Search results for: cassava processing waste

Authors: Eugene Y. J. Aw, J. W. Koh, S. H. Chew, K. E. Chua, Lionel L. J. Ang, Algernon C. S. Hong, Danette S. E. Tan, Grace H. B. Foo, K. Q. Hong, L. M. Cheng, M. L. Leong

Abstract:

This paper presents a novel rapid soil classification technique that combines computer vision with four-probe soil electrical resistivity method and cone penetration test (CPT), to improve the accuracy and productivity of on-site classification of excavated soil. In Singapore, excavated soils from local construction projects are transported to Staging Grounds (SGs) to be reused as fill material for land reclamation. Excavated soils are mainly categorized into two groups (“Good Earth” and “Soft Clay”) based on particle size distribution (PSD) and water content (w) from soil investigation reports and on-site visual survey, such that proper treatment and usage can be exercised. However, this process is time-consuming and labour-intensive. Thus, a rapid classification method is needed at the SGs. Computer vision, four-probe soil electrical resistivity and CPT were combined into an innovative non-destructive and instantaneous classification method for this purpose. The computer vision technique comprises soil image acquisition using industrial grade camera; image processing and analysis via calculation of Grey Level Co-occurrence Matrix (GLCM) textural parameters; and decision-making using an Artificial Neural Network (ANN). Complementing the computer vision technique, the apparent electrical resistivity of soil (ρ) is measured using a set of four probes arranged in Wenner’s array. It was found from the previous study that the ANN model coupled with ρ can classify soils into “Good Earth” and “Soft Clay” in less than a minute, with an accuracy of 85% based on selected representative soil images. To further improve the technique, the soil strength is measured using a modified mini cone penetrometer, and w is measured using a set of time-domain reflectometry (TDR) probes. Laboratory proof-of-concept was conducted through a series of seven tests with three types of soils – “Good Earth”, “Soft Clay” and an even mix of the two. Validation was performed against the PSD and w of each soil type obtained from conventional laboratory tests. The results show that ρ, w and CPT measurements can be collectively analyzed to classify soils into “Good Earth” or “Soft Clay”. It is also found that these parameters can be integrated with the computer vision technique on-site to complete the rapid soil classification in less than three minutes.

Keywords: Computer vision technique, cone penetration test, electrical resistivity, rapid and non-destructive, soil classification

Procedia PDF Downloads 184

Authors: Katsue Edo, Yu Hiroi

Abstract:

T Increasing attention has been paid to using pictures and photographs in research since the beginning of the 21th century in social sciences. Meanwhile we have been studying the usefulness of Picture mining, which is one of the new ways for a these picture using researches. Picture Mining is an explorative research analysis method that takes useful information from pictures, photographs and static or moving images. It is often compared with the methods of text mining. The Picture Mining concept includes observational research in the broad sense, because it also aims to analyze moving images (Ochihara and Edo 2013). In the recent literature, studies and reports using pictures are increasing due to the environmental changes. These are identified as technological and social changes (Edo et.al. 2013). Low price digital cameras and i-phones, high information transmission speed, low costs for information transferring and high performance and resolution of the cameras of mobile phones have changed the photographing behavior of people. Consequently, there is less resistance in taking and processing photographs for most of the people in the developing countries. In these studies, this method of collecting data from respondents is often called as ‘participant-generated photography’ or ‘respondent-generated visual imagery’, which focuses on the collection of data and its analysis (Pauwels 2011, Snyder 2012). But there are few systematical and conceptual studies that supports it significance of these methods. We have discussed in the recent years to conceptualize these picture using research methods and formalize theoretical findings (Edo et. al. 2014). We have identified the most efficient fields of Picture mining in the following areas inductively and in case studies; 1) Research in Consumer and Customer Lifestyles. 2) New Product Development. 3) Research in Fashion and Design. Though we have found that it will be useful in these fields and areas, we must verify these assumptions. In this study we will focus on the field of fashion and design, to determine whether picture mining methods are really reliable in this area. In order to do so we have conducted an empirical research of the respondents’ attitudes and behavior concerning pictures and photographs. We compared the attitudes and behavior of pictures toward fashion to meals, and found out that taking pictures of fashion is not as easy as taking meals and food. Respondents do not often take pictures of fashion and upload their pictures online, such as Facebook and Instagram, compared to meals and food because of the difficulty of taking them. We concluded that we should be more careful in analyzing pictures in the fashion area for there still might be some kind of bias existing even if the environment of pictures have drastically changed in these years.

