Search results for: Mandarin Chinese processing

Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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This study aimed to address the problem of improving the confidence of key points by fusing multi-view information, thereby estimating human posture more accurately. We first obtained multi-view image information and then used the MvP algorithm to fuse this multi-view information together to obtain a set of high-confidence human key points. We used these as the input for the Spatio-Temporal Graph Convolution (ST-GCN). ST-GCN is a deep learning model used for processing spatio-temporal data, which can effectively capture spatio-temporal relationships in video sequences. By using the MvP algorithm to fuse multi-view information and inputting it into the spatio-temporal graph convolution model, this study provides an effective method to improve the accuracy of human posture estimation and provides strong support for further research and application in related fields.

Keywords: multi-view, pose estimation, ST-GCN, joint fusion

Procedia PDF Downloads 71

Authors: Long Kim Vu

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The central processing unit in Electro-Optical devices is a Field-programmable gate array (FPGA) chip package allowing flexible, reconfigurable computing but energy consumption. Because chip package is placed in isolated devices based on IP67 waterproof standard, there is no air circulation and the heat dissipation is a challenge. In this paper, the author successfully modeled a chip package which various interposer materials such as silicon, glass and organics. Computational fluid dynamics (CFD) was utilized to analyze the thermal performance of chip package in the case of considering comprehensive heat transfer modes: conduction, convection and radiation, which proposes equivalent heat dissipation. The logic chip temperature varying with time is compared between the simulation and experiment results showing the excellent correlation, proving the reasonable chip modeling and simulation method.

Keywords: CFD, FPGA, heat transfer, thermal analysis

Procedia PDF Downloads 184

Authors: Ashish Kumar, Tejendra Dixit, I. A. Palani, Vipul Singh

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Zinc oxide, with its interesting properties such as large band gap (3.37eV), high exciton binding energy (60 meV) and intense UV absorption has been studied in literature for various applications viz. optoelectronics, biosensors, UV-photodetectors etc. The performance of ZnO devices is highly influenced by morphologies, size, crystallinity of the ZnO active layer and processing conditions. Recently, our group has shown the influence of the in situ addition of KMnO4 in the precursor solution during the hydrothermal growth of ZnO nanorods (NRs) on their near band edge (NBE) emission. In this paper, we have investigated the effect of post-growth annealing on the variations in NBE and deep level (DL) emissions of as grown ZnO nanorods. These observed results have been explained on the basis of X-ray Diffraction (XRD) and Raman spectroscopic analysis, which clearly show that improved crystalinity and quantum confinement in ZnO nanorods.

Keywords: ZnO, nanorods, hydrothermal, KMnO4

Procedia PDF Downloads 403

Authors: A. S. Ibrahim Mamane, S. Giljean, M.-J. Pac, G. L’Hostis

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Fiber reinforced composite laminates are particularly subject to residual stresses due to their heterogeneity and the complex chemical, mechanical and thermal mechanisms that occur during their processing. Residual stresses are now well known to cause damage accumulation, shape instability, and behavior disturbance in composite parts. Many works exist in the literature on techniques for minimizing residual stresses in thermosetting and thermoplastic composites mainly. To study in-depth the influence of processing mechanisms on the formation of residual stresses and to minimize them by establishing a reliable correlation, it is essential to be able to measure very precisely the profile of residual stresses in the composite. Residual stresses are important data to consider when sizing composite parts and predicting their behavior. The incremental hole drilling is very effective in measuring the gradient of residual stresses in composite laminates. This method is semi-destructive and consists of drilling incrementally a hole through the thickness of the material and measuring relaxation strains around the hole for each increment using three strain gauges. These strains are then converted into residual stresses using a matrix of coefficients. These coefficients, called calibration coefficients, depending on the diameter of the hole and the dimensions of the gauges used. The reliability of the incremental hole drilling depends on the accuracy with which the calibration coefficients are determined. These coefficients are calculated using a finite element model. The samples’ features and the experimental conditions must be considered in the simulation. Any mismatch can lead to inadequate calibration coefficients, thus introducing errors on residual stresses. Several calibration coefficient correction methods exist for isotropic material, but there is a lack of information on this subject concerning composite laminates. In this work, a Python program was developed to automatically generate the adequate finite element model. This model allowed us to perform a parametric study to assess the influence of experimental errors on the calibration coefficients. The results highlighted the sensitivity of the calibration coefficients to the considered errors and gave an order of magnitude of the precisions required on the experimental device to have reliable measurements. On the basis of these results, improvements were proposed on the experimental device. Furthermore, a numerical method was proposed to correct the calibration coefficients for different types of materials, including thick composite parts for which the analytical approach is too complex. This method consists of taking into account the experimental errors in the simulation. Accurate measurement of the experimental errors (such as eccentricity of the hole, angular deviation of the gauges from their theoretical position, or errors on increment depth) is therefore necessary. The aim is to determine more precisely the residual stresses and to expand the validity domain of the incremental hole drilling technique.

