Search results for: uncertainty of processing times

Authors: Natália B. Pompermayer, Mariana B. Porto, Elizabeth F. Souza

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Nanophotocatalysts such as titanium (TiO2), zinc (ZnO), and iron (Fe2O3) oxides can be used in organic pollutants oxidation, and in many other applications. But among the challenges for technological application (scale-up) of the nanotechnology scientific developments two aspects are still little explored: research on environmental risk of the nanomaterials preparation methods, and the study of nanomaterials properties and/or performance variability. The environmental analysis was performed for six different methods of ZnO nanoparticles synthesis, and showed that it is possible to identify the more environmentally compatible process even at laboratory scale research. The obtained ZnO nanoparticles were tested as photocatalysts, and increased the degradation rate of the Rhodamine B dye up to 30 times.

Keywords: Environmental impact analysis, inorganic nanoparticles, photocatalysts.

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Authors: N. Nouali, H. Drias, A. Doucet

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During more than a decade, many proposals and standards have been designed to deal with the mobility issues; however, there are still some serious limitations in basing solutions on them. In this paper we discuss the possibility of handling mobility at the application layer. We do this while revisiting the conventional implementation of the Two Phase Commit (2PC) protocol which is a fundamental asset of transactional technology for ensuring the consistent commitment of distributed transactions. The solution is based on an execution framework providing an efficient extension that is aware of the mobility and preserves the 2PC principle.

Keywords: Application layer, distributed mobile protocols, mobility management, mobile transaction processing.

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Authors: Kati Manskinen, Risto Pöykiö, Hannu Nurmesniemi

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In an assessment of the extractability of metals in green liquor dregs from the chemical recovery circuit of semichemical pulp mill, extractable concentrations of heavy metals in artificial gastric fluid were between 10 (Ni) and 717 (Zn) times higher than those in artificial sweat fluid. Only Al (6.7 mg/kg; d.w.), Ni (1.2 mg/kg; d.w.) and Zn (1.8 mg/kg; d.w.) showed extractability in the artificial sweat fluid, whereas Al (730 mg/kg; d.w.), Ba (770 mg/kg; d.w.) and Zn (1290 mg/kg; d.w.) showed clear extractability in the artificial gastric fluid. As certain heavy metals were clearly soluble in the artificial gastric fluid, the careful handling of this residue is recommended in order to prevent the penetration of green liquor dregs across the human gastrointestinal tract.

Keywords: Dregs, non-process elements, pulping, waste.

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Authors: A. G. Gashua, T. T. Bello, I. Alhassan, K. K. Gwiokura

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Weeds are known to interfere seriously with crop growth, thereby affecting the productivity and quality of crops. Crops are also known to compete for natural growth resources if they are not adequately spaced, also affecting the performance of the growing crop. Farmers grow cowpea in mixtures with cereals and this is known to affect its yield. For this reason, a field experiment was conducted at Yobe State College of Agriculture Gujba, Damaturu station in the 2014 and 2015 rainy seasons to determine the appropriate intra row spacing and weeding regime for optimum growth and yield of cowpea (Vigna unguiculata L.) in pure stand in Sudan Savanna ecology. The treatments consist of three levels of spacing within rows (20 cm, 30 cm and 40 cm) and four weeding regimes (none, once at 3 weeks after sowing (WAS), twice at 3 and 6WAS, thrice at 3WAS, 6WAS and 9WAS); arranged in a Randomized Complete Block Design (RCBD) and replicated three times. The variety used was the local cowpea variety (white, early and spreading) commonly grown by farmers. The growth and yield data were collected and subjected to analysis of variance using SAS software, and the significant means were ranked by Students Newman Keul’s test (SNK). The findings of this study revealed better crop performance in 2015 than in 2014 despite poor soil condition. Intra row spacing significantly influenced vegetative growth especially the number of main branches, leaves and canopy spread at 6WAS and 9WAS with the highest values obtained at wider spacing (40 cm). The values obtained in 2015 doubled those obtained in 2014 in most cases. Spacing also significantly affected the number of pods in 2015, seed weight in both years and grain yield in 2014 with the highest values obtained when the crop was spaced at 30-40 cm. Similarly, weeding regime significantly influenced almost all the growth attributes of cowpea with higher values obtained from where cowpea was weeded three times at 3-week intervals, though statistically similar results were obtained even from where cowpea was weeded twice. Weeding also affected the entire yield and yield components in 2015 with the highest values obtained with increase weeding. Based on these findings, it is recommended that spreading cowpea varieties should be grown at 40 cm (or wider spacing) within rows and be weeded twice at three-week intervals for better crop performance in related ecologies.