Keywords: empirical research, fashion and design, Picture Mining, qualitative research

Procedia PDF Downloads 339

Authors: Mohammadreza Hedyehzadeh, Mahdi Yousefi

Abstract:

Colon cancer is one of the most common cancer, which predicted to increase its prevalence due to the bad eating habits of peoples. Nowadays, due to the busyness of people, the use of fast foods is increasing, and therefore, diagnosis of this disease and its treatment are of particular importance. To determine the best treatment approach for each specific colon cancer patients, the oncologist should be known the stage of the tumor. The most common method to determine the tumor stage is TNM staging system. In this system, M indicates the presence of metastasis, N indicates the extent of spread to the lymph nodes, and T indicates the size of the tumor. It is clear that in order to determine all three of these parameters, an imaging method must be used, and the gold standard imaging protocols for this purpose are CT and PET/CT. In CT imaging, due to the use of X-rays, the risk of cancer and the absorbed dose of the patient is high, while in the PET/CT method, there is a lack of access to the device due to its high cost. Therefore, in this study, we aimed to estimate the tumor size and the extent of its spread to the lymph nodes using MR images. More than 1300 MR images collected from the TCIA portal, and in the first step (pre-processing), histogram equalization to improve image qualities and resizing to get the same image size was done. Two expert radiologists, which work more than 21 years on colon cancer cases, segmented the images and extracted the tumor region from the images. The next step is feature extraction from segmented images and then classify the data into three classes: T0N0، T3N1 و T3N2. In this article, the VGG-16 convolutional neural network has been used to perform both of the above-mentioned tasks, i.e., feature extraction and classification. This network has 13 convolution layers for feature extraction and three fully connected layers with the softmax activation function for classification. In order to validate the proposed method, the 10-fold cross validation method used in such a way that the data was randomly divided into three parts: training (70% of data), validation (10% of data) and the rest for testing. It is repeated 10 times, each time, the accuracy, sensitivity and specificity of the model are calculated and the average of ten repetitions is reported as the result. The accuracy, specificity and sensitivity of the proposed method for testing dataset was 89/09%, 95/8% and 96/4%. Compared to previous studies, using a safe imaging technique (MRI) and non-use of predefined hand-crafted imaging features to determine the stage of colon cancer patients are some of the study advantages.

Keywords: colon cancer, VGG-16, magnetic resonance imaging, tumor size, lymph node metastasis

Procedia PDF Downloads 38

Authors: Eva Šmelová, Alena Berčíková

Abstract:

The issue of school maturity and readiness of a child for a successful start of compulsory education is one of the long-term monitored areas, especially in the context of education and psychology. In the context of the curricular reform in the Czech Republic, the issue has recently gained importance. Analyses of research in this area suggest a lack of a broader overview of indicators informing about the current level of children’s school maturity and school readiness. Instead, various studies address partial issues. Between 2009 and 2013 a research study was performed at the Faculty of Education, Palacký University Olomouc (Czech Republic) focusing on children’s maturity and readiness for compulsory education. In this study, social skills were of marginal interest; the main focus was on the mental area. This previous research is smoothly linked with the present study, the objective of which is to identify the level of school maturity and school readiness in selected characteristics of social skills as part of the adaptation process after enrolment in compulsory education. In this context, the following research question has been formulated: During the process of adaptation to the school environment, which social skills are weakened? The method applied was observation, for the purposes of which the authors developed a research tool – record sheet with 11 items – social skills that a child should have by the end of preschool education. The items were assessed by first-grade teachers at the beginning of the school year. The degree of achievement and intensity of the skills were assessed for each child using an assessment scale. In the research, the authors monitored a total of three independent variables (gender, postponement of school attendance, participation in inclusive education). The effect of these independent variables was monitored using 11 dependent variables. These variables are represented by the results achieved in selected social skills. Statistical data processing was assisted by the Computer Centre of Palacký University Olomouc. Statistical calculations were performed using SPSS v. 12.0 for Windows and STATISTICA: StatSoft STATISTICA CR, Cz (software system for data analysis). The research sample comprised 115 children. In their paper, the authors present the results of the research and at the same time point to possible areas of further investigation. They also highlight possible risks associated with weakened social skills.