Keywords: fiber reinforced composites, finite element simulation, incremental hole drilling method, numerical correction of the calibration coefficients, residual stresses

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Authors: Abdolvahab Ehsani Rad, Mohd Shafry Mohd Rahim, Alireza Norouzi

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Medical image analysis is one of the great effects of computer image processing. There are several processes to analysis the medical images which the segmentation process is one of the challenging and most important step. In this paper the segmentation method proposed in order to segment the dental radiograph images. Thresholding method has been applied to simplify the images and to morphologically open binary image technique performed to eliminate the unnecessary regions on images. Furthermore, horizontal and vertical integral projection techniques used to extract the each individual tooth from radiograph images. Segmentation process has been done by applying the level set method on each extracted images. Nevertheless, the experiments results by 90% accuracy demonstrate that proposed method achieves high accuracy and promising result.

Keywords: integral production, level set method, morphological operation, segmentation

Procedia PDF Downloads 320

Authors: A. Boateng, La Gil-Alana, M. Lesaoana; Hj. Siweya, A. Belete

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This study examines long memory or long-range dependence in the CPI inflation rates of Ghana and South Africa using Whittle methods and autoregressive fractionally integrated moving average (ARFIMA) models. Standard I(0)/I(1) methods such as Augmented Dickey-Fuller (ADF), Philips-Perron (PP) and Kwiatkowski–Phillips–Schmidt–Shin (KPSS) tests were also employed. Our findings indicate that long memory exists in the CPI inflation rates of both countries. After processing fractional differencing and determining the short memory components, the models were specified as ARFIMA (4,0.35,2) and ARFIMA (3,0.49,3) respectively for Ghana and South Africa. Consequently, the CPI inflation rates of both countries are fractionally integrated and mean reverting. The implication of this result will assist in policy formulation and identification of inflationary pressures in an economy.

Keywords: Consumer Price Index (CPI) inflation rates, Whittle method, long memory, ARFIMA model

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Authors: Masaya Yoshikawa, Toshiya Asai, Ryoma Matsuhisa, Yusuke Nozaki, Kensaku Asahi

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Recently, side-channel attacks, which estimate secret keys using side-channel information such as power consumption and compromising emanations of cryptography circuits embedded in hardware, have become a serious problem. In particular, electromagnetic analysis attacks against cryptographic circuits between information processing and electromagnetic fields, which are related to secret keys in cryptography circuits, are the most threatening side-channel attacks. Therefore, it is important to evaluate tamper resistance against electromagnetic analysis attacks for cryptography circuits. The present study performs basic examination of the tamper resistance of cryptography circuits using electromagnetic analysis attacks with noise resources.

Keywords: tamper resistance, cryptographic circuit, hardware security evaluation, noise resources

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Authors: Julia Ive, Lucia Specia

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Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

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Authors: E. M. S. Azzam, S. A. Ahmed, H. H. Mohamed, M. A. Adly, E. A. M. Gad

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In this work we prepared 3-(p-methyl) phenyl-5-thionyl-1,2,4-triazoline (C1). The nanostructure of the prepared C1 compound was fabricated by assembling on silver nanoparticles. The UV and TEM analyses confirm the assembling of C1 compound on silver nanoparticles. The effect of C1 compound on the removal of Iron (II) from Iron contaminated samples and industrial wastewater samples (produced water from oil processing facility) were studied before and after their assembling on silver nanoparticles. The removal of Iron was studied at different concentrations of FeSO4 solution (5, 14 and 39 mg/l) and field sample concentration (661 mg/l). In addition, the removal of Iron (II) was investigated at different times. The Prepared compound and its nanostructure with AgNPs show highly efficient in removing the Iron ions. Quantum chemical descriptors using DFT was discussed. The output of the study pronounces that the C1 molecule can act as chelating agent for Iron (II).

Keywords: triazole derivatives, silver nanoparticles, iron (II), oil field

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Authors: Josef Steinberger, Vanni Zavarella, Hristo Tanev

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Natural disasters cause tens of thousands of victims and massive material damages. We refer to all those events caused by natural disasters, such as damage on people, infrastructure, vehicles, services and resource supply, as micro events. This paper addresses the problem of micro - event detection in online media sources. We present a natural language grammar learning algorithm and apply it to online news. The algorithm in question is based on distributional clustering and detection of word collocations. We also explore the extraction of micro-events from social media and describe a Twitter mining robot, who uses combinations of keywords to detect tweets which talk about effects of disasters.