Keywords: Intra row spacing, local cowpea, Nigeria, weeding.

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Authors: Alexey V. Klyuev, Valery P. Samarin, Viktor F. Klyuev

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A power measurement algorithm of the input mix components of the noise signal and narrowband interference is considered using functional transformations of the input mix in the postdetection processing channel. The algorithm efficiency analysis has been carried out for different interference-to-signal ratio. Algorithm performance features have been explored by numerical experiment results.

Keywords: Noise signal, continuous narrowband interference, signal power, spectrum width, detection.

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Authors: Khashayar Jafari, Mostafa Jafarian Abyaneh, Vahab Toufigh

Abstract:

Polymer concrete (PC) is a distinct concrete with superior characteristics in comparison to ordinary cement concrete. It has become well-known for its applications in thin overlays, floors and precast components. In this investigation, the mechanical properties of PC with different epoxy resin contents, ordinary cement concrete (OCC) and lightweight concrete (LC) have been studied under uniaxial compression test. The study involves five types of concrete, with each type being tested four times. Their complete elastic-plastic behavior was compared with each other through the measurement of volumetric strain during the tests. According to the results, PC showed higher strength, ductility and energy absorption with respect to OCC and LC.

Keywords: Polymer concrete, ordinary cement concrete, lightweight concrete, uniaxial compression test, volumetric strain.

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Authors: Aytunc Durlanik, Ibrahim Sogukpinar

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SIP (Session Initiation Protocol), using HTML based call control messaging which is quite simple and efficient, is being replaced for VoIP networks recently. As for authentication and authorization purposes there are many approaches and considerations for securing SIP to eliminate forgery on the integrity of SIP messages. On the other hand Elliptic Curve Cryptography has significant advantages like smaller key sizes, faster computations on behalf of other Public Key Cryptography (PKC) systems that obtain data transmission more secure and efficient. In this work a new approach is proposed for secure SIP authentication by using a public key exchange mechanism using ECC. Total execution times and memory requirements of proposed scheme have been improved in comparison with non-elliptic approaches by adopting elliptic-based key exchange mechanism.

Keywords: SIP, Elliptic Curve Cryptography, voice over IP.

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Authors: Nishi Bhuvandas, P. V. Timbadiya, P. L. Patel, P. D. Porey

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Recent perceived climate variability raises concerns with unprecedented hydrological phenomena and extremes. Distribution and circulation of the waters of the Earth become increasingly difficult to determine because of additional uncertainty related to anthropogenic emissions. The world wide observed changes in the large-scale hydrological cycle have been related to an increase in the observed temperature over several decades. Although the effect of change in climate on hydrology provides a general picture of possible hydrological global change, new tools and frameworks for modelling hydrological series with nonstationary characteristics at finer scales, are required for assessing climate change impacts. Of the downscaling techniques, dynamic downscaling is usually based on the use of Regional Climate Models (RCMs), which generate finer resolution output based on atmospheric physics over a region using General Circulation Model (GCM) fields as boundary conditions. However, RCMs are not expected to capture the observed spatial precipitation extremes at a fine cell scale or at a basin scale. Statistical downscaling derives a statistical or empirical relationship between the variables simulated by the GCMs, called predictors, and station-scale hydrologic variables, called predictands. The main focus of the paper is on the need for using statistical downscaling techniques for projection of local hydrometeorological variables under climate change scenarios. The projections can be then served as a means of input source to various hydrologic models to obtain streamflow, evapotranspiration, soil moisture and other hydrological variables of interest.

