Search results for: GLCM texture features

Authors: Abderrahim Cheriguene, Fatiha Arioui

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The experimental study focuses on the extraction of pectin, whey protein and gelatin, and the study of their functional properties. Microbiological, physicochemical and sensory approach integrated has been implanted to study the effect of the incorporation of these natural food additives in the matrix of a fermented milk type set yogurt, to study the stability of the product during the periods of fermentation and post-acidification over a period of 21 days at 4°C. Pectin was extracted in hot HCl solution. Thermo-precipitation was carried out to obtain the whey proteins while the gelatin was extracted by hydrolysis of the collagen from bovine ossein. The fermented milk was prepared by varying the concentration of the incorporated additives. The measures and controls carried performed periodically on fermented milk experimental tests were carried out: pH, acidity, viscosity, the enumeration of Streptococcus thermophilus, cohesiveness, adhesiveness, taste, aftertaste, whey exudation, and odor. It appears that the acidity, viscosity, and number of Streptococcus thermophilus increased with increasing concentration of additive added in the experimental tests. Indeed, it seems clear that the quality of fermented milk and storability is more improved than the incorporation rate is high. The products showed a better test and a firmer texture limiting the whey exudation.

Keywords: fermented milk, pectin, gelatin, whey proteins, functional properties, quality, conservation, valorization

Procedia PDF Downloads 128

Authors: Theresa Zagers, Rita Guerra

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Most research investigating how receiving communities perceive, and experience migration has overlooked the potential role of subjective social class and social class identity in positive intergroup relations and social cohesion of migrants and host societies. The present study aimed to provide insights to understand this relationship and focused on three important features: prosocial behaviour, attitudes and emotions towards Muslim immigrants in Flanders, Belgium. Building on relative deprivation-gratification theory we examined the indirect relationships of subjective social class on prosocial behaviour/intentions, attitudes and emotions via relative deprivation (RD), as well as the moderator role of the importance of social class identity. 431 Belgian participants participated in an online survey study. Overall, our results supported the predicted indirect effect of subjective social class: the lower the subjective social class, the higher the perceptions of relative deprivation, which in turn is related to less prosocial behaviour intentions, and more negative attitudes and emotions towards immigrants. This indirect effect was, however, not moderated by the importance of social class identity. Interestingly, the direct effects of subjective social class showed a different pattern: when bypassing deprivation our results showed higher subjective social class was detrimental for intergroup relations (more negative attitudes and emotions), and that lower subjective social class was positively related to prosocial intentions for those identifying highly with their class identity. Overall, we gained valuable insights in the relationship of subjective social class and the three features of intergroup relations.

Keywords: social class, relative deprivation-gratification, prosocial behavior, attitudes, emotions, Muslim immigrants

Procedia PDF Downloads 48

Authors: Magdeline Pakeng Mohlala, R. L. Molatudi, M. A. Mofokeng

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Cowpea (Vigna unguiculata (L.) Walp) is an important annual leguminous crop in semi-arid and tropics. Most of cowpea grain production in South Africa is mainly used for domestic consumption, as seed planting and little or none gets to be used in industrial processing; thus, there is a need to expand the utilization of cowpea through industrial processing. Agronomic traits contribute to the understanding of the association between yield and its component traits to facilitate effective selection for yield improvement. The aim of this study was to evaluate cowpea genotypes using grain yield and canning quality traits. The field experiment was conducted in two locations in Limpopo Province, namely Syferkuil Agricultural Experimental farm and Ga-Molepo village during 2017/2018 growing season and canning took place at ARC-Grain Crops Potchefstroom. The experiment comprised of 100 cowpea genotypes laid out in a Randomized Complete Block Designs (RCBD). The grain yield, yield components, and canning quality traits were analysed using Genstat software. About 62 genotypes were suitable for canning, 38 were not due to their seed coat texture, and water uptake was less than 80% resulting in too soft (mushy) seeds. Grain yield for RV115, 99k-494-6, ITOOK1263, RV111, RV353 and 53 other genotypes recorded high positive association with number of branches, pods per plant, and number of seeds per pod, unshelled weight and shelled weight for Syferkuil than at Ga-Molepo are therefore recommended for canning quality.

Keywords: agronomic traits, canning quality, genotypes, yield

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Authors: Faiza Belbachir, Thibault Schienhinski

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The massive development of online social networks allows users to post and share their opinions on various topics. With this huge volume of opinion, it is interesting to extract and interpret these information for different domains, e.g., product and service benchmarking, politic, system of recommendation. This is why opinion detection is one of the most important research tasks. It consists on differentiating between opinion data and factual data. The difficulty of this task is to determine an approach which returns opinionated document. Generally, there are two approaches used for opinion detection i.e. Lexical based approaches and Machine Learning based approaches. In Lexical based approaches, a dictionary of sentimental words is used, words are associated with weights. The opinion score of document is derived by the occurrence of words from this dictionary. In Machine learning approaches, usually a classifier is trained using a set of annotated document containing sentiment, and features such as n-grams of words, part-of-speech tags, and logical forms. Majority of these works are based on documents text to determine opinion score but dont take into account if these texts are really correct. Thus, it is interesting to exploit other information to improve opinion detection. In our work, we will develop a new way to consider the opinion score. We introduce the notion of trust score. We determine opinionated documents but also if these opinions are really trustable information in relation with topics. For that we use lexical SentiWordNet to calculate opinion and trust scores, we compute different features about users like (numbers of their comments, numbers of their useful comments, Average useful review). After that, we combine opinion score and trust score to obtain a final score. We applied our method to detect trust opinions in TRIPADVISOR collection. Our experimental results report that the combination between opinion score and trust score improves opinion detection.

