansoff matrix

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Authors: William Huang

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Retinal prostheses are currently limited to low resolution grayscale images that lack color and spatial information. This study develops a novel real-time image optimization framework and tools to encode maximum information to the prostheses which are constrained by the number of electrodes. One key idea is to localize main objects in images while reducing unnecessary background noise through region-contrast saliency maps. A novel color depth mapping technique was developed through MiniBatchKmeans clustering and color space selection. The resulting image was downsampled using bicubic interpolation to reduce image size while preserving color quality. In comparison to current schemes, the proposed framework demonstrated better visual quality in tested images. The use of the region-contrast saliency map showed improvements in efficacy up to 30%. Finally, the computational speed of this algorithm is less than 380 ms on tested cases, making real-time retinal prostheses feasible.

Keywords: retinal implants, virtual processing unit, computer vision, saliency maps, color quantization

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Authors: Keyi Wang

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Similar to the touchscreen, hand gesture based human-computer interaction (HCI) is a technology that could allow people to perform a variety of tasks faster and more conveniently. This paper proposes a training method of an image-based hand gesture image and video clip recognition system using a CNN (Convolutional Neural Network) with a dataset. A dataset containing 6 hand gesture images is used to train a 2D CNN model. ~98% accuracy is achieved. Furthermore, a 3D CNN model is trained on a dataset containing 4 hand gesture video clips resulting in ~83% accuracy. It is demonstrated that a Cozmo robot loaded with pre-trained models is able to recognize static and dynamic hand gestures.

Keywords: deep learning, hand gesture recognition, computer vision, image processing

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Authors: El Asnaoui Khalid, Aksasse Brahim, Ouanan Mohammed

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In this paper, we are interested in the problem of finding similar images in a large database. For this purpose we propose a new algorithm based on a combination of the 2-D histogram intersection in the HSV space and statistical moments. The proposed histogram is based on a 3x3 window and not only on the intensity of the pixel. This approach can overcome the drawback of the conventional 1-D histogram which is ignoring the spatial distribution of pixels in the image, while the statistical moments are used to escape the effects of the discretisation of the color space which is intrinsic to the use of histograms. We compare the performance of our new algorithm to various methods of the state of the art and we show that it has several advantages. It is fast, consumes little memory and requires no learning. To validate our results, we apply this algorithm to search for similar images in different image databases.

Keywords: 2-D histogram, statistical moments, indexing, similarity distance, histograms intersection

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Authors: Leveque Benjamin, Rabaud Suzanne, Anest Hugo, Catalan Caroline, Neveux Guillaume

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Human products consumption is one of the main drivers of biodiversity loss. However, few pertinent ecological indicators regarding product life cycle impact on species and ecosystems have been built. Life cycle assessment (LCA) methodologies are well under way to conceive standardized methods to assess this impact, by taking already partially into account three of the Millennium Ecosystem Assessment pressures (land use, pollutions, climate change). Coupling LCA and ecological data and methods is an emerging challenge to develop a product biodiversity footprint. This approach was tested on three case studies from food processing, textile, and cosmetic industries. It allowed first to improve the environmental relevance of the Potential Disappeared Fraction of species, end-point indicator typically used in life cycle analysis methods, and second to introduce new indicators on overexploitation and invasive species. This type of footprint is a major step in helping companies to identify their impacts on biodiversity and to propose potential improvements.

Keywords: biodiversity, companies, footprint, life cycle assessment, products

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Authors: Javed Khan, Aamir Saeed Malik, Nidal Kamel, Sarat Chandra Dass, Azura Mohd Affandi

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Low contrast images can result from the wrong setting of image acquisition or poor illumination conditions. Such images may not be visually appealing and can be difficult for feature extraction. Contrast enhancement of color images can be useful in medical area for visual inspection. In this paper, a new technique is proposed to improve the contrast of color images. The RGB (red, green, blue) color image is transformed into normalized RGB color space. Adaptive histogram equalization technique is applied to each of the three channels of normalized RGB color space. The corresponding channels in the original image (low contrast) and that of contrast enhanced image with adaptive histogram equalization (AHE) are morphed together in proper proportions. The proposed technique is tested on seventy color images of acne patients. The results of the proposed technique are analyzed using cumulative variance and contrast improvement factor measures. The results are also compared with decorrelation stretch. Both subjective and quantitative analysis demonstrates that the proposed techniques outperform the other techniques.

Keywords: contrast enhacement, normalized RGB, adaptive histogram equalization, cumulative variance.