Keywords: Climate Change, Downscaling, GCM, RCM.

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Authors: Parvinder S. Sandhu, Iqbaldeep Kaur, Amit Verma, Samriti Jindal, Shailendra Singh

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Biometric measures of one kind or another have been used to identify people since ancient times, with handwritten signatures, facial features, and fingerprints being the traditional methods. Of late, Systems have been built that automate the task of recognition, using these methods and newer ones, such as hand geometry, voiceprints and iris patterns. These systems have different strengths and weaknesses. This work is a two-section composition. In the starting section, we present an analytical and comparative study of common biometric techniques. The performance of each of them has been viewed and then tabularized as a result. The latter section involves the actual implementation of the techniques under consideration that has been done using a state of the art tool called, MATLAB. This tool aids to effectively portray the corresponding results and effects.

Keywords: Matlab, Recognition, Facial Vectors, Functions.

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Authors: Yukiko Sasaki Alam, Shahid Alam

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Syntactic parsing is vital for semantic treatment by many applications related to natural language processing (NLP), because form and content coincide in many cases. However, it has not yet reached the levels of reliable performance. By manually examining and analyzing individual machine translation output errors that involve syntax as well as semantics, this study attempts to discover what is required for improving syntactic and semantic parsing.

Keywords: Machine translation, error analysis, syntactic errors, knowledge required for parsing.

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Authors: C. Bay, A. Mahr, H. Groneberg, F. Döpper

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Additive Manufacturing processes are becoming increasingly established in the industry for the economic production of complex prototypes and functional components. Laser beam melting (LBM), the most frequently used Additive Manufacturing technology for metal parts, has been gaining in industrial importance for several years. The LBM process chain – from material storage to machine set-up and component post-processing – requires many manual operations. These steps often depend on the manufactured component and are therefore not standardized. These operations are often not performed in a standardized manner, but depend on the experience of the machine operator, e.g., levelling of the build plate and adjusting the first powder layer in the LBM machine. This lack of standardization limits the reproducibility of the component quality. When processing metal powders with inhalable and alveolar particle fractions, the machine operator is at high risk due to the high reactivity and the toxic (e.g., carcinogenic) effect of the various metal powders. Faulty execution of the operation or unintentional omission of safety-relevant steps can impair the health of the machine operator. In this paper, all the steps of the LBM process chain are first analysed in terms of their influence on the two aforementioned challenges: reproducibility and work safety. Standardization to avoid errors increases the reproducibility of component quality as well as the adherence to and correct execution of safety-relevant operations. The corresponding lean method 5S will therefore be applied, in order to develop approaches in the form of recommended actions that standardize the work processes. These approaches will then be evaluated in terms of ease of implementation and their potential for improving reproducibility and work safety. The analysis and evaluation showed that sorting tools and spare parts as well as standardizing the workflow are likely to increase reproducibility. Organizing the operational steps and production environment decreases the hazards of material handling and consequently improves work safety.

Keywords: Additive manufacturing, lean production, reproducibility, work safety.

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Authors: L. Korpinen, R. Pääkkönen, F. Gobba

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There has been discussion if the use of mobile phones causes accidents. We studied workers’ accidents and near accidents related to the use of phones. This study is part of a large cross-sectional study that was carried out on 15,000 working-age Finns. We noticed that there were 4–5 times more close call situations than accidents connected to mobile phones and also work related accidents were fewer than leisure related. There are confusing parameters like the use of mobile phones at work, differences in work content between women and men.

Keywords: Blue-collar workers, accident, cell phone, close call situation.