Keywords: Tripadvisor, opinion detection, SentiWordNet, trust score

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Authors: Jonathan Matyenyika

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In recent years, automobile manufacturers have increasingly produced vehicles equipped with cutting-edge automotive electronic technology to match the fast-paced digital world of today; this has brought about various benefits in different business sectors that make use of these vehicles as a means of turning over a profit. In the logistics industry, vehicles equipped with this technology have proved to be very utilitarian; this paper focuses on the benefits automobile electronic equipped vehicles have in the logistics industry. Automotive vehicle manufacturers have introduced new technological electronic features to their vehicles to enhance and improve the overall performance, efficiency, safety and driver comfort. Some of these features have proved to be beneficial to logistics operators. To start with the introduction of adaptive cruise control in long-distance haulage vehicles, to see how this system benefits the drivers, we carried out research in the form of interviews with long-distance truck drivers with the main question being, what major difference have they experienced since they started to operate vehicles equipped with this technology to which most stated they had noticed that they are less tired and are able to drive longer distances as compared to when they used vehicles not equipped with this system. As a result, they can deliver faster and take on the next assignment, thus improving efficiency and bringing in more monetary return for the logistics company. Secondly, the introduction of electric hybrid technology, this system allows the vehicle to be propelled by electric power stored in batteries located in the vehicle instead of fossil fuel. Consequently, this benefits the logistic company as vehicles become cheaper to run as electricity is more affordable as compared to fossil fuel. The merging of electronic systems in vehicles has proved to be of great benefit, as my research proves that this can benefit the logistics industry in plenty of ways.

Keywords: logistics, manufacturing, hybrid technology, haulage vehicles

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Authors: Lana Burmistrova

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Introduction: The influence of visual impairments on several cognitive processes used in the music learning process is an increasingly important area in special education and cognitive musicology. Many children have several visual impairments due to the refractive errors and irreversible inhibitors. However, based on the compensatory neuroplasticity and functional reorganization, congenitally blind (CB) and early blind (EB) individuals use several areas of the occipital lobe to perceive and process auditory and tactile information. CB individuals have greater memory capacity, memory reliability, and less false memory mechanisms are used while executing several tasks, they have better working memory (WM) and short-term memory (STM). Blind individuals use several strategies while executing tactile and working memory n-back tasks: verbalization strategy (mental recall), tactile strategy (tactile recall) and combined strategies. Methods and design: The aim of the pilot study was to substantiate similar tendencies while executing attention, memory and combined auditory tasks in blind and sighted individuals constructed for this study, and to investigate attention, memory and combined mechanisms used in the music learning process. For this study eight (n=8) blind and eight (n=8) sighted individuals aged 13-20 were chosen. All respondents had more than five years music performance and music learning experience. In the attention task, all respondents had to identify pitch changes in tonal and randomized melodic pairs. The memory task was based on the mismatch negativity (MMN) proportion theory: 80 percent standard (not changed) and 20 percent deviant (changed) stimuli (sequences). Every sequence was named (na-na, ra-ra, za-za) and several items (pencil, spoon, tealight) were assigned for each sequence. Respondents had to recall the sequences, to associate them with the item and to detect possible changes. While executing the combined task, all respondents had to focus attention on the pitch changes and had to detect and describe these during the recall. Results and conclusion: The results support specific features in CB and EB, and similarities between late blind (LB) and sighted individuals. While executing attention and memory tasks, it was possible to observe the tendency in CB and EB by using more precise execution tactics and usage of more advanced periodic memory, while focusing on auditory and tactile stimuli. While executing memory and combined tasks, CB and EB individuals used passive working memory to recall standard sequences, active working memory to recall deviant sequences and combined strategies. Based on the observation results, assessment of blind respondents and recording specifics, following attention and memory correlations were identified: reflective attention and STM, reflective attention and periodic memory, auditory attention and WM, tactile attention and WM, auditory tactile attention and STM. The results and the summary of findings highlight the attention and memory features used in the music learning process in the context of blindness, and the tendency of the several attention and memory types correlated based on the task, strategy and individual features.

Keywords: attention, blindness, memory, music learning, strategy

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Authors: Takatoshi Ishii, Koji Kimita, Keiichi Muramatsu, Yoshiki Shimomura

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To increase the quality of learning, teacher and learner need mutual effort for realization of educational value. For this purpose, we need to manage the co-creational education among teacher and learners. In this research, we try to find a feature of co-creational education. To be more precise, we analyzed learners’ reports by natural language processing, and extract some features that describe the state of the co-creational education.