Keywords: online news, natural language processing, machine learning, event extraction, crisis computing, disaster effects, Twitter

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Authors: Lexi Li, Vanessa H. K. Pang

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This study aims to demonstrate how native and learner corpora can be used to enhance modal verb treatment in EFL textbooks in mainland China. It contributes to a corpus-informed and learner-centered design of grammar presentation in EFL textbooks that enhances the authenticity and appropriateness of textbook language for target learners. The linguistic focus is will, would, can, could, may, might, shall, should, must. The native corpus is the spoken component of BNC2014 (hereafter BNCS2014). The spoken part is chosen because pedagogical purpose of the textbooks is communication-oriented. Using the standard query option of CQPweb, 5% of each of the nine modals was sampled from BNCS2014. The learner corpus is the POS-tagged Ten-thousand English Compositions of Chinese Learners (TECCL). All the essays under the 'secondary school' section were selected. A series of five secondary coursebooks comprise the textbook corpus. All the data in both the learner and the textbook corpora are retrieved through the concordance functions of WordSmith Tools (version, 5.0). Data analysis was divided into two parts. The first part compared the patterns of modal verbs in the textbook corpus and BNC2014 with respect to distributional features, semantic functions, and co-occurring constructions to examine whether the textbooks reflect the authentic use of English. Secondly, the learner corpus was analyzed in terms of the use (distributional features, semantic functions, and co-occurring constructions) and the misuse (syntactic errors, e.g., she can sings*.) of the nine modal verbs to uncover potential difficulties that confront learners. The analysis of distribution indicates several discrepancies between the textbook corpus and BNCS2014. The first four most frequent modal verbs in BNCS2014 are can, would, will, could, while can, will, should, could are the top four in the textbooks. Most strikingly, there is an unusually high proportion of can (41.1%) in the textbooks. The results on different meanings shows that will, would and must are the most problematic. For example, for will, the textbooks contain 20% more occurrences of 'volition' and 20% less of 'prediction' than those in BNCS2014. Regarding co-occurring structures, the textbooks over-represented the structure 'modal +do' across the nine modal verbs. Another major finding is that the structure of 'modal +have done' that frequently co-occur with could, would, should, and must is underused in textbooks. Besides, these four modal verbs are the most difficult for learners, as the error analysis shows. This study demonstrates how the synergy of native and learner corpora can be harnessed to improve EFL textbook presentation of modal verbs in a way that textbooks can provide not only authentic language used in natural discourse but also appropriate design tailed for the needs of target learners.

Keywords: English as Foreign Language, EFL textbooks, learner corpus, modal verbs, native corpus

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Authors: Rendong Cai, Bei Peng, Yanping Dong

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In risk decision making, individuals are found to be susceptible to 'frames': people tend to be risk averse when the choice is described in terms of potential 'gains' (gain frame), whereas they tend to be risk seeking when the same choice is described in terms of potential 'losses' (loss frame); this effect is termed the framing effect. The framing effect has been well documented and some studies even find a developmental reversal in the framing effect: The more experience an individual has in a certain field, the easier for him to be influenced by the frame relevant to the field, resulting in greater decision inconsistency. Recent studies reported that using a foreign language can reduce the framing effect. However, it is not clear whether foreign language use can overcome the developmental reversal in the framing effect. The present study investigated three potential factors that may influence the developmental reversal in the framing effect: specialized knowledge of the participants, the language in which the problem is presented, and the types of problems. The present study examined the decision making behavior of 188 Chinese-English bilinguals who majored in Finance, with a group of 277 English majors as the control group. They were asked to solve a financial problem (experimental condition) and a life problem (control condition). Each problem was presented in one of the following four versions: native language-gain frame, foreign language-gain frame, native language-loss frame, and foreign language-loss frame. Results revealed that for the life problem, under the native condition, both groups were affected by the frame; but under the foreign condition, this framing effect disappeared for the financial majors. This confirmed that foreign language use modulates framing effects in general decision making, which served as an effective baseline. For the financial problem, under the native condition, only the financial major was observed to be influenced by the frame, which was a developmental reversal; under the foreign condition, however, this framing effect disappeared. The results provide further empirical evidence for the universal of the developmental reversal in risky decision making. More importantly, the results suggest that using a foreign language can overcome such reversal, which has implications for the reduction of decision biases in professionals. The findings also shed new light on the complex interaction between general decision-making and bilingualism.