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Authors: Marco Kennemann, Steffen C. Eickemeyer, Peter Nyhuis

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An increasingly dynamic and complex environment poses huge challenges to production enterprises, especially with regards to logistics. The Logistic Operating Curve Theory, developed at the Institute of Production Systems and Logistics (IFA) of the Leibniz University of Hanover, is a recognized approach to describing logistic interactions, nevertheless, it reaches its limits when it comes to the dynamic aspects. In order to facilitate a timely and optimal Logistic Positioning a method is developed for quickly and reliably identifying dynamic processing states.

Keywords: Dynamics, Logistic Operating Curves, Production Logistics, Production Planning and Control

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Authors: Yu-Wei Chen, Li-Ren Han

Abstract:

In this paper, we employ the approach of linear programming to propose a new interactive broadcast method. In our method, a film S is divided into n equal parts and broadcast via k channels. The user simultaneously downloads these segments from k channels into the user-s set-top-box (STB) and plays them in order. Our method assumes that the initial p segments will not have fast-forwarding capabilities. Every time the user wants to initiate d times fast-forwarding, according to our broadcasting strategy, the necessary segments already saved in the user-s STB or are just download on time for playing. The proposed broadcasting strategy not only allows the user to pause and rewind, but also to fast-forward.

Keywords: Broadcasting, Near Video-on-Demand (VOD), Linear Programming, Video-Cassette-Recorder (VCR) Functions, Waiting Time.

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Authors: R. Sekula

Abstract:

Epoxy composites are broadly used as an electrical insulation for the high voltage applications since only such materials can fulfill particular mechanical, thermal, and dielectric requirements. However, properties of the final product are strongly dependent on proper manufacturing process with minimized material failures, as too large shrinkage, voids and cracks. Therefore, application of proper materials (epoxy, hardener, and filler) and process parameters (mold temperature, filling time, filling velocity, initial temperature of internal parts, gelation time), as well as design and geometric parameters are essential features for final quality of the produced components. In this paper, an approach for three-dimensional modeling of all molding stages, namely filling, curing and post-curing is presented. The reactive molding simulation tool is based on a commercial CFD package, and include dedicated models describing viscosity and reaction kinetics that have been successfully implemented to simulate the reactive nature of the system with exothermic effect. Also a dedicated simulation procedure for stress and shrinkage calculations, as well as simulation results are presented in the paper. Second part of the paper is dedicated to recent developments on formulations of functional composites for electrical insulation applications, focusing on thermally conductive materials. Concepts based on filler modifications for epoxy electrical composites have been presented, including the results of the obtained properties. Finally, having in mind tough environmental regulations, in addition to current process and design aspects, an approach for product re-design has been presented focusing on replacement of epoxy material with the thermoplastic one. Such “design-for-recycling” method is one of new directions associated with development of new material and processing concepts of electrical products and brings a lot of additional research challenges. For that, one of the successful products has been presented to illustrate the presented methodology.

Keywords: Curing, epoxy insulation, numerical simulations, recycling.

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Authors: Abbas Teimouri, Alireza Najafi Chermahini, Leila Ghorbanian

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An efficient and green protocol for the synthesis of α- aminonitriles derivatives by one-pot reaction of different aldehydes with amines and trimethylsilyl cyanides has been developed using natural alumina, alumina sulfuric acid (ASA), nano-γ-alumina, nanoalumina sulfuric acid (nano-ASA) under microwave irradiation and solvent-free conditions. The advantages of methods are short reaction times, high yields, milder conditions and easy work up. The catalysts can be recovered for the subsequent reactions and reused without any appreciable loss of efficiency.

Keywords: Nano-γ-alumina, nano-alumina sulfuric acid, green synthesis, microwave irradiation, α-aminonitriles derivatives.