Keywords: co-creational education, e-portfolios, ICT integration, latent dirichlet allocation

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Authors: Usha Barahmand, Ruhollah Heydari Sheikh Ahmad

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Distress refers to an unpleasant metal state or emotional suffering marked by negative affect such as depression (e.g., lost interest; sadness; hopelessness), anxiety (e.g., restlessness; feeling tense). These negative affect have been mostly suggested to be concomitant of metal disorders such as positive psychosis symptoms and also of proneness to psychotic features in non-clinical population. Psychotic features proneness including hallucination, delusion and schizotypal traits, have been found to be associated with metacognitive beliefs. Metacognition has been conceptualized as ‘thinking about thoughts, monitoring and controlling of cognitive processes’. The aim of the current study was to investigate the role of psychosis proneness in the association of metacognitions and distress. We predicted psychosis proneness would mediate the association of metacognitive beliefs and the distress. A sample of 420 university students was randomly recruited to endorse questionnaires of the study that consisted of DASS-21questionnaire for assessing levels of distress, Cartwright–Hatton & Wells, Meta-cognitions Questionnaire (MCQ-30) for assessing metacognitive beliefs, Launay-Slade Hallucination Scale-revised (LSHS-R), Peters et al. Delusions Inventory, Schizotypal Personality Questionnaire-Brief. Conducting a bootstrapping approach in order to investigate our hypothesis, the result showed that there was no a direct association between metacognitive dimensions and psychological distress and psychosis proneness significantly mediated the association. Finding suggested that individuals with dysfunctional metacognitive beliefs experience high levels of distress if they are prone to psychosis symptoms. In other words, psychosis proneness is a path through which individuals with dysfunctional metacognitions experience high levels of psychological distress.

Keywords: metacognition, non-clinical population, psychological distress, psychosis proneness

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Authors: Andrea Hernandez Hurtado

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Research on social networks (SNs) -- the interactions individuals share with others has shed important light in helping to explain differential use of variable linguistic forms, both in L1s and L2s. Nevertheless, the acquisition of nonstandard L2 Spanish in the Region of Murcia, Spain, and how learners interact with other speakers while sojourning there have received little attention. Murcian Spanish (MuSp) was widely influenced by Panocho, a divergent evolution of Hispanic Latin, and differs from the more standard Peninsular Spanish (StSp) in phonology, morphology, and lexicon. For instance, speakers from this area will most likely palatalize diminutive endings, producing animalico [̩a.ni.ma.ˈli.ko] instead of animalito [̩a.ni.ma.ˈli.to] ‘little animal’. Because L1 speakers of the area produce and prefer salient regional lexicon and morphology (particularly the palatalized diminutive -ico) in their speech, the current research focuses on how international residents in the Region of Murcia use Spanish: (1) whether or not they acquire (perceptively and/or productively) any of the salient regional features of MuSp, and (2) how their SNs explain such acquisition. This study triangulates across three tasks -recognition, production, and preference- addressing both lexicon and morphology, with each task specifically created for the investigation of MuSp features. Among other variables, the effects of L1, residence, and identity are considered. As an ongoing dissertation research, data are currently being gathered through an online questionnaire. So far, 7 participants from multiple nationalities have completed the survey, although a minimum of 25 are expected to be included in the coming months. Preliminary results revealed that MuSp lexicon and morphology were successfully recognized by participants (p<.001). In terms of regional lexicon production (10.0%) and preference (47.5%), although participants showed higher percentages of StSp, results showed that international residents become aware of stigmatized lexicon and may incorporate it into their language use. Similarly, palatalized diminutives (production 14.2%, preference 19.0%) were present in their responses. The Social Network Analysis provided information about participants’ relationships with their interactants, as well as among them. Results indicated that, generally, when residents were more immersed in the culture (i.e., had more Murcian alters) they produced and preferred more regional features. This project contributes to the knowledge of language variation acquisition in L2 speakers, focusing on a stigmatized Spanish dialect and exploring how stigmatized varieties may affect L2 development. Results will show how L2 Spanish speakers’ language is affected by their stay in Murcia. This, in turn, will shed light on the role of SNs in language acquisition, the acquisition of understudied and marginalized varieties, and the role of immersion on language acquisition. As the first systematic account on the acquisition of L2 Spanish lexicon and morphology in the Region of Murcia, it lays important groundwork for further research on the connection between SNs and the acquisition of regional variants, applicable to Murcia and beyond.

Keywords: international residents, L2 Spanish, lexicon, morphology, nonstandard language acquisition, social networks

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Authors: Ashkan Ebadi, Adam Krzyzak

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Recommender systems, also known as recommender engines, have become an important research area and are now being applied in various fields. In addition, the techniques behind the recommender systems have been improved over the time. In general, such systems help users to find their required products or services (e.g. books, music) through analyzing and aggregating other users’ activities and behavior, mainly in form of reviews, and making the best recommendations. The recommendations can facilitate user’s decision making process. Despite the wide literature on the topic, using multiple data sources of different types as the input has not been widely studied. Recommender systems can benefit from the high availability of digital data to collect the input data of different types which implicitly or explicitly help the system to improve its accuracy. Moreover, most of the existing research in this area is based on single rating measures in which a single rating is used to link users to items. This paper proposes a highly accurate hotel recommender system, implemented in various layers. Using multi-aspect rating system and benefitting from large-scale data of different types, the recommender system suggests hotels that are personalized and tailored for the given user. The system employs natural language processing and topic modelling techniques to assess the sentiment of the users’ reviews and extract implicit features. The entire recommender engine contains multiple sub-systems, namely users clustering, matrix factorization module, and hybrid recommender system. Each sub-system contributes to the final composite set of recommendations through covering a specific aspect of the problem. The accuracy of the proposed recommender system has been tested intensively where the results confirm the high performance of the system.