Keywords: compulsory education, curricular reform, educational diagnostics, pupil, school curriculum, school maturity, school readiness, social skills

Procedia PDF Downloads 228

Authors: Päärn Paiste, Margit Kõiv, Riho Mõtlep, Kalle Kirsimäe

Abstract:

For small-scale wastewater management, the treatment wetlands (TWs) as a low cost alternative to conventional treatment facilities, can be used. However, P removal capacity of TW systems is usually problematic. P removal in TWs is mainly dependent on the physico–chemical and hydrological properties of the filter material. Highest P removal efficiency has been shown trough Ca-phosphate precipitation (i.e. active filtration) in Ca-rich alkaline filter materials, e.g. industrial by-products like hydrated oil shale ash (HOSA), metallurgical slags. In this contribution we report preliminary results of a full-scale TW system using HOSA material for P removal for a municipal wastewater at Nõo site, Estonia. The main goals of this ongoing project are to evaluate: a) the long-term P removal efficiency of HOSA using real waste water; b) the effect of high organic loading rate; c) variable P-loading effects on the P removal mechanism (adsorption/direct precipitation); and d) the form and composition of phosphate precipitates. Onsite full-scale experiment with two concurrent filter systems for treatment of municipal wastewater was established in September 2013. System’s pretreatment steps include septic tank (2 m2) and vertical down-flow LECA filters (3 m2 each), followed by horizontal subsurface HOSA filters (effective volume 8 m3 each). Overall organic and hydraulic loading rates of both systems are the same. However, the first system is operated in a stable hydraulic loading regime and the second in variable loading regime that imitates the wastewater production in an average household. Piezometers for water and perforated sample containers for filter material sampling were incorporated inside the filter beds to allow for continuous in-situ monitoring. During the 18 months of operation the median removal efficiency (inflow to outflow) of both systems were over 99% for TP, 93% for COD and 57% for TN. However, we observed significant differences in the samples collected in different points inside the filter systems. In both systems, we observed development of preferred flow paths and zones with high and low loadings. The filters show formation and a gradual advance of a “dead” zone along the flow path (zone with saturated filter material characterized by ineffective removal rates), which develops more rapidly in the system working under variable loading regime. The formation of the “dead” zone is accompanied by the growth of organic substances on the filter material particles that evidently inhibit the P removal. Phase analysis of used filter materials using X-ray diffraction method reveals formation of minor amounts of amorphous Ca-phosphate precipitates. This finding is supported by ATR-FTIR and SEM-EDS measurements, which also reveal Ca-phosphate and authigenic carbonate precipitation. Our first experimental results demonstrate that organic pollution and loading regime significantly affect the performance of hydrated ash filters. The material analyses also show that P is incorporated into a carbonate substituted hydroxyapatite phase.

Keywords: active filtration, apatite, hydrated oil shale ash, organic pollution, phosphorus

Procedia PDF Downloads 254

Authors: C. Brecher, M. Fey, F. Du Bois-Reymond, S. Neus

Abstract:

Additive manufacturing has emerged into a fast-growing section within the manufacturing technologies. Established machine tool manufacturers, such as DMG MORI, recently presented machine tools combining milling and laser welding. By this, machine tools can realize a higher degree of flexibility and a shorter production time. Still there are challenges that have to be accounted for in terms of maintaining the necessary machining accuracy - especially due to thermal effects arising through the use of high power laser processing units. To study the thermal behavior of laser-integrated machine tools, it is essential to analyze and simulate the thermal behavior of machine components, individual and assembled. This information will help to design a geometrically stable machine tool under the influence of high power laser processes. This paper presents an approach to decrease the loss of machining precision due to thermal impacts. Real effects of laser machining processes are considered and thus enable an optimized design of the machine tool, respective its components, in the early design phase. Core element of this approach is a matched FEM model considering all relevant variables arising, e.g. laser power, angle of laser beam, reflective coefficients and heat transfer coefficient. Hence, a systematic approach to obtain this matched FEM model is essential. Indicating the thermal behavior of structural components as well as predicting the laser beam path, to determine the relevant beam intensity on the structural components, there are the two constituent aspects of the method. To match the model both aspects of the method have to be combined and verified empirically. In this context, an essential machine component of a five axis machine tool, the turn-swivel table, serves as the demonstration object for the verification process. Therefore, a turn-swivel table test bench as well as an experimental set-up to measure the beam propagation were developed and are described in the paper. In addition to the empirical investigation, a simulative approach of the described types of experimental examination is presented. Concluding, it is shown that the method and a good understanding of the two core aspects, the thermo-elastic machine behavior and the laser beam path, as well as their combination helps designers to minimize the loss of precision in the early stages of the design phase.

Keywords: additive manufacturing, laser beam machining, machine tool, thermal effects

Procedia PDF Downloads 243

Authors: Martina Katalin Szabó, Bernadett Lipóczi, Csenge Guba, István Uveges

Abstract:

In this study, an exhaustive analysis was carried out about the historical development of negative emotive intensifiers in the Hungarian language via NLP methods. Intensifiers are linguistic elements which modify or reinforce a variable character in the lexical unit they apply to. Therefore, intensifiers appear with other lexical items, such as adverbs, adjectives, verbs, infrequently with nouns. Due to the complexity of this phenomenon (set of sociolinguistic, semantic, and historical aspects), there are many lexical items which can operate as intensifiers. The group of intensifiers are admittedly one of the most rapidly changing elements in the language. From a linguistic point of view, particularly interesting are a special group of intensifiers, the so-called negative emotive intensifiers, that, on their own, without context, have semantic content that can be associated with negative emotion, but in particular cases, they may function as intensifiers (e.g.borzasztóanjó ’awfully good’, which means ’excellent’). Despite their special semantic features, negative emotive intensifiers are scarcely examined in literature based on large Historical corpora via NLP methods. In order to become better acquainted with trends over time concerning the intensifiers, The exhaustively analysed a specific historical corpus, namely the Magyar TörténetiSzövegtár (Hungarian Historical Corpus). This corpus (containing 3 millions text words) is a collection of texts of various genres and styles, produced between 1772 and 2010. Since the corpus consists of raw texts and does not contain any additional information about the language features of the data (such as stemming or morphological analysis), a large amount of manual work was required to process the data. Thus, based on a lexicon of negative emotive intensifiers compiled in a previous phase of the research, every occurrence of each intensifier was queried, and the results were stored in a separate data frame. Then, basic linguistic processing (POS-tagging, lemmatization etc.) was carried out automatically with the ‘magyarlanc’ NLP-toolkit. Finally, the frequency and collocation features of all the negative emotive words were automatically analyzed in the corpus. Outcomes of the research revealed in detail how these words have proceeded through grammaticalization over time, i.e., they change from lexical elements to grammatical ones, and they slowly go through a delexicalization process (their negative content diminishes over time). What is more, it was also pointed out which negative emotive intensifiers are at the same stage in this process in the same time period. Giving a closer look to the different domains of the analysed corpus, it also became certain that during this process, the pragmatic role’s importance increases: the newer use expresses the speaker's subjective, evaluative opinion at a certain level.

Keywords: historical corpus analysis, historical linguistics, negative emotive intensifiers, semantic changes over time

Procedia PDF Downloads 204

Authors: Paulo Sérgio Ribeiro de Araújo Bogas

Abstract:

Although several studies have assumed (at least implicitly) that learners' approaches to learning develop into deeper approaches to higher education, there appears to be no clear theoretical basis for this assumption and no empirical evidence. As a scientific contribution to this discussion, a pedagogical intervention of a quasi-experimental nature was developed, with a mixed methodology, evaluating the intervention within a single curricular unit of Marketing, using cases based on real challenges of brands, business simulation, and customer projects. Primary and secondary experiences were incorporated in the intervention: the primary experiences are the experiential activities themselves; the secondary experiences result from the primary experience, such as reflection and discussion in work teams. A diversified learning relationship was encouraged through the various connections between the different members of the learning community. The present study concludes that in the same context, the student's responses can be described as students who reinforce the initial deep approach, students who maintain the initial deep approach level, and others who change from an emphasis on the deep approach to one closer to superficial. This typology did not always confirm studies reported in the literature, namely, whether the initial level of deep processing would influence the superficial and the opposite. The result of this investigation points to the inclusion of pedagogical and didactic activities that integrate different motivations and initial strategies, leading to the possible adoption of deep approaches to learning since it revealed statistically significant differences in the difference in the scores of the deep/superficial approach and the experiential level. In the case of real challenges, the categories of “attribution of meaning and meaning of studied” and the possibility of “contact with an aspirational context” for their future professional stand out. In this category, the dimensions of autonomy that will be required of them were also revealed when comparing the classroom context of real cases and the future professional context and the impact they may have on the world. Regarding the simulated practice, two categories of response stand out: on the one hand, the motivation associated with the possibility of measuring the results of the decisions taken, an awareness of oneself, and, on the other hand, the additional effort that this practice required for some of the students.

Keywords: experiential learning, higher education, mixed methods, reflective learning, marketing

Procedia PDF Downloads 63

Authors: Sana Rezig, Yosr Ben Mlik, Mounir Jaouadi, Foued Khoffi, Slah Msahli, Bernard Durand

Abstract:

Increasing interest in environmental concerns, natural fibers are once again being considered as reinforcements for polymer composites. The main objective of this study is to explore another natural resource, Typha fiber; which is renewable without production cost and available abundantly in nature. The aim of this study was to study the flexural properties of composite resin with and without reinforcing Typha leaf and stem fibers. The specimens were made by the hand-lay-up process using polyester matrix. In our work, we focused on the effect of various treatment conditions (sea water, alkali treatment and a combination of the two treatments), as a surface modifier, on the flexural properties of the Typha fibers reinforced polyester composites. Moreover, weight ratio of Typha leaf or stem fibers was investigated. Besides, both fibers from leaf and stem of Typha plant were used to evaluate the reinforcing effect. Another parameter, which is reinforcement structure, was investigated. In fact, a first composite was made with air-laid nonwoven structure of fibers. A second composite was with a mixture of fibers and resin for each kind of treatment. Results show that alkali treatment and combined process provided better mechanical properties of composites in comparison with fiber treated by sea water. The fiber weight ratio influenced the flexural properties of composites. Indeed, a maximum value of flexural strength of 69.8 and 62,32 MPa with flexural modulus of 6.16 and 6.34 GPawas observed respectively for composite reinforced with leaf and stem fibers for 12.6 % fiber weight ratio. For the different treatments carried out, the treatment using caustic soda, whether alone or after retting seawater, show the best results because it improves adhesion between the polyester matrix and the fibers of reinforcement. SEM photographs were made to ascertain the effects of the surface treatment of the fibers. By varying the structure of the fibers of Typha, the reinforcement used in bulk shows more effective results as that used in the non-woven structure. In addition, flexural strength rises with about (65.32 %) in the case of composite reinforced with a mixture of 12.6% leaf fibers and (27.45 %) in the case of a composite reinforced with a nonwoven structure of 12.6 % of leaf fibers. Thus, to better evaluate the effect of the fiber origin, the reinforcing structure, the processing performed and the reinforcement factor on the performance of composite materials, a statistical study was performed using Minitab. Thus, ANOVA was used, and the patterns of the main effects of these parameters and interaction between them were established. Statistical analysis, the fiber treatment and reinforcement structure seem to be the most significant parameters.