Keywords: the foreign language effect, developmental reversals, the framing effect, bilingualism

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Authors: Marcel Schulze, Behrem Aslan, Silke Lux, Alexandra Philipsen

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Objective: Patients with Attention Deficit/Hyperactivity Disorder (ADHD) often report that they are being flooded by sensory impressions. Studies investigating sensory processing show hypersensitivity for sensory inputs across the senses in children and adults with ADHD. Especially the auditory modality is affected by deficient acoustical inhibition and modulation of signals. While studying unimodal signal-processing is relevant and well-suited in a controlled laboratory environment, everyday life situations occur multimodal. A complex interplay of the senses is necessary to form a unified percept. In order to achieve this, the unimodal sensory modalities are bound together in a process called multisensory integration (MI). In the current study we investigate MI in an adult ADHD sample using the McGurk-effect – a well-known illusion where incongruent speech like phonemes lead in case of successful integration to a new perceived phoneme via late top-down attentional allocation . In ADHD neuronal dysregulation at rest e.g., aberrant within or between network functional connectivity may also account for difficulties in integrating across the senses. Therefore, the current study includes resting-state functional connectivity to investigate a possible relation of deficient network connectivity and the ability of stimulus integration. Method: Twenty-five ADHD patients (6 females, age: 30.08 (SD:9,3) years) and twenty-four healthy controls (9 females; age: 26.88 (SD: 6.3) years) were recruited. MI was examined using the McGurk effect, where - in case of successful MI - incongruent speech-like phonemes between visual and auditory modality are leading to a perception of a new phoneme. Mann-Whitney-U test was applied to assess statistical differences between groups. Echo-planar imaging-resting-state functional MRI was acquired on a 3.0 Tesla Siemens Magnetom MR scanner. A seed-to-voxel analysis was realized using the CONN toolbox. Results: Susceptibility to McGurk was significantly lowered for ADHD patients (ADHDMdn:5.83%, ControlsMdn:44.2%, U= 160.5, p=0.022, r=-0.34). When ADHD patients integrated phonemes, reaction times were significantly longer (ADHDMdn:1260ms, ControlsMdn:582ms, U=41.0, p<.000, r= -0.56). In functional connectivity medio temporal gyrus (seed) was negatively associated with primary auditory cortex, inferior frontal gyrus, precentral gyrus, and fusiform gyrus. Conclusion: MI seems to be deficient for ADHD patients for stimuli that need top-down attentional allocation. This finding is supported by stronger functional connectivity from unimodal sensory areas to polymodal, MI convergence zones for complex stimuli in ADHD patients.

Keywords: attention-deficit hyperactivity disorder, audiovisual integration, McGurk-effect, resting-state functional connectivity

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Authors: Mosab Alrashed, Wei Xu, Stephen Abineri, Yifan Zhao, Jörn Mehnen

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Thermographic inspection is a relatively new technique for Non-Destructive Testing (NDT) which has been gathering increasing interest due to its relatively low cost hardware and extremely fast data acquisition properties. This technique is especially promising in the area of rapid automated damage detection and quantification. In collaboration with a major industry partner from the aerospace sector advanced thermography-based NDT software for impact damaged composites is introduced. The software is based on correlation analysis of time-temperature profiles in combination with an image enhancement process. The prototype software is aiming to a) better visualise the damages in a relatively easy-to-use way and b) automatically and quantitatively measure the properties of the degradation. Knowing that degradation properties play an important role in the identification of degradation types, tests and results on specimens which were artificially damaged have been performed and analyzed.

Keywords: NDT, correlation analysis, image processing, damage, inspection

Procedia PDF Downloads 549

Authors: X. Gumara Rigol, I. Martínez de Apellaniz Anzuola, A. Garcia Serrano, A. Franzi Cros, O. Vidal Calbet, A. Al Maruf

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Traditional federated architectures for data warehousing work well when corporations have existing regional data warehouses and there is a need to aggregate data at a global level. Schibsted Media Group has been maturing from a decentralised organisation into a more globalised one and needed to build both some of the regional data warehouses for some brands at the same time as the global one. In this paper, we present the architectural alternatives studied and why a custom federated approach was the notable recommendation to go further with the implementation. Although the data warehouses are logically federated, the implementation uses a single database system which presented many advantages like: cost reduction and improved data access to global users allowing consumers of the data to have a common data model for detailed analysis across different geographies and a flexible layer for local specific needs in the same place.

Keywords: data integration, data warehousing, federated architecture, Online Analytical Processing (OLAP)

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Authors: Aleksey Fedorov

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Building a scalable platform for quantum computing remains one of the most challenging tasks in quantum science and technologies. However, the implementation of most important quantum operations with qubits (quantum analogues of classical bits), such as multiqubit Toffoli gate, requires either a polynomial number of operation or a linear number of operations with the use of ancilla qubits. Therefore, the reduction of the number of operations in the presence of scalability is a crucial goal in quantum information processing. One of the most elegant ideas in this direction is to use qudits (multilevel systems) instead of qubits and rely on additional levels of qudits instead of ancillas. Although some of the already obtained results demonstrate a reduction of the number of operation, they suffer from high complexity and/or of the absence of scalability. We show a strong reduction of the number of operations for the realization of the Toffoli gate by using qudits for a scalable multi-qudit processor. This is done on the basis of a general relation between the dimensionality of qudits and their topology of connections, that we derived.