Keywords: tourism, hotel recommender system, hybrid, implicit features

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Authors: Diana Serbezeanu, Ionela-Daniela Carja, Tachita Vlad-Bubulac, Sergiu Sova

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New phosphorus-containing monomers having methoxy end functional groups were prepared from methyl 4-hydroxybenzoate and two different dichlorides with phosphorus, namely phenyl phosphonic dichloride and phenyl dichlorophosphate. The structures of the monomers were confirmed by FTIR and NMR spectroscopy. The assignments for the 1H, 13C and 31P chemical shifts are based on 1D and 2D NMR homo- and heteronuclear correlations (H,H-COSY (Correlation Spectroscopy), H,C-HMQC (Heteronuclear Multiple Quantum Correlation and H,C-HMBC (Heteronuclear Multiple Bond Correlation)) and 31P-13C couplings. The monomers exhibited good solubility in common organic solvents. Dimethyl sulfoxide was to be a good solvent to grow crystals of considerable size which were investigated by X-ray analysis. One of these two new monomers presented thermotropic liquid crystalline behaviour, as revealed by differential scanning calorimetry (DSC), polarized light microscopy (PLM) and X-ray diffraction (XRD). The transition temperature from crystal to liquid crystalline state (K→LC) was 143°C and from the LC to isotropic state (LC→I) was 167°C. Upon heating, bis(4-(methoxycarbonyl)phenyl formed fine textures, difficult to be ascribed to smectic or nematic phases. Upon cooling from the isotropic state, bis(4-(methoxycarbonyl)phenyl exhibited a mosaic-type texture. X-ray diffraction measurements at small angles (SAXS) of bis(4-(methoxycarbonyl)phenyl showed two peaks at 1.8 Å and 3.5 Å, respectively suggesting organization at supramolecular level.

Keywords: phosphorus-containing monomers, polarized light microscopy, structure investigation, thermotropic liquid crystalline properties

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Authors: Rara Wulan Anggareni, Narita Putri, Riski Septianing Astuti

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Breastfeeding is a key to prevent mortality and morbidity in children. It is also the second highest risk responsible for Disability Adjusted Life Years (DALYs) among children below five years old. UNICEF estimates that during 1995 – 2003, there are only about 38% infants in developing countries who get to be exclusively breastfed during the first six months of their lives. According to Demography and Health Survey in Indonesia 2007, breastfeed practice rate still considered as low which is about 41%. One of the factors causing the low breastfeed practice rate in Indonesia is the anxiety and postpartum depression, and also the weanling dilemma in which mother feels that her breastmilk cannot suffice infant needs. Those factors finally resulting into low or even stopped production of breastmilk. Breastmilk production can be enhanced by consuming food containing phytosterol and lactogoga effect. Food with the highest phytosterol level is Sauropus androgynus (L.) Merr leaf (merr leaf). In this study, we made alternative food which named Chocomerr for breastfeeding mothers. Chocomerr consists of merr leaves which have lactogoga effect and chocolate for relaxation. Based on organoleptic tests conducted towards 2 age groups, which are 18 – 21 and 25 – 40 years old, this product gets good acceptance in taste, texture, and colour categories. Chocomerr can be used as an alternative way for increasing breastmilk production to aim for the decreasing number of DALYs among children aged under 5 years old.

Keywords: breastfeeding, increasing, chocolate, merr leaves

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Authors: Sang-Keun Moon, Hong-Rok Lim, Jin-O Kim

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This paper presents a Power Quality (PQ) modeling and filtering processes for the distribution system disturbances using recognition learning methods. Typical PQ waveforms with mathematical applications and gathered field data are applied to the proposed models. The objective of this paper is analyzing PQ data with respect to monitoring, discriminating, and evaluating the waveform of power disturbances to ensure the system preventative system failure protections and complex system problem estimations. Examined signal filtering techniques are used for the field waveform noises and feature extractions. Using extraction and learning classification techniques, the efficiency was verified for the recognition of the PQ disturbances with focusing on interactive modeling methods in this paper. The waveform of selected 8 disturbances is modeled with randomized parameters of IEEE 1159 PQ ranges. The range, parameters, and weights are updated regarding field waveform obtained. Along with voltages, currents have same process to obtain the waveform features as the voltage apart from some of ratings and filters. Changing loads are causing the distortion in the voltage waveform due to the drawing of the different patterns of current variation. In the conclusion, PQ disturbances in the voltage and current waveforms indicate different types of patterns of variations and disturbance, and a modified technique based on the symmetrical components in time domain was proposed in this paper for the PQ disturbances detection and then classification. Our method is based on the fact that obtained waveforms from suggested trigger conditions contain potential information for abnormality detections. The extracted features are sequentially applied to estimation and recognition learning modules for further studies.

Keywords: power quality recognition, PQ modeling, waveform feature extraction, disturbance trigger condition, PQ signal filtering

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Authors: R. Poonkuzhali, M. Y. Sanavullah, M. R. Gurupriya

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Opportunistic routing is used, where the network has the features like dynamic topology changes and intermittent network connectivity. In Delay Tolerant network or Disruption tolerant network opportunistic forwarding technique is widely used. The key idea of opportunistic routing is selecting forwarding nodes to forward data and coordination among these nodes to avoid duplicate transmissions. This paper gives the analysis of pros and cons of various opportunistic routing techniques used in MANET.