Keywords: flexural properties, fiber treatment, structure and weight ratio, SEM photographs, Typha leaf and stem fibers

Procedia PDF Downloads 393

Authors: Tahamina Begum, Wan Nor Azlen Wan Mohamad, Faruque Reza, Wan Rosilawati Wan Rosli

Abstract:

To assess auditory perception and cognitive function during pregnancy is necessary as the pregnant women need extra effort for attention mainly for their executive function to maintain their quality of life. This study aimed to investigate neural correlates of cognitive and behavioral processing during mid trimester pregnancy. Event-Related Potentials (ERPs) were studied by using 128-sensor net and PAS or COWA (controlled Oral Word Association), WCST (Wisconsin Card Sorting Test), RAVLTIM (Rey Auditory Verbal and Learning Test: immediate or interference recall, delayed recall (RAVLT DR) and total score (RAVLT TS) were tested for neuropsychology assessment. In total 18 subjects were recruited (n= 9 in each group; control and pregnant group). All participants of the pregnant group were within 16-27 (mid trimester) weeks gestation. Age and education matched control healthy subjects were recruited in the control group. Participants were given a standardized test of auditory cognitive function as auditory oddball paradigm during ERP study. In this paradigm, two different auditory stimuli (standard and target stimuli) were used where subjects counted silently only target stimuli with giving attention by ignoring standard stimuli. Mean differences between target and standard stimuli were compared across groups. N100 (auditory sensory ERP component) and P300 (auditory cognitive ERP component) were recorded at T3, T4, T5, T6, Cz and Pz electrode sites. An equal number of electrodes showed non-significantly shorter amplitude of N100 component (except significantly shorter at T3, P= 0.05) and non-significant longer latencies (except significantly longer latency at T5, P= 0.008) of N100 component in pregnant group comparing control. In case of P300 component, maximum electrode sites showed non-significantly higher amplitudes and equal number of sites showed non-significant shorter latencies in pregnant group comparing control. Neuropsychology results revealed the non-significant higher score of PAS, lower score of WCST, lower score of RAVLTIM and RAVLTDR in pregnant group comparing control. The results of N100 component and RAVLT scores concluded that auditory perception is mildly impaired and P300 component proved very mild cognitive dysfunction with good executive functions in second trimester of pregnancy.

Keywords: auditory perception, pregnancy, stimuli, trimester

Procedia PDF Downloads 347

Authors: Sarah A. Alotaibi, Mohammed A. Almutairi, Abdullah A. Alsayari, Adibah M. Almutairi, Somaiah K. Almubayedh

Abstract:

Concerns over the presence of acrylamide in food date back to 2002, when Swedish scientists stated that, in carbohydrate-rich foods, amounts of acrylamide were formed when cooked at high temperatures. Similar findings were reported by other researchers which, consequently, caused major international efforts to investigate dietary exposure and the subsequent health complications in order to properly manage this issue. Due to this issue, in this work, we aim to determine the acrylamide level in different foods (coffee, potato chips, biscuits, and baby food) commonly consumed by the Saudi population. In a total of forty-three samples, acrylamide was detected in twenty-three samples at levels of 12.3 to 2850 µg/kg. In reference to the food groups, the highest concentration of acrylamide was found in coffee samples (<12.3-2850 μg/kg), followed by potato chips (655-1310 μg/kg), then biscuits (23.5-449 μg/kg), whereas the lowest acrylamide level was observed in baby food (<14.75 – 126 μg/kg). Most coffee, biscuits and potato chips products contain high amount of acrylamide content and also the most commonly consumed product. Saudi adults had a mean exposure of acrylamide for coffee, potato, biscuit, and cereal (0.07439, 0.04794, 0.01125, 0.003371 µg/kg-b.w/day), respectively. On the other hand, exposure to acrylamide in Saudi infants and children to the same types of food was (0.1701, 0.1096, 0.02572, 0.00771 µg/kg-b.w/day), respectively. Most groups have a percentile that exceeds the tolerable daily intake (TDI) cancer value (2.6 µg/kg-b.w/day). Overall, the MOE results show that the Saudi population is at high risk of acrylamide-related disease in all food types, and there is a chance of cancer risk in all age groups (all values ˂10,000). Furthermore, it was found that in non-cancer risks, the acrylamide in all tested foods was within the safe limit (˃125), except for potato chips, in which there is a risk for diseases in the population. With potato and coffee as raw materials, additional studies were conducted to assess different factors, including temperature, cocking time, and additives affecting the acrylamide formation in fried potato and roasted coffee, by systematically varying processing temperatures and time values, a mitigation of acrylamide content was achieved when lowering the temperature and decreasing the cooking time. Furthermore, it was shown that the combination of the addition of chitosan and NaCl had a large impact on the formation.