Keywords: quantum computing, qudits, Toffoli gates, gate decomposition

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Authors: Fahad Suleiman

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Queuing, in medical system is the process of moving patients in a specific sequence to a specific service according to the patients’ nature of illness. The term scheduling stands for the process of computing a schedule. This may be done by a queuing based scheduler. This paper focuses on the medical consultancy system, the different queuing algorithms that are used in healthcare system to serve the patients, and the average waiting time. The aim of this paper is to build automatic queuing system for organizing the medical queuing system that can analyses the queue status and take decision which patient to serve. The new queuing architecture model can switch between different scheduling algorithms according to the testing results and the factor of the average waiting time. The main innovation of this work concerns the modeling of the average waiting time is taken into processing, in addition with the process of switching to the scheduling algorithm that gives the best average waiting time.

Keywords: queuing systems, queuing system models, scheduling algorithms, patients

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Authors: Jerzy Merkisz, Piotr Lijewski, Pawel Fuc, Maciej Siedlecki, Andrzej Ziolkowski, Sylwester Weymann

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The paper discusses the problem of load transport using farm tractors and road tractor units. This type of carriage of goods is often done with farm vehicles. The tests were performed with the PEMS equipment (Portable Emission Measurement System) under actual traffic conditions. The vehicles carried a load of 20000 kg. This research method is one of the most desired because it provides reliable information on the actual vehicle emissions and fuel consumption (carbon balance method). For the tests, a route was selected that simulated a trip from a small town to a food-processing facility located in a city. The analysis of the obtained results gave a clear answer as to what vehicles need to be used for the carriage of this type of cargo in terms of exhaust emissions and fuel consumption.

Keywords: emission, transport, fuel consumption, PEMS

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Authors: Ružica Tomičić, Zorica Tomičić, Peter Raspor

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An abundant growth of unwanted yeasts in food processing plants can lead to problems in quality and safety with significant financial losses. Candida and Pichia are the genera mainly involved in spoilage of products in the food and beverage industry. These contaminating microorganisms can form biofilms on food contact surfaces, being difficult to eradicate, increasing the probability of microbial survival and further dissemination during food processing. It is well known that biofilms are more resistant to antimicrobial agents compared to planktonic cells and this makes them difficult to eliminate. Among the strategies used to overcome resistance to antifungal drugs and preservatives, the use of natural substances such as plant extracts has shown particular promise, and many natural substances have been found to exhibit antifungal properties. This study aimed to investigated the impact of growth medium (Malt Extract broth (MEB) or Yeast Peptone Dextrose (YPD) broth) and temperatures (7°C, 37°C, 43°C for Candida strains and 7°C, 27°C, 32°C for Pichia strains) on the adhesion of Candida spp. and Pichia spp. to stainless steel (AISI 304) discs with different degrees of surface roughness (Ra = 25.20 – 961.9 nm), a material commonly used in the food industry. We also evaluated the antifungal and antiadhesion activity of plant extracts such as Humulus lupulus, Alpinia katsumadai and Evodia rutaecarpa against C. albicans, C glabrata and P. membranifaciens and investigated whether these plant extracts can interfere with biofilm formation. The adhesion was assessed by the crystal violet staining method, while the broth microdilution method CLSI M27-A3 was used to determine the minimum inhibitory concentration (MIC) of plant extracts. Our results indicated that the nutrient content of the medium significantly influenced the amount of adhered cells of the tested yeasts. The growth medium which resulted in a higher adhesion of C. albicans and C. glabrata was MEB, while for C. parapsilosis and C. krusei was YPD. In the case of P. pijperi and P. membranifaciens, YPD broth was more effective in promoting adhesion than MEB. Regarding the effect of temperature, C. albicans strain adhered to stainless steel surfaces in significantly higher level at a temperature of 43°C, while on the other hand C. glabrata, C. parapsilosis and C. krusei showed a different behavior with significantly higher adhesion at 37°C than at 7°C and 43°C. Further, the adherence ability of Pichia strains was highest at 27°C. Based on the MIC values, all plant extracts exerted significant antifungal effects with MIC values ranged from 100 to 400 μg/mL. It was observed that biofilm of C. glabrata were more resistance to plant extracts as compared to C. albicans. However, extracts of A. katsumadai and E. rutaecarpa promoted the growth and development of the preformed biofilm of P. membranifaciens. Thus, the knowledge of how these microorganisms adhere and which factors affect this phenomenon is of great importance in order to avoid their colonization on food contact surfaces.