Keywords: ETX, opportunistic routing, PSR, throughput

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Authors: Lorenzo Buti

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This paper investigates the nature of democratic action through a critical reading of Claude Lefort’s notion of the democratic ‘regime’. Lefort provides one of the most innovative accounts of the essential features of a democratic regime. According to him, democracy is a political regime that acknowledges the indeterminacy of a society and stages it as a contestation between competing political actors. As such, democracy provides the symbolic markers of society’s openness towards the future. However, despite their democratic features, the recent decades in late capitalist societies attest to a sense of the future becoming fixed and predetermined. This suggests that Lefort’s conception of democracy harbours a misunderstanding of the character and experience of democratic action. This paper examines this underlying tension in Lefort’s work. It claims that Lefort underestimates how a democratic regime, next to its symbolic function, also takes a materially constituted form with its particular dynamics of power relations. Lefort’s systematic dismissal of this material dimension for democratic action can lead to the contemporary paradoxical situation where democracy’s symbolic markers are upheld (free elections, public debate, dynamic between government and opposition in parliament,…) but the room for political decision-making is constrained due to a myriad of material constraints (e.g., market pressures, institutional inertias). The paper draws out the implications for the notion of democratic action. Contra Lefort, it argues that democratic action necessarily targets the material conditions that impede the capacity for decision-making on the basis of equality and liberty. This analysis shapes our understanding of democratic action in two ways. First, democratic action takes an asymmetrical, insurgent form, as a contestation of material power relations from below. Second, it reveals an ambivalent position vis-à-vis the political regime: democratic action is symbolically made possible by the democratic dispositive, but it contests the constituted form that the democratic regime takes.

Keywords: Claude Lefort, democratic action, material constitution, political regime

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Authors: Kuo-Cheng Liu

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In the latest research efforts, the structures of the image in the spatial domain have been successfully analyzed and proved to deduce the visual masking for accurately estimating the visibility thresholds of the image. If the structural properties of the video sequence in the temporal domain are taken into account to estimate the temporal masking, the improvement and enhancement of the as-sessing spatio-temporal visibility thresholds are reasonably expected. In this paper, the temporal characteristics of human perception to the change in block structures on the time axis are analyzed. The temporal characteristics of human perception are represented in terms of the significant variation in block structures for the analysis of human visual system (HVS). Herein, the block structure in each frame is computed by combined the pattern masking and the contrast masking simultaneously. The contrast masking always overestimates the visibility thresholds of edge regions and underestimates that of texture regions, while the pattern masking is weak on a uniform background and is strong on the complex background with spatial patterns. Under considering the significant variation of block structures between successive frames, we extend the block structures of images in the spatial domain to that of video sequences in the temporal domain to analyze the relation between the inter-frame variation of structures and the temporal masking. Meanwhile, the subjective viewing test and the fair rating process are designed to evaluate the consistency of the temporal characteristics with the HVS under a specified viewing condition.

Keywords: temporal characteristic, block structure, pattern masking, contrast masking

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Authors: Abdel Khalek Selim, Safaa Mahmoud

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Experiments were designed to study nitrogen loss through leaching in soil columns treated with different nitrogen sources and elemental sulfur. The soil material (3 kg alluvial or calcareous soil) were packed in Plexiglas columns (10 cm diameter). The soil columns were treated with 2 g N in the form of Ca(NO3)2, urea, urea + inhibitor (Nitrapyrin), another set of these treatments was prepared to add elemental sulfur. During incubation period, leaching was performed by applying a volume of water that allows the percolation of 250-ml water throughout the soil column. The leachates were analyzed for NH4-N and N03-N. After 10 weeks, soil columns were cut into four equal segments and analyzed for ammonium, nitrate, and total nitrogen. Results indicated the following: Ca(NO3)2 treatment showed a rapid NO3 leaching, especially in the first 3 weeks, in both clay and calcareous soils. This means that soil texture did not play any role in this respect. Sulfur addition also did not affect the rate of NO3 leaching. In urea treatment, there was a steady increase of NH4- and NO3–N from one leachate to another. Addition of sulfur with urea slowed down the nitrification process and decreased N losses. Clay soil contained residual N much more than calcareous soil. Almost one-third of added nitrogen might have been immobilized by soil microorganisms or lost through other loss paths. Nitrification inhibitor can play a role in preserving added nitrogen from being lost through leaching. Combining the inhibitor with elemental sulfur may help to stabilize certain preferred ratio of NH4 to NO3 in the soil for the benefit of the growing plants.

Keywords: alluvial soil, calcareous soil, elemental sulfur, nitrate leaching

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Authors: Rafik Balti, Nourhene Zayoud, Mohamed Ben Mansour, Abdellah Arhaliass, Anthony Masse

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Application of edible films and coatings with natural active compounds for enhancing storage stability of food products is a promising active packaging approach. Shrimp are generally known as valuable seafood products around the world because of their delicacy and good nutritional. However, shrimp is highly vulnerable to quality deterioration associated with biochemical, microbiological or physical changes during postmortem storage, which results in the limited shelf life of the product. Chitosan is considered as a functional packaging component for maintaining the quality and increasing the shelf life of perishable foods. The present study was conducted to evaluate edible coating of crab chitosan containing variable levels of ethanolic extract of Spirulina on microbiological (mesophilic aerobic, psychrotrophic, lactic acid bacteria, and enterobacteriacea), chemical (pH, TVB-N, TMA-N, PV, TBARS) and sensory (odor, color, texture, taste, and overall acceptance) properties of shrimp during refrigerated storage. Also, textural and color characteristics of coated shrimp were performed. According to the obtained results, crab chitosan in combination with Spirulina extract was very effective in order to extend the shelf life of shrimp during storage in refrigerated condition.