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Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

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Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

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Authors: Khalid Salhi, El Miloud Jaara, Mohammed Talibi Alaoui

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In this paper, we present a neural approach for unsupervised natural color-texture image segmentation, which is based on both Kohonen maps and mathematical morphology, using a combination of the texture and the image color information of the image, namely, the fractal features based on fractal dimension are selected to present the information texture, and the color features presented in RGB color space. These features are then used to train the network Kohonen, which will be represented by the underlying probability density function, the segmentation of this map is made by morphological watershed transformation. The performance of our color-texture segmentation approach is compared first, to color-based methods or texture-based methods only, and then to k-means method.

Keywords: segmentation, color-texture, neural networks, fractal, watershed

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Authors: Zineb Nougrara

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In this paper, we propose a novel methodology for extracting a road network and its nodes from satellite images of Algeria country. This developed technique is a progress of our previous research works. It is founded on the information theory and the mathematical morphology; the information theory and the mathematical morphology are combined together to extract and link the road segments to form a road network and its nodes. We, therefore, have to define objects as sets of pixels and to study the shape of these objects and the relations that exist between them. In this approach, geometric and radiometric features of roads are integrated by a cost function and a set of selected points of a crossing road. Its performances were tested on satellite images of Algeria country.

Keywords: satellite image, road network, nodes, image analysis and processing

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Authors: Rudi Hartono, Bambang Purwanto

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The translation quality of food and drink labels from Indonesian into English is poor because the translation is not accurate, less natural, and difficult to read. The label translation can be found in some cans packages of food and drink products produced and marketed by several companies in Indonesia. If this problem is left unchecked, it will lead to a misunderstanding on the translation results and make consumers confused. This study was conducted to analyze the translation errors on food and drink products labels and formulate the solution for the better translation quality. The research design was the evaluation research with a holistic criticism approach. The data used were words, phrases, and sentences translated from Indonesian to English language printed on food and drink product labels. The data were processed by using Interactive Model Analysis that carried out three main steps: collecting, classifying, and verifying data. Furthermore, the data were analyzed by using content analysis to view the accuracy, naturalness, and readability of translation. The results showed that the translation quality of food and drink product labels from Indonesian to English has the level of accuracy (60%), level of naturalness (50%), and level readability (60%). This fact needs a help to create an effective strategy for translating food and drink product labels later.

Keywords: translation quality, food and drink product labels, a holistic criticism approach, interactive model, content analysis

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Authors: İmren Öztürk Yılmaz, Abdullah Yasin Bilici, Yasin Atalay Candemir

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The system consists of 4 main elements: motion system, image acquisition system, image processing software, and control interface. The parts coming out of the production line to enter the image processing system with the conveyor belt at the end of the line. The 3D scanning of the produced part is performed with the laser scanning system integrated into the system entry side. With the 3D scanning method, it is determined at what position and angle the parts enter the system, and according to the data obtained, parameters such as part origin and conveyor speed are calculated with the designed software, and the robot is informed about the position where it will take part. The robot, which receives the information, takes the produced part on the belt conveyor and shows it to high-resolution cameras for quality control. Measurement processes are carried out with a maximum error of 20 microns determined by the experiments.

Keywords: quality control, industry 4.0, image processing, automated fault detection, digital visual inspection

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Authors: Ashi Gautam, Isha Shukla, Akhil Seghal

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Biosensors are analytical devices that use a biological sensing element to detect and measure a specific chemical substance or biomolecule in a sample. These devices are widely used in various fields, including medical diagnostics, environmental monitoring, and food analysis, due to their high specificity, sensitivity, and selectivity. In this research paper, a machine learning model is proposed for predicting the suitability of skin care products based on biosensor readings. The proposed model takes in features extracted from biosensor readings, such as biomarker concentration, skin hydration level, inflammation presence, sensitivity, and free radicals, and outputs the most appropriate skin care product for an individual. This model is trained on a dataset of biosensor readings and corresponding skin care product information. The model's performance is evaluated using several metrics, including accuracy, precision, recall, and F1 score. The aim of this research is to develop a personalised skin care product recommendation system using biosensor data. By leveraging the power of machine learning, the proposed model can accurately predict the most suitable skin care product for an individual based on their biosensor readings. This is particularly useful in the skin care industry, where personalised recommendations can lead to better outcomes for consumers. The developed model is based on supervised learning, which means that it is trained on a labeled dataset of biosensor readings and corresponding skin care product information. The model uses these labeled data to learn patterns and relationships between the biosensor readings and skin care products. Once trained, the model can predict the most suitable skin care product for an individual based on their biosensor readings. The results of this study show that the proposed machine learning model can accurately predict the most appropriate skin care product for an individual based on their biosensor readings. The evaluation metrics used in this study demonstrate the effectiveness of the model in predicting skin care products. This model has significant potential for practical use in the skin care industry for personalised skin care product recommendations. The proposed machine learning model for predicting the suitability of skin care products based on biosensor readings is a promising development in the skin care industry. The model's ability to accurately predict the most appropriate skin care product for an individual based on their biosensor readings can lead to better outcomes for consumers. Further research can be done to improve the model's accuracy and effectiveness.