Keywords: adhesion, Candida spp., Pichia spp., plant extracts

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Authors: Charlotte Entwistle, Ryan Boyd

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Recent developments in information retrieval techniques and natural language processing have allowed for greater exploration of psychological and social processes. Linguistic analysis methods for understanding behaviour have provided useful insights within the field of mental health. One area within mental health that has received little attention though, is borderline personality disorder (BPD). BPD is a common mental health disorder characterised by instability of interpersonal relationships, self-image and affect. It also manifests through maladaptive behaviours, such as impulsivity and self-harm. Examination of language patterns associated with BPD could allow for a greater understanding of the disorder and its links to maladaptive thoughts and behaviours. Language analysis methods could also be used in a predictive way, such as by identifying indicators of BPD or predicting maladaptive thoughts, emotions and behaviours. Additionally, associations that are uncovered between language and maladaptive thoughts and behaviours could then be applied at a more general level. This study explores linguistic characteristics of BPD, and their links to maladaptive thoughts and behaviours, through the analysis of social media data. Data were collected from a large corpus of posts from the publicly available social media platform Reddit, namely, from the ‘r/BPD’ subreddit whereby people identify as having BPD. Data were collected using the Python Reddit API Wrapper and included all users which had posted within the BPD subreddit. All posts were manually inspected to ensure that they were not posted by someone who clearly did not have BPD, such as people posting about a loved one with BPD. These users were then tracked across all other subreddits of which they had posted in and data from these subreddits were also collected. Additionally, data were collected from a random control group of Reddit users. Disorder-relevant behaviours, such as self-harming or aggression-related behaviours, outlined within Reddit posts were coded to by expert raters. All posts and comments were aggregated by user and split by subreddit. Language data were then analysed using the Linguistic Inquiry and Word Count (LIWC) 2015 software. LIWC is a text analysis program that identifies and categorises words based on linguistic and paralinguistic dimensions, psychological constructs and personal concern categories. Statistical analyses of linguistic features could then be conducted. Findings revealed distinct linguistic features associated with BPD, based on Reddit posts, which differentiated these users from a control group. Language patterns were also found to be associated with the occurrence of maladaptive thoughts and behaviours. Thus, this study demonstrates that there are indeed linguistic markers of BPD present on social media. It also implies that language could be predictive of maladaptive thoughts and behaviours associated with BPD. These findings are of importance as they suggest potential for clinical interventions to be provided based on the language of people with BPD to try to reduce the likelihood of maladaptive thoughts and behaviours occurring. For example, by social media tracking or engaging people with BPD in expressive writing therapy. Overall, this study has provided a greater understanding of the disorder and how it manifests through language and behaviour.

Keywords: behaviour analysis, borderline personality disorder, natural language processing, social media data

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Authors: Thu Le Thi Bao

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Industrial parks have both active roles in promoting economic development and source of appearance of boarding houses and slums in the adjacent area, lacking infrastructure, causing many social evils. The context of the recent pandemic and climate change on a global scale pose issues that need to be resolved for sustainable development. Ho Chi Minh City aims to develop housing for migrant workers to stabilize human resources and, at the same time, solve problems of social evils caused by poor living conditions. The paper focuses on the content of renovating existing industrial parks and worker accommodation in Ho Chi Minh City to propose appropriate models, contributing to the goal of urban embellishment and solutions for industrial parks to adapt to abnormal impact conditions such as pandemics, climate change, crises.

Keywords: industrial park, social housing, accommodation, distribution center

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Authors: Diya Alsafadi, Fawwaz Khalili, Mohammad W. Amer

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Butanol is an important industrial solvent and potentially a better liquid transportation biofuel than ethanol. The cost of feedstock is one key problem associated with the biobutanol production. Date palm is sugar-rich fruit and highly abundant. Thousands of tons of date wastes that generated from date processing industries are thrown away each year and imposing serious environmental problems. To exploit the utilization of renewable biomass feedstock, date palm waste was utilized for butanol production by Clostridium acetobutylicum DSM 1731. Fermentation conditions were optimized by investigating several parameters that affect the production of butanol such as temperature, substrate concentration and pH. The highest butanol yield (1.0 g/L) and acetone, butanol, and ethanol (ABE) content (1.3 g/L) were achieved at 20 g/L date waste, pH 5.0 and 37 °C. These results suggest that date palm waste can be used for biobutanol production.