Keywords: risk assessment, dietary exposure, MOA, acrylamide, hazard

Procedia PDF Downloads 28

Authors: Brandon Takahashi, Marielle Hanley, Gerry Hanley

Abstract:

The large-scale quick-service restaurant industry is a complex business to manage optimally. With over 40 suppliers providing different ingredients for food preparation and thousands of restaurants serving over 50 unique food offerings across a wide range of regions, the company must implement a quality assurance process. Businesses want to deliver quality food efficiently, reliably, and successfully at a low cost that the public wants to buy. They also want to make sure that their food offerings are never unsafe to eat or of poor quality. A good reputation (and profitable business) developed over the years can be gone in an instant if customers fall ill eating your food. Poor quality also results in food waste, and the cost of corrective actions is compounded by the reduction in revenue. Product compliance evaluation assesses if the supplier’s ingredients are within compliance with the specifications of several attributes (physical, chemical, organoleptic) that a company will test to ensure that a quality, safe to eat food is given to the consumer and will deliver the same eating experience in all parts of the country. The technical component of the evaluation includes the chemical and physical tests that produce numerical results that relate to shelf-life, food safety, and organoleptic qualities. The psychological component of the evaluation includes organoleptic, which is acting on or involving the use of the sense organs. The rubric for product compliance evaluation has four levels: (1) Ideal: Meeting or exceeding all technical (physical and chemical), organoleptic, & psychological specifications. (2) Deviation from ideal but no impact on quality: Not meeting or exceeding some technical and organoleptic/psychological specifications without impact on consumer quality and meeting all food safety requirements (3) Acceptable: Not meeting or exceeding some technical and organoleptic/psychological specifications resulting in reduction of consumer quality but not enough to lessen demand and meeting all food safety requirements (4) Unacceptable: Not meeting food safety requirements, independent of meeting technical and organoleptic specifications or meeting all food safety requirements but product quality results in consumer rejection of food offering. Sampling of products and consumer tastings within the distribution network is a second critical element of the quality assurance process and are the data sources for the statistical analyses. Each finding is not independently assessed with the rubric. For example, the chemical data will be used to back up/support any inferences on the sensory profiles of the ingredients. Certain flavor profiles may not be as apparent when mixed with other ingredients, which leads to weighing specifications differentially in the acceptability decision. Quality assurance processes are essential to achieve that balance of quality and profitability by making sure the food is safe and tastes good but identifying and remediating product quality issues before they hit the stores. Comprehensive quality assurance procedures implement human factors methodologies, and this report provides recommendations for systemic application of quality assurance processes for quick service restaurant services. This case study will review the complex decision rubric and evaluate processes to ensure the right balance of cost, quality, and safety is achieved.

Keywords: decision making, food safety, organoleptics, product compliance, quality assurance

Procedia PDF Downloads 165

Authors: Phakamani Xaba, Robert Huberts, Bilainu Oboirien

Abstract:

It has been over 200 years since margarine was discovered and manufactured using liquid oil, liquified hardstock oils and other oil phase & aqueous phase ingredients. Henry W. Bradley first used vegetable oils in liquid state and around 1871, since then; spreads have been traditionally manufactured using liquified oils. The main objective of this study was to develop a process method to produce spreads using spray dried hardstock fat powders as a structing fats in place of current liquid structuring fats. A high shear mixing system was used to condition the fat phase and the aqueous phase was prepared separately. Using a single scraped surface heat exchanger and pin stirrer, margarine was produced. The process method was developed for to produce spreads with 40%, 50% and 60% fat . The developed method was divided into three steps. In the first step, fat powders were conditioned by melting and dissolving them into liquid oils. The liquified portion of the oils were at 65 °C, whilst the spray dried fat powder was at 25 °C. The two were mixed using a mixing vessel at 900 rpm for 4 minutes. The rest of the ingredients i.e., lecithin, colorant, vitamins & flavours were added at ambient conditions to complete the fat/ oil phase. The water phase was prepared separately by mixing salt, water, preservative, acidifier in the mixing tank. Milk was also separately prepared by pasteurizing it at 79°C prior to feeding it into the aqueous phase. All the water phase contents were chilled to 8 °C. The oil phase and water phase were mixed in a tank, then fed into a single scraped surface heat exchanger. After the scraped surface heat exchanger, the emulsion was fed in a pin stirrer to work the formed crystals and produce margarine. The margarine produced using the developed process had fat levels of 40%, 50% and 60%. The margarine passed all the qualitative, stability, and taste assessments. The scores were 6/10, 7/10 & 7.5/10 for the 40%, 50% & 60% fat spreads, respectively. The success of the trials brought about differentiated knowledge on how to manufacture spreads using non micronized spray dried fat powders as hardstock. Manufacturers do not need to store structuring fats at 80-90°C and even high in winter, instead, they can adapt their processes to use fat powders which need to be stored at 25 °C. The developed process method used one scrape surface heat exchanger instead of the four to five currently used in votator based plants. The use of a single scraped surface heat exchanger translated to about 61% energy savings i.e., 23 kW per ton of product. Furthermore, it was found that the energy saved by implementing separate pasteurization was calculated to be 6.5 kW per ton of product produced.