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Authors: Aung Myo Thu, Sang Eon Jeon, Yung Hwan Byun, Soo Hyung Park

Abstract:

The unsteady flow field around oscillating OA-209 airfoil at a Reynolds number of 3.5×105 were investigated. Three different reduced frequencies were tested in order to see how it affects the hysteresis loop of an airfoil. At a reduced frequency of 0.05 the deep dynamic stall phenomenon was observed. Lift overshooting was observed as a result of dynamic stall vortex (DSV) shedding. Further investigation was carried out to find out the cause of DSV formation and shedding over airfoil. Particle image velocimetry (PIV) and CFD tools were used and it was found out that dynamic stall separation (DSS), which is separated from leading edge separation (LES) and trailing edge separation (TES), triggered the dynamic stall vortex (DSV).

Keywords: Airfoil Flow, CFD, PIV, Dynamic Stall, Flow Separation.

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Authors: P. Ashok, G. M. Kadhar Nawaz

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Rough set theory is used to handle uncertainty and incomplete information by applying two accurate sets, Lower approximation and Upper approximation. In this paper, the rough clustering algorithms are improved by adopting the Similarity, Dissimilarity–Similarity and Entropy based initial centroids selection method on three different clustering algorithms namely Entropy based Rough K-Means (ERKM), Similarity based Rough K-Means (SRKM) and Dissimilarity-Similarity based Rough K-Means (DSRKM) were developed and executed by yeast dataset. The rough clustering algorithms are validated by cluster validity indexes namely Rand and Adjusted Rand indexes. An experimental result shows that the ERKM clustering algorithm perform effectively and delivers better results than other clustering methods. Outlier detection is an important task in data mining and very much different from the rest of the objects in the clusters. Entropy based Rough Outlier Factor (EROF) method is seemly to detect outlier effectively for yeast dataset. In rough K-Means method, by tuning the epsilon (ᶓ) value from 0.8 to 1.08 can detect outliers on boundary region and the RKM algorithm delivers better results, when choosing the value of epsilon (ᶓ) in the specified range. An experimental result shows that the EROF method on clustering algorithm performed very well and suitable for detecting outlier effectively for all datasets. Further, experimental readings show that the ERKM clustering method outperformed the other methods.

Keywords: Clustering, Entropy, Outlier, Rough K-Means, validity index.

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Authors: R. Arulmurugan, P. Sengottuvelan

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Object detection using Wavelet Neural Network (WNN) plays a major contribution in the analysis of image processing. Existing cluster-based algorithm for co-saliency object detection performs the work on the multiple images. The co-saliency detection results are not desirable to handle the multi scale image objects in WNN. Existing Super Resolution (SR) scheme for landmark images identifies the corresponding regions in the images and reduces the mismatching rate. But the Structure-aware matching criterion is not paying attention to detect multiple regions in SR images and fail to enhance the result percentage of object detection. To detect the objects in the high-resolution remote sensing images, Tagged Grid Matching (TGM) technique is proposed in this paper. TGM technique consists of the three main components such as object determination, object searching and object verification in WNN. Initially, object determination in TGM technique specifies the position and size of objects in the current image. The specification of the position and size using the hierarchical grid easily determines the multiple objects. Second component, object searching in TGM technique is carried out using the cross-point searching. The cross out searching point of the objects is selected to faster the searching process and reduces the detection time. Final component performs the object verification process in TGM technique for identifying (i.e.,) detecting the dissimilarity of objects in the current frame. The verification process matches the search result grid points with the stored grid points to easily detect the objects using the Gabor wavelet Transform. The implementation of TGM technique offers a significant improvement on the multi-object detection rate, processing time, precision factor and detection accuracy level.

Keywords: Object Detection, Cross-point Searching, Wavelet Neural Network, Object Determination, Gabor Wavelet Transform, Tagged Grid Matching.