Keywords: biofuel, acetone-butanol-ethanol fermentation, date palm waste, Clostridium acetobutylicum

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Authors: Mehdi Brahimi, Kamal Medjaher, Noureddine Zerhouni, Mohammed Leouatni

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The Prognostics and Health Management is a system engineering discipline which provides solutions and models to the implantation of a predictive maintenance. The approach is based on extracting useful information from monitoring data to assess the “health” state of an industrial equipment or an asset. In this paper, we examine multiple extracted features from Pantograph-Catenary contact force in order to select the most relevant ones to achieve a diagnostics function. The feature extraction methodology is based on simulation data generated thanks to a Pantograph-Catenary simulation software called INPAC and measurement data. The feature extraction method is based on both statistical and signal processing analyses. The feature selection method is based on statistical criteria.

Keywords: catenary/pantograph interaction, diagnostics, Prognostics and Health Management (PHM), quality of current collection

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Authors: Amir Azaron

Abstract:

In this research, a stochastic programming approach is developed for designing supply chains with uncertain parameters. Demands and selling prices of products at markets are considered as the uncertain parameters. The proposed mathematical model will be multi-period two-stage stochastic programming, which takes into account the selection of retailer sites, suppliers, production levels, inventory levels, transportation modes to be used for shipping goods, and shipping quantities among the entities of the supply chain network. The objective function is to maximize the chain’s net present value. In order to maximize the chain’s NPV, the sum of first-stage investment costs on retailers, and the expected second-stage processing, inventory-holding and transportation costs should be kept as low as possible over multiple periods. The effects of supply uncertainty where suppliers are unreliable will also be investigated on the efficiency of the supply chain.

Keywords: supply chain management, stochastic programming, multiobjective programming, inventory control

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Authors: Iris Käppler, Paul Matthäi, Chokri Cherif

Abstract:

In the scope of application of technical textiles, Non-Crimp Fabrics are increasingly used. In general, NCF exhibit excellent load bearing properties, but caused by the manufacturing process, there are some remaining disadvantages which have to be reduced. Regarding to this, a novel technique of processing NCF was developed substituting the binding-thread by an adhesive. This stitch-free method requires new manufacturing concept as well as new basic methods to prove adhesion of glue at fibres and textiles. To improve adhesion properties and the wettability of carbon-fibres by the adhesive, oxyfluorination was used. The modification of carbon-fibres by oxyfluorination was investigated via scanning electron microscope, X-ray photo electron spectroscopy and single fibre tensiometry. Special tensile tests were developed to determine the maximum force required for detachment.

Keywords: non-crimp fabric, adhesive, stitch-free, high-performance fibre

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Authors: Eng. Alaa K. Satti Salih

Abstract:

Revolutions Applications such as telecommunications, hands-free communications, recording, etc. which need at least one microphone, the signal is usually infected by noise and echo. The important application is the speech enhancement, which is done to remove suppressed noises and echoes taken by a microphone, beside preferred speech. Accordingly, the microphone signal has to be cleaned using digital signal processing DSP tools before it is played out, transmitted, or stored. Engineers have so far tried different approaches to improving the speech by get back the desired speech signal from the noisy observations. Especially Mobile communication, so in this paper will do reconstruction of the speech signal, observed in additive background noise, using the Kalman filter technique to estimate the parameters of the Autoregressive Process (AR) in the state space model and the output speech signal obtained by the MATLAB. The accurate estimation by Kalman filter on speech would enhance and reduce the noise then compare and discuss the results between actual values and estimated values which produce the reconstructed signals.

Keywords: autoregressive process, Kalman filter, Matlab, noise speech

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Authors: Denis Özdemir, Max Senges

Abstract:

There are many examples of AI-supported apps for better health and wellbeing. Generally, these applications help people to achieve their goals based on scientific research and input data. Still, they do not always explain how those three are related, e.g. by making implicit assumptions about goals that hold for many but not for all. We present a seven-step method for designing health and wellbeing AIs considering goal setting, measurable results, real-time indicators, analytics, visual representations, communication, and feedback. It can help engineers as guidance in developing apps, recommendation algorithms, and interfaces that support humans in their decision-making without patronization. To illustrate the method, we create a recommender AI for tiny wellbeing habits and run a small case study, including a survey. From the results, we infer how people perceive the relationship between them and the AI and to what extent it helps them to achieve their goals. We review our seven-step engineering method and suggest modifications for the next iteration.