Keywords: biosensors, data model, machine learning, skin care

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Authors: Behnaz Sohani, Sahand Shahalinezhad, Amir Rahmani, Aliyu Aliyu

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Recently, medical imaging and specifically medical image processing is becoming one of the most dynamically developing areas of medical science. It has led to the emergence of new approaches in terms of the prevention, diagnosis, and treatment of various diseases. In the process of diagnosis of lung cancer, medical professionals rely on computed tomography (CT) scans, in which failure to correctly identify masses can lead to incorrect diagnosis or sampling of lung tissue. Identification and demarcation of masses in terms of detecting cancer within lung tissue are critical challenges in diagnosis. In this work, a segmentation system in image processing techniques has been applied for detection purposes. Particularly, the use and validation of a novel lung cancer detection algorithm have been presented through simulation. This has been performed employing CT images based on multilevel thresholding. The proposed technique consists of segmentation, feature extraction, and feature selection and classification. More in detail, the features with useful information are selected after featuring extraction. Eventually, the output image of lung cancer is obtained with 96.3% accuracy and 87.25%. The purpose of feature extraction applying the proposed approach is to transform the raw data into a more usable form for subsequent statistical processing. Future steps will involve employing the current feature extraction method to achieve more accurate resulting images, including further details available to machine vision systems to recognise objects in lung CT scan images.

Keywords: lung cancer detection, image segmentation, lung computed tomography (CT) images, medical image processing

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Authors: Lucia Steenkamp, Chris V. D. Westhuyzen, Kgama Mathiba

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Ambergris, and more specifically its oxidation product (–)-ambrafuran, is a scarce, valuable, and sought-after perfumery ingredient. The material is used as a fixative agent to stabilise perfumes in formulations by reducing the evaporation rate of volatile substances. Ambergris is a metabolic product of the sperm whale (Physeter macrocephatus L.), resulting from intestinal irritation. Chemically, (–)-ambrafuran is produced from the natural product sclareol in eight synthetic steps – in the process using harsh and often toxic chemicals to do so. An overall yield of no more than 76% can be achieved in some routes, but generally, this is lower. A new 'green' route has been developed in our laboratory in which sclareol, extracted from the Clary sage plant, is converted to (–)-ambrafuran in two steps with an overall yield in excess of 80%. The first step uses a microorganism, Hyphozyma roseoniger, to bioconvert sclareol to an intermediate diol using substrate concentrations up to 50g/L. The yield varies between 90 and 67% depending on the substrate concentration used. The purity of the diol product is 95%, and the diol is used without further purification in the next step. The intermediate diol is then cyclodehydrated to the final product (–)-ambrafuran using a zeolite, which is not harmful to the environment and is readily recycled. The yield of the product is 96%, and following a single recrystallization, the purity of the product is > 99.5%. A preliminary LC-MS study of the bioconversion identified several intermediates produced in the fermentation broth under oxygen-restricted conditions. Initially, a short-lived ketone is produced in equilibrium with a more stable pyranol, a key intermediate in the process. The latter is oxidised under Norrish type I cleavage conditions to yield an acetate, which is hydrolysed either chemically or under lipase action to afford the primary fermentation product, an intermediate diol. All the intermediates identified point to the likely CYP450 action as the key enzyme(s) in the mechanism. This invention is an exceptional example of how the power of biocatalysis, combined with a mild, benign chemical step, can be deployed to replace a total chemical synthesis of a specific chiral antipode of a commercially relevant material.