Keywords: food packaging, chitosan, spirulina extract, white shrimp, shelf life

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Authors: H. Djaaboube, I. Loucif, Y. Bouachiba, R. Aouati, A. Maameri, A. Taabouche, A. Bouabellou

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Thin films of pure and barium-doped zinc oxide (ZnO) were prepared using a spray pyrolysis process. The films were deposited on glass substrates at 450°C. The different samples are characterized by X-ray diffraction (XRD) and UV-Vis spectroscopy. X-ray diffraction patterns reveal the formation of a single ZnO Wurtzite structure and the good crystallinity of the films. The substitution of Ba ions influences the texture of the layers and makes the (002) plane a preferential growth plane. At concentrations below 6% Ba, the hexagonal structure of ZnO undergoes compressive stresses due to barium ions which have a radius twice of the Zn ions. This result leads to the decrees of a and c parameters and, therefore, the volume of the unit cell. This result is confirmed by the decrease in the number of crystallites and the increase in the size of the crystallites. At concentrations above 6%, barium substitutes the zinc atom and modifies the structural parameters of the thin layers. The bandgap of ZnO films decreased with increasing doping; this decrease is probably due to the 4d orbitals of the Ba atom due to the sp-d spin-exchange interactions between the band electrons and the localized d-electrons of the substituted Ba ion. Although, the Urbache energy undergoes an increase which implies the creation of energy levels below the conduction band and decreases the band gap width. The photocatalytic activity of ZnO doped 9% Ba was evaluated by the photodegradation of methylene blue under UV irradiation.

Keywords: barium, doping, photodegradation, spray pyrolysis, ZnO

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Authors: Sweeti, Anoop Kant Godiyal, Neha Singh, Sneh Anand, B. K. Panigrahi, Jayasree Santhosh

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This work is about developing a tool for visualization and segmentation of Electroencephalograph (EEG) signals based on frequency domain features. Change in the frequency domain characteristics are correlated with change in mental state of the subject under study. Proposed algorithm provides a way to represent the change in the mental states using the different frequency band powers in form of segmented EEG signal. Many segmentation algorithms have been suggested in literature having application in brain computer interface, epilepsy and cognition studies that have been used for data classification. But the proposed method focusses mainly on the better presentation of signal and that’s why it could be a good utilization tool for clinician. Algorithm performs the basic filtering using band pass and notch filters in the range of 0.1-45 Hz. Advanced filtering is then performed by principal component analysis and wavelet transform based de-noising method. Frequency domain features are used for segmentation; considering the fact that the spectrum power of different frequency bands describes the mental state of the subject. Two sliding windows are further used for segmentation; one provides the time scale and other assigns the segmentation rule. The segmented data is displayed second by second successively with different color codes. Segment’s length can be selected as per need of the objective. Proposed algorithm has been tested on the EEG data set obtained from University of California in San Diego’s online data repository. Proposed tool gives a better visualization of the signal in form of segmented epochs of desired length representing the power spectrum variation in data. The algorithm is designed in such a way that it takes the data points with respect to the sampling frequency for each time frame and so it can be improved to use in real time visualization with desired epoch length.

Keywords: de-noising, multi-channel data, PCA, power spectra, segmentation

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Authors: Jaehong Yu, Seoung Bum Kim

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Clustering analysis can facilitate the extraction of intrinsic patterns in a dataset and reveal its natural groupings without requiring class information. For effective clustering analysis in high dimensional datasets, unsupervised dimensionality reduction is an important task. Unsupervised dimensionality reduction can generally be achieved by feature extraction or feature selection. In many situations, feature selection methods are more appropriate than feature extraction methods because of their clear interpretation with respect to the original features. The unsupervised feature selection can be categorized as feature subset selection and feature ranking method, and we focused on unsupervised feature ranking methods which evaluate the features based on their importance scores. Recently, several unsupervised feature ranking methods were developed based on ensemble approaches to achieve their higher accuracy and stability. However, most of the ensemble-based feature ranking methods require the true number of clusters. Furthermore, these algorithms evaluate the feature importance depending on the ensemble clustering solution, and they produce undesirable evaluation results if the clustering solutions are inaccurate. To address these limitations, we proposed an ensemble-based feature ranking method with random subspace and multiple-k ensemble (FRRM). The proposed FRRM algorithm evaluates the importance of each feature with the random subspace ensemble, and all evaluation results are combined with the ensemble importance scores. Moreover, FRRM does not require the determination of the true number of clusters in advance through the use of the multiple-k ensemble idea. Experiments on various benchmark datasets were conducted to examine the properties of the proposed FRRM algorithm and to compare its performance with that of existing feature ranking methods. The experimental results demonstrated that the proposed FRRM outperformed the competitors.

Keywords: clustering analysis, multiple-k ensemble, random subspace-based feature evaluation, unsupervised feature ranking

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Authors: Jorge Iván Bañol-Betancur, Lina María Martínez-Sánchez, María de los Ángeles Rodríguez-Gázquez, Estefanía Bahamonde-Olaya, Ana María Gutiérrez-Tamayo, Laura Isabel Jaramillo-Jaramillo, Camilo Ruiz-Mejía, Natalia Morales-Quintero

Abstract:

Acute chest pain is a distressing sensation between the diaphragm and the base of the neck and it represents a diagnostic challenge for any physician in the emergency department. Objective: To establish the main clinical and epidemiological characteristics of patients who present with chest pain to the emergency department in a private clinic from the city of Medellin, during 2014-2015. Methods: Cross-sectional retrospective observational study. Population and sample were patients who consulted for chest pain in the emergency department who met the eligibility criteria. The information was analyzed in SPSS program vr.21; qualitative variables were described through relative frequencies, and the quantitative through mean and standard deviation ‬or medians according to their distribution in the study population. Results: A total of 231 patients were evaluated, the mean age was 49.5 ± 19.9 years, 56.7% were females. The most frequent pathological antecedents were hypertension 35.5%, diabetes 10,8%, dyslipidemia 10.4% and coronary disease 5.2%. Regarding pain features, in 40.3% of the patients the pain began abruptly, in 38.2% it had a precordial location, for 20% of the cases physical activity acted as a trigger, and 60.6% was oppressive. Costochondritis was the most common cause of chest pain among patients with an established etiologic diagnosis, representing the 18.2%. Conclusions: Although the clinical features of pain reported coincide with the clinical presentation of an acute coronary syndrome, the most common cause of chest pain in study population was costochondritis instead, indicating that it is a differential diagnostic in the approach of patients with pain acute chest.