Keywords: recommender systems, natural language processing, health apps, engineering methods

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Authors: Chan Yan Nok

Abstract:

The present study is a qualitative study based on the coping experiences of six Hong Kong Chinese mothers who had childhood trauma from their first-person perspective. Expanding the perspective beyond the dominant discourse of “inter-generation transmission of trauma”, this study explores the experiences and meanings of child trauma embedded in their narratives through the process of thematic analysis and narrative analysis. The interviewees painted a nuanced picture of their process of coping and trauma resolution. First, acknowledgement; second, feel safe and start to tell the story of trauma; third, feel the feelings and expression of emotions; fourth, clarifying and coping with the impacts of trauma; fifth, integration and transformation; and sixth, using their new understanding of experience to have a better life. It was seen that there was no “end” within the process of trauma resolution. Instead, this is an ongoing process with positive healing trajectory. Analysis of the stories of the mothers revealed recurrent themes around continuous self-reflective awareness in the process of trauma coping. Rather than being necessarily negative and detrimental, childhood trauma could highlight the meanings of being a mother and reveal opportunities for continuous personal growth and self-enhancement. Utilizing the sense of inadequacy as a core driver in the trauma recovery process while developing a heightened awareness of the unfinished business embedded in their “automatic pattern” of behaviors, emotions, and thoughts can help these mothers become more flexible to formulate new methods in facing future predicaments. Future social work and parent education practices should help mothers deal with unresolved trauma, make sense of their impacts of childhood trauma and discover the growth embedded in the past traumatic experience. They should be facilitated in “acknowledging the reality of the trauma”, including understanding their complicated emotions arising from the traumatic experiences and voicing their struggles. In addition, helping these mothers to be aware of short-term and long-term trauma impacts (i.e., secondary responses to the trauma) and explore their effective coping strategies in “overcoming secondary responses to the trauma” are crucial for their future positive adjustment and transformation. Through affirming their coping abilities and lessons learnt from past experiences, mothers can reduce feelings of shame and powerlessness and enhance their parental capacity.

Keywords: childhood trauma, coping, mothers, self-awareness, self-reflection, trauma resolution

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Authors: Sidong Zhao, Xingping Wang

Abstract:

Recently, the government of China has provided strong support the developments of overseas industrial parks. The global distribution of China overseas industrial parks has gradually moved from the 'sparks of fire' to the 'prairie fires.' The support and distribution have promoted developing overseas industrial parks to a strategy of constructing a China's new open economic system and a typical representative of the 'Chinese wisdom' and the 'China's plans' that China has contributed to the globalization of the new era under the initiative of the Belt and Road. As the industrial parks are the basis of 'work/employment', a basic function of a city (Athens Constitution), planning for developments of industrial parks has become a long-term focus of urban planning. Based on the research of the planning and the analysis of the present developments of some typical China overseas industrial parks, we found some interesting rules: First, large numbers of the China overseas industrial parks are located in less developed countries. These industrial parks have become significant drives of the developments of the host cities and even the regions in those countries, especially in investment, employment and paid tax fee for the local, etc. so, the planning and development of overseas industrial parks have received extensive attention. Second, there are some problems in the small part of the overseas Park, such as the planning of the park not following the planning of the host city and lack of implementation of the park planning, etc. These problems have led to the difficulties of the implementation of the planning and the sustainable developments of the parks. Third, a unique pattern of space development has been formed. in the dimension of the patterns of regional spatial distribution, there are five characteristics - along with the coast, along the river, along with the main traffic lines and hubs, along with the central urban area and along the connections of regions economic. In the dimension of the spatial relationships between the industrial park and the city, there is a growing and evolving trend as 'separation – integration - union'. In the dimension of spatial mode of the industrial parks, there are different patterns of development, such as a specialized industrial park, complex industrial park, characteristic town and new urban area of industry, etc. From the perspective of the trends of the developments and spatial modes, in the future, the planning of China overseas industrial parks should emphasize the idea of 'building a city based on the industrial park'. In other words, it's making the developments of China overseas industrial parks move from 'driven by policy' to 'driven by the functions of the city', accelerating forming the system of China overseas industrial parks and integrating the industrial parks and the cities.

Keywords: overseas industrial park, spatial mode, planning, China

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Authors: Chaitanya Chawla, Divya Panwar, Gurneesh Singh Anand, M. P. S Bhatia

Abstract:

This paper presents a deep-learning mechanism for classifying computer generated images and photographic images. The proposed method accounts for a convolutional layer capable of automatically learning correlation between neighbouring pixels. In the current form, Convolutional Neural Network (CNN) will learn features based on an image's content instead of the structural features of the image. The layer is particularly designed to subdue an image's content and robustly learn the sensor pattern noise features (usually inherited from image processing in a camera) as well as the statistical properties of images. The paper was assessed on latest natural and computer generated images, and it was concluded that it performs better than the current state of the art methods.

Keywords: image forensics, computer graphics, classification, deep learning, convolutional neural networks

Procedia PDF Downloads 338