Keywords: ambrafuran, biocatalysis, fragrance, microorganism

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Authors: Li-Ting Huang, Yu-Hsiang Shen, Cing-Ciao Ke, Sheng-Pin Tseng, Fan-Pin Tseng, Yu-Ching Ni, Chia-Yu Lin

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Chest radiography is the most common technique for the diagnosis and follow-up of pulmonary diseases. However, the lesions superimposed with normal structures are difficult to be detected in chest radiography. Chest tomosynthesis is a relatively new technique to obtain 3D section images from a set of low-dose projections acquired over a limited angular range. However, there are some limitations with chest tomosynthesis. Patients undergoing tomosynthesis have to be able to hold their breath firmly for 10 seconds. A digital tomosynthesis system with advanced reconstruction algorithm and high-stability motion mechanism was developed by our research group. The potential for the system to perform a bidirectional chest scan within 10 seconds is expected. The purpose of this study is to realize the influences of the scan speed on the image quality for our digital tomosynthesis system. The major factors that lead image blurring are the motion of the X-ray source and the patient. For the fore one, an experiment of imaging a chest phantom with three different scan speeds, which are 6 cm/s, 8 cm/s, and 15 cm/s, was proceeded to understand the scan speed influences on the image quality. For the rear factor, a normal SD (Sprague-Dawley) rat was imaged with it alive and sacrificed to assess the impact on the image quality due to breath motion. In both experiments, the profile of the ROIs (region of interest) and the CNRs (contrast-to-noise ratio) of the ROIs to the normal tissue of the reconstructed images was examined to realize the degradations of the qualities of the images. The preliminary results show that no obvious degradation of the image quality was observed with increasing scan speed, possibly due to the advanced designs for the hardware and software of the system. It implies that higher speed (15 cm/s) than that of the commercialized tomosynthesis system (12 cm/s) for the proposed system is achieved, and therefore a complete chest scan within 10 seconds is expected.

Keywords: chest radiography, digital tomosynthesis, image quality, scan speed

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Authors: Abderrahim Elmoataz

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More and more contemporary applications involve data in the form of functions defined on irregular and topologically complicated domains (images, meshs, points clouds, networks, etc). Such data are not organized as familiar digital signals and images sampled on regular lattices. However, they can be conveniently represented as graphs where each vertex represents measured data and each edge represents a relationship (connectivity or certain affinities or interaction) between two vertices. Processing and analyzing these types of data is a major challenge for both image and machine learning communities. Hence, it is very important to transfer to graphs and networks many of the mathematical tools which were initially developed on usual Euclidean spaces and proven to be efficient for many inverse problems and applications dealing with usual image and signal domains. Historically, the main tools for the study of graphs or networks come from combinatorial and graph theory. In recent years there has been an increasing interest in the investigation of one of the major mathematical tools for signal and image analysis, which are Partial Differential Equations (PDEs) variational methods on graphs. The normalized p-laplacian operator has been recently introduced to model a stochastic game called tug-of-war-game with noise. Part interest of this class of operators arises from the fact that it includes, as particular case, the infinity Laplacian, the mean curvature operator and the traditionnal Laplacian operators which was extensiveley used to models and to solve problems in image processing. The purpose of this paper is to introduce and to study a new class of normalized p-Laplacian on graphs. The introduction is based on the extension of p-harmonious function introduced in as discrete approximation for both infinity Laplacian and p-Laplacian equations. Finally, we propose to use these operators as a framework for solving many inverse problems in image processing.

Keywords: normalized p-laplacian, image processing, stochastic game, inverse problems

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Authors: Sabine Ambros, Ulrich Kulozik

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Berries such as blue- and raspberries belong to the most valuable fruits. To preserve the characteristic flavor and the high contents of vitamins and anthocyanins, the very sensitive berries are usually dried by lyophilization. As this method is very time- and energy-consuming, the dried fruit is extremely expensive. However, healthy snack foods are growing in popularity. Especially dried fruit free of any additives or additional sugar are more and more asked for. To make these products affordable, the fruits have to be dried by a method that is more energy-efficient than freeze drying but reveals the same high product quality. The additional insertion of microwaves to a freeze drying process was examined in this work to overcome the inconveniences of freeze drying. As microwaves penetrate the product volumetrically, sublimation takes place simultaneously all over the product and leads to a many times shorter process duration. A range of microwave and pressure settings was applied to find the optimum drying condition. The influence of the process parameters microwave power and chamber pressure on drying kinetics, product temperature and product quality was investigated to find the best condition for an energy-efficient process with high product quality. The product quality was evaluated by rehydration capacitiy, crispiness, shrinkage, color, vitamin C content and antioxidative capacity. The conclusion could be drawn that microwave freeze dried berries were almost equal to freeze dried fruit in all measured quality parameters or even could overcome it. Additionally, sensory evaluations could confirm the analytical studies. Drying time could be reduced by more than 75% at much lower energy consumption rates. Thus, an energy-efficient and cost saving method compared to the conventional freeze drying technique for the gentle production of tasty fruit or vegetable snacks has been found. This technique will make dried high-quality snacks available for many of consumers.