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Authors: Amanzhol Kalysh, Didar Kassymova, Aliya Isaeva

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Practices of food sharing as part of the brotherhood and hospitality interpretation have been essential part of the Kazakh ethnic culture since early times. Dialogue in time and space between Kazakhs through differences in food interpretation among the ethnic repatriates may become a link connecting them and platform for stable relations with the host society or serious barrier on the way of their integration in the Kazakhstani society. The article elucidates by the field materials how some aspects of food culture differences among ethnic Kazakhs living abroad (XUAR of China) and ethnic repatriates in Kazakhstan may influence their integration path.

Keywords: Ethnic repatriation, food canon, Kazakh identity, oralman.

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Authors: Shih-Yan Chen, Shin-Shin Kao

Abstract:

In this paper, a thorough review about dual-cubes, DCn, the related studies and their variations are given. DCn was introduced to be a network which retains the pleasing properties of hypercube Qn but has a much smaller diameter. In fact, it is so constructed that the number of vertices of DCn is equal to the number of vertices of Q2n +1. However, each vertex in DCn is adjacent to n + 1 neighbors and so DCn has (n + 1) × 2^2n edges in total, which is roughly half the number of edges of Q2n+1. In addition, the diameter of any DCn is 2n +2, which is of the same order of that of Q2n+1. For selfcompleteness, basic definitions, construction rules and symbols are provided. We chronicle the results, where eleven significant theorems are presented, and include some open problems at the end.

Keywords: Hypercubes, dual-cubes, fault-tolerant hamiltonian property, dual-cube extensive networks, dual-cube-like networks.

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Authors: Jatinderkumar R. Saini, Apurva A. Desai

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In recent times, the problem of Unsolicited Bulk Email (UBE) or commonly known as Spam Email, has increased at a tremendous growth rate. We present an analysis of survey based on classifications of UBE in various research works. There are many research instances for classification between spam and non-spam emails but very few research instances are available for classification of spam emails, per se. This paper does not intend to assert some UBE classification to be better than the others nor does it propose any new classification but it bemoans the lack of harmony on number and definition of categories proposed by different researchers. The paper also elaborates on factors like intent of spammer, content of UBE and ambiguity in different categories as proposed in related research works of classifications of UBE.

Keywords: E-mail, Scams, Spam Email, Unsolicited Bulk Email(UBE)

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Authors: András Barta, István Vajk

Abstract:

In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem.

Keywords: Object recognition, Bayesian network, Wavelets, Document processing.

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Authors: Shan Gao

Abstract:

This paper treats a discrete-time finite buffer batch arrival queue with a single working vacation and partial batch rejection in which the inter-arrival and service times are, respectively, arbitrary and geometrically distributed. The queue is analyzed by using the supplementary variable and the imbedded Markov-chain techniques. We obtain steady-state system length distributions at prearrival, arbitrary and outside observer-s observation epochs. We also present probability generation function (p.g.f.) of actual waiting-time distribution in the system and some performance measures.

Keywords: Discrete-time, finite buffer, single working vacation, batch arrival, partial rejection.

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Authors: Daesung Moon, Woo-Yong Choi, Kiyoung Moon

Abstract:

Fuzzy fingerprint vault is a recently developed cryptographic construct based on the polynomial reconstruction problem to secure critical data with the fingerprint data. However, the previous researches are not applicable to the fingerprint having a few minutiae since they use a fixed degree of the polynomial without considering the number of fingerprint minutiae. To solve this problem, we use an adaptive degree of the polynomial considering the number of minutiae extracted from each user. Also, we apply multiple polynomials to avoid the possible degradation of the security of a simple solution(i.e., using a low-degree polynomial). Based on the experimental results, our method can make the possible attack difficult 2192 times more than using a low-degree polynomial as well as verify the users having a few minutiae.

Keywords: Fuzzy vault, fingerprint recognition multiple polynomials.