Keywords: acute coronary syndrome, chest pain, epidemiology, osteochondritis

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Authors: Alireza Rafieerad, Bushroa Abd Razak, Bahman Nasiri Tabrizi, Jamunarani Vadivelu

Abstract:

Recently, reports on the fabrication of nanotubular arrays have generated considerable scientific interest, owing to the broad range of applications of the oxide nanotubes in solar cells, orthopedic and dental implants, photocatalytic devices as well as lithium-ion batteries. A more attractive approach for the fabrication of oxide nanotubes with controllable morphology is the electrochemical anodization of substrate in a fluoride-containing electrolyte. Consequently, titanium dioxide nanotubes (TiO2 NTs) have been highly considered as an applicable material particularly in the district of artificial implants. In addition, regarding long-term efficacy and reasons of failing and infection after surgery of currently used dental implants required to enhance the cytocompatibility properties of Ti-based bone-like tissue. As well, graphene oxide (GO) with relevant biocompatibility features in tissue sites, osseointegration and drug delivery functionalization was fully understood. Besides, the boasting antibacterial ability of silver (Ag) remarkably provided for implantable devices without infection symptoms. Here, surface modification of Ti–6Al–7Nb implants (Ti67IMP) by the development of Ag/GO co-decorated TiO2 NTs was examined. Initially, the anodic TiO2 nanotubes obtained at a constant potential of 60 V were annealed at 600 degree centigrade for 2 h to improve the adhesion of the coating. Afterward, the Ag/GO co-decorated TiO2 NTs were developed by spin coating on Ti67IM. The microstructural features, phase composition and wettability behavior of the nanostructured coating were characterized comparably. In a nutshell, the results of the present study may contribute to the development of the nanostructured Ti67IMP with improved surface properties.

Keywords: anodic tio2 nanotube, biomedical applications, graphene oxide, silver, spin coating

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Authors: Ainouna Bouziane

Abstract:

The ability of Electron Tomography to recover the 3D structure of catalysts, with spatial resolution in the subnanometer scale, has been widely explored and reviewed in the last decades. A variety of experimental techniques, based either on Transmission Electron Microscopy (TEM) or Scanning Transmission Electron Microscopy (STEM) have been used to reveal different features of nanostructured catalysts in 3D, but High Angle Annular Dark Field imaging in STEM mode (HAADF-STEM) stands out as the most frequently used, given its chemical sensitivity and avoidance of imaging artifacts related to diffraction phenomena when dealing with crystalline materials. In this regard, our group has developed a methodology that combines image denoising by undecimated wavelet transforms (UWT) with automated, advanced segmentation procedures and parameter selection methods using CS-TVM (Compressed Sensing-total variation minimization) algorithms to reveal more reliable quantitative information out of the 3D characterization studies. However, evaluating the accuracy of the magnitudes estimated from the segmented volumes is also an important issue that has not been properly addressed yet, because a perfectly known reference is needed. The problem particularly complicates in the case of multicomponent material systems. To tackle this key question, we have developed a methodology that incorporates volume reconstruction/segmentation methods. In particular, we have established an approach to evaluate, in quantitative terms, the accuracy of TVM reconstructions, which considers the influence of relevant experimental parameters like the range of tilt angles, image noise level or object orientation. The approach is based on the analysis of material-realistic, 3D phantoms, which include the most relevant features of the system under analysis.

Keywords: electron tomography, supported catalysts, nanometrology, error assessment

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Authors: Carol Anne Hargreaves

Abstract:

A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.

Keywords: machine learning, stock market trading, logistic regression, cluster analysis, factor analysis, decision trees, neural networks, automated stock investment system

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Authors: Toka Aly

Abstract:

Historically, marketplaces were the most important nodes and focal points of cities, where different activities took place. Commercial streets offer more than just spaces for shopping; they also offer choices for social activities and cultural exchange. They are considered the backbone of the city’s vibrancy and vitality. Despite that, the public life in Cairo’s commercial streets has deteriorated, where the shopping activities became reliant mainly on 'planned formal places', mainly in privatized or indoor spaces like shopping malls. The main aim of this paper is to explore the key elements and tools of assessing the successfulness of commercial streets in Cairo. The methodology followed in this paper is based on a case study methodology (multiple cases) that is based on assessing and analyzing the physical and social elements in historical and contemporary commercial streets in El Muiz Street and Baghdad Street in Cairo. The data collection is based on personal observations, photographs, maps and street sections. Findings indicate that the key factors of analyzing commercial streets are factors affecting the sensory experience, factors affecting the social behavior, and general aspects that attract people. Findings also indicate that urban features have clear influence on shopping pedestrian activities in both streets. Moreover, in order for a commercial street to be successful, shopping patterns must provide people with a quality public space that can provide easy navigation and accessibility, good visual continuity, and well-designed urban features and social gathering. Outcomes of this study will be a significant endeavor in providing a good background for urban designers on analyzing and assessing successfulness of commercial streets. The study will also help in understanding the different physical and social pattern of vending activities taking place in Cairo.