Keywords: blueberries, freeze drying, microwave freeze drying, process parameters, product quality

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Authors: Michael Zenker, Henrik Prinzhorn, Christian Böning, Tom Strating

Abstract:

Large-scale products are often assembled according to the job-site principle, meaning that during the assembly the product is located at a fixed position, while the area requirements are constantly changing. On one hand, the product itself is growing with each assembly step, whereas varying areas for storage, machines or working areas are temporarily required. This is an important factor when arranging products to be assembled within the factory. Currently, it is common to reserve a fixed area for each product to avoid overlaps or collisions with the other assemblies. Intending to be large enough to include the product and all adjacent areas, this reserved area corresponds to the superposition of the maximum extents of all required areas of the product. In this procedure, the reserved area is usually poorly utilized over the course of the entire assembly process; instead a large part of it remains unused. If the available area is a limited resource, a systematic arrangement of the products, which complies with the dynamic area requirements, will lead to an increased area utilization and productivity. This paper presents the results of a study on the arrangement of assembly objects assuming dynamic, competing area requirements. First, the problem situation is extensively explained, and existing research on associated topics is described and evaluated on the possibility of an adaptation. Then, a newly developed mathematical optimization model is introduced. This model allows an optimal arrangement of dynamic areas, considering logical and practical constraints. Finally, in order to quantify the potential of the developed method, some test series results are presented, showing the possible increase in area utilization.

Keywords: dynamic area requirements, facility layout problem, optimization model, product assembly

Procedia PDF Downloads 222

Authors: Magdi Elmessiry, Adel Elmessiry

Abstract:

The fashion industry represents a significant portion of the global gross domestic product, however, it is plagued by cheap imitators that infringe on the trademarks which destroys the fashion industry's hard work and investment. While eventually the copycats would be found and stopped, the damage has already been done, sales are missed and direct and indirect jobs are lost. The infringer thrives on two main facts: the time it takes to discover them and the lack of tracking technologies that can help the consumer distinguish them. Blockchain technology is a new emerging technology that provides a distributed encrypted immutable and fault resistant ledger. Blockchain presents a ripe technology to resolve the infringement epidemic facing the fashion industry. The significance of the study is that a new approach leveraging the state of the art blockchain technology coupled with artificial intelligence is used to create a framework addressing the fashion infringement problem. It transforms the current focus on legal enforcement, which is difficult at best, to consumer awareness that is far more effective. The framework, Crypto CopyCat, creates an immutable digital asset representing the actual product to empower the customer with a near real time query system. This combination emphasizes the consumer's awareness and appreciation of the product's authenticity, while provides real time feedback to the producer regarding the fake replicas. The main findings of this study are that implementing this approach can delay the fake product penetration of the original product market, thus allowing the original product the time to take advantage of the market. The shift in the fake adoption results in reduced returns, which impedes the copycat market and moves the emphasis to the original product innovation.

Keywords: fashion, infringement, blockchain, artificial intelligence, textiles supply chain

Procedia PDF Downloads 251

Authors: Michael J. Hahn

Abstract:

Docker is a powerful tool used by many companies such as PayPal, MetLife, Expedia, Visa, and many others. Docker works by bundling multiple applications, binaries, and libraries together on top of an operating system image called a container. The container runs on a Docker engine that in turn runs on top of a standard operating system. This centralization saves a lot of system resources. In this paper, we will be demonstrating how to bypass Transport Layer Security and execute remote code within Docker containers built on a base image of Alpine Linux version 3.7.0 through the use of .apk files due to flaws in the Alpine Linux package management program. This exploit renders any applications built using Docker with a base image of Alpine Linux vulnerable to unwanted outside forces.

Keywords: cloud, cryptography, Docker, Linux, security

Procedia PDF Downloads 188

Authors: Fumihiko Isada, Yuriko Isada

Abstract:

The aim of this research is to clarify the difference by industry segment or product characteristics as regards organisation management for an open innovation to raise R&D performance. In particular, the trait of the pharmaceutical industry is defined in comparison with IT component industry segment. In considering open innovation, both inter-organisational relation and the management in an organisation are important issues. As methodology, a questionnaire was conducted. In conclusion, suitable organisation management according to the difference in industry segment or product characteristics became clear.

Keywords: empirical study, industry segment, open innovation, product-development organisation pattern

Procedia PDF Downloads 411