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Authors: L. Korpinen, P. Taskinen, P. Rautio

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This study aimed to describe procedures that we developed to use in the quantitative, bone-specific SPECT/CT at our hospital. Our procedures included the following questions for choosing imaging protocols, which were based on a clinical doctor's referral: (1) Is she/he a cancer patient or not? (2) Are there any indications of inflammatory rheumatoid arthritis? We performed about 1,106 skeletal scintigraphies over two years. About 394 patients were studied with quantitative bone-specific single-photon emission computed tomography/computerized tomography (SPECT/CT) (i.e., about 36% of all bone scintigraphies). Approximately 64% of the patients were studied using the conventional Anterior-Posterior/Posterior-Anterior imaging. Our procedure has improved efficiency and decreased cycle times.

Keywords: Skeletal scintigraphy, SPECT/CT, imaging.

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Authors: Nahla Ibraheem Jabbar, Monica Mehrotra

Abstract:

This paper used a fuzzy kohonen neural network for medical image segmentation. Image segmentation plays a important role in the many of medical imaging applications by automating or facilitating the diagnostic. The paper analyses the tumor by extraction of the features of (area, entropy, means and standard deviation).These measurements gives a description for a tumor.

Keywords: FCM, features extraction, medical image processing, neural network, segmentation.

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Authors: Rosalba D'onofrio

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It is not easy to imagine how the existing city can be converted to the principles of sustainability, however, the need for innovation, requires a pioneering phase which must address the main problems of rehabilitation of the operating models of the city. Today, however, there is a growing awareness that the identification and implementation of policies and measures to promote the adaptation, resilience and reversibility of the city, require the contribution of our discipline. This breakthrough is present in some recent international experiences of Climate Plans, in which the envisaged measures are closely interwoven with those of urban planning. These experiences, provide some answers principle questions, such as: how the strategies to combat climate can be integrated in the instruments of the local government; what new and specific analysis must be introduced in urban planning in order to understand the issues of urban sustainability, and how the project compares with different spatial scales.

Keywords: Climate change, urban sustainability, urban planning

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Authors: Angelo Corallo, Maria Elena Latino, Marta Menegoli

Abstract:

Agri-food value chain involves various stakeholders with different roles. All of them abide by national and international rules and leverage marketing strategies to advance their products. Food products and related processing phases carry with it a big mole of data that are often not used to inform final customer. Some data, if fittingly identified and used, can enhance the single company, and/or the all supply chain creates a math between marketing techniques and voluntary traceability strategies. Moreover, as of late, the world has seen buying-models’ modification: customer is careful on wellbeing and food quality. Food citizenship and food democracy was born, leveraging on transparency, sustainability and food information needs. Internet of Things (IoT) and Analytics, some of the innovative technologies of Industry 4.0, have a significant impact on market and will act as a main thrust towards a genuine ‘4.0 change’ for agriculture. But, realizing a traceability system is not simple because of the complexity of agri-food supply chain, a lot of actors involved, different business models, environmental variations impacting products and/or processes, and extraordinary climate changes. In order to give support to the company involved in a traceability path, starting from business model analysis and related business process a Framework to Manage Product Data in Agri-Food Supply Chain for Voluntary Traceability was conceived. Studying each process task and leveraging on modeling techniques lead to individuate information held by different actors during agri-food supply chain. IoT technologies for data collection and Analytics techniques for data processing supply information useful to increase the efficiency intra-company and competitiveness in the market. The whole information recovered can be shown through IT solutions and mobile application to made accessible to the company, the entire supply chain and the consumer with the view to guaranteeing transparency and quality.

Keywords: Agriculture 4.0, agri-food supply chain, Industry 4.0, voluntary traceability.

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Authors: Shannon Steinmetz, Ellen Gethner

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In this paper a theoretical foundation is developed to segment, analyze and associate patterns within audio. We explore this on imagery via sonified audio applied to our segmentation framework. The approach involves a geodesic estimator within the statistical manifold, parameterized by musical centricity. We demonstrate viability by processing a database of random imagery to produce statistically significant clusters of similar imagery content.

Keywords: Sonification, musical information geometry, image content extraction, automated quantification, audio segmentation, pattern recognition.

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