Keywords: activities, commercial street, marketplace, successful, vending

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Authors: Lovorka Galetic, Zeljko Vukelic

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The advanced concepts of strategic and innovation management in the sphere of company dynamic and innovation capabilities, and achieving their mutual alignment and a synergy effect, are important elements in business today. This paper analyses the theory and empirically investigates the influence of a company’s dynamic capabilities on its innovation capabilities. A new multidimensional model of dynamic capabilities is presented, consisting of five factors appropriate to real time requirements, while innovation capabilities are considered pursuant to the official OECD and Eurostat standards. After examination of dynamic and innovation capabilities indicated their theoretical links, the empirical study testing the model and examining the influence of a company’s dynamic capabilities on its innovation capabilities showed significant results. In the study, a research model was posed to relate company dynamic and innovation capabilities. One side of the model features the variables that are the determinants of dynamic capabilities defined through their factors, while the other side features the determinants of innovation capabilities pursuant to the official standards. With regard to the research model, five hypotheses were set. The study was performed in late 2014 on a representative sample of large and very large Croatian enterprises with a minimum of 250 employees. The research instrument was a questionnaire administered to company top management. For both variables, the position of the company was tested in comparison to industry competitors, on a fivepoint scale. In order to test the hypotheses, correlation tests were performed to determine whether there is a correlation between each individual factor of company dynamic capabilities with the existence of its innovation capabilities, in line with the research model. The results indicate a strong correlation between a company’s possession of dynamic capabilities in terms of their factors, due to the new multi-dimensional model presented in this paper, with its possession of innovation capabilities. Based on the results, all five hypotheses were accepted. Ultimately, it was concluded that there is a strong association between the dynamic and innovation capabilities of a company. 

Keywords: dynamic capabilities, innovation capabilities, competitive advantage, business results

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Authors: Isabella Jabbour

Abstract:

The world's population is expected to reach over 10 billion by 2050, creating a significant demand for food production, particularly in the agricultural industry. Cellular agriculture presents a solution to this challenge by producing meat that resembles traditionally produced meat, but with significantly less land use. Decellularized plant scaffolds, such as spinach leaves, have been shown to be a suitable edible scaffold for growing animal muscle, enabling cultured cells to grow and organize into three-dimensional structures that mimic the texture and flavor of conventionally produced meat. However, the use of freshwater to remove the intact extracellular material from these plants remains a concern, particularly when considering scaling up the production process. In this study, two protocols were used, 1X SDS and Boom Sauce, to decellularize spinach leaves with both distilled water and ocean water. The decellularization process was confirmed by histology, which showed an absence of cell nuclei, DNA and protein quantification. Results showed that spinach decellularized with ocean water contained 9.9 ± 1.4 ng DNA/mg tissue, which is comparable to the 9.2 ± 1.1 ng DNA/mg tissue obtained with DI water. These findings suggest that decellularized spinach leaves using ocean water hold promise as an eco-friendly and cost-effective scaffold for laboratory-grown meat production, which could ultimately transform the meat industry by providing a sustainable alternative to traditional animal farming practices while reducing freshwater use.

Keywords: cellular agriculture, plant scaffold, decellularization, ocean water usage

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Authors: B. S. Akhmetov, A. I. Ivanov, T. S. Kartbayev, A. Y. Malygin, K. Mukapil, S. D. Tolybayev

Abstract:

The article examines the testing of the neural network converter of biometrics code. Determined the main reasons that prevented the use adopted in the works of foreign researchers classical a Binomial Law when describing distribution of measures of Hamming "Alien" codes-responses.

Keywords: biometrics, testing, neural network, converter of biometrics-code, Hamming's measure

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Authors: S. Sulochana Singha

Abstract:

Dhiyan or Dehan is the name of the community and language spoken by the Koch-Rajbangshi people of Barak Valley of Assam. Ethnically, they are Mongoloids, and their language belongs to the Indo-Aryan language family. However, Dhiyan is absent in any classification of Indo-Aryan languages. So the classification of Dhiyan language under the Indo-Aryan language family is completely based on the shared typological features of the other Indo-Aryan languages. Typologically, Dhiyan is an agglutinating language, and it shares many features of Indo-Aryan languages like presence of aspirated voiced stops, non-tonal, verb-person agreement, adjectives as different word class, prominent tense and subject object verb word order. Reduplication is a productive word-formation process in Dhiyan. Besides it also expresses plurality, intensification, and distributive. Generally, reduplication in Dhiyan can be at the morphological or lexical level. Morphological reduplication in Dhiyan involves expressives which includes onomatopoeias, sound symbolism, idiophones, and imitatives. Lexical reduplication in the language can be formed by echo formations and word reduplication. Echo formation in Dhiyan is formed by partial repetition from the base word which can be either consonant alternation or vowel alternation. The consonant alternation is basically found in onset position while the alternation of vowel is basically found in open syllable particularly in final syllable. Word reduplication involves reduplication of nouns, interrogatives, adjectives, and numerals which further can be class changing or class maintaining reduplication. The process of reduplication can be partial or complete whether it is lexical or morphological. The present paper is an attempt to describe some aspects of the formation, function, and usage of reduplications in Dhiyan which is mainly spoken in ten villages in the Eastern part of Barak River in the Cachar District of Assam.

Keywords: Barak-Valley, Dhiyan, Indo-Aryan, reduplication

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