Keywords: margarine emulsion, votator technology, margarine processing, scraped sur, fat powders

Procedia PDF Downloads 68

Authors: Priyanka Kumari Gupta, Punya Prasanna Paltani, Shrivishal Tripathi

Abstract:

This paper proposes a nonlinear photonic crystal ring resonator-based all-optical 2 × 2 switch. The nonlinear Kerr effect is used to evaluate the essential 2 x 2 components of the photonic crystal-based optical switch, including the bar and cross states. The photonic crystal comprises a two-dimensional square lattice of dielectric rods in an air background. In the background air, two different dielectric materials are used for this comparison study separately. Initially with chalcogenide glass rods, then with GaAs rods. For both materials, the operating wavelength, bandgap diagram, operating power intensities, and performance parameters, such as the extinction ratio, insertion loss, and cross-talk of an optical switch, have also been estimated using the plane wave expansion and the finite-difference time-domain method. The chalcogenide glass material (Ag20As32Se48) has a high refractive index of 3.1 which is highly suitable for switching operations. This dielectric material is immersed in an air background with a nonlinear Kerr coefficient of 9.1 x 10-17 m2/W. The resonance wavelength is at 1552 nm, with the operating power intensities at the cross-state and bar state around 60 W/μm2 and 690 W/μm2. The extinction ratio, insertion loss, and cross-talk value for the chalcogenide glass at the cross-state are 17.19 dB, 0.051 dB, and -17.14 dB, and the bar state, the values are 11.32 dB, 0.025 dB, and -11.35 dB respectively. The gallium arsenide (GaAs) dielectric material has a high refractive index of 3.4, a direct bandgap semiconductor material highly preferred nowadays for switching operations. This dielectric material is immersed in an air background with a nonlinear Kerr coefficient of 3.1 x 10-16 m2/W. The resonance wavelength is at 1558 nm, with the operating power intensities at the cross-state and bar state around 110 W/μm2 and 200 W/μm2. The extinction ratio, insertion loss, and cross-talk value for the chalcogenide glass at the cross-state are found to be 3.36.19 dB, 2.436 dB, and -5.8 dB, and for the bar state, the values are 15.60 dB, 0.985 dB, and -16.59 dB respectively. This paper proposes an all-optical 2 × 2 switch based on a nonlinear photonic crystal using a ring resonator. The two-dimensional photonic crystal comprises a square lattice of dielectric rods in an air background. The resonance wavelength is in the range of photonic bandgap. Later, another widely used material, GaAs, is also considered, and its performance is compared with the chalcogenide glass. Our presented structure can be potentially applicable in optical integration circuits and information processing.

Keywords: photonic crystal, FDTD, ring resonator, optical switch

Procedia PDF Downloads 57

Authors: Belbaly Nassim

Abstract:

Virtual teams (VT) initiatives, in which teams are geographically dispersed and communicate via modern computer-driven technologies, have attracted increasing attention from researchers and professionals. The growing need to examine how to balance and optimize VT is particularly important given the exposure experienced by companies when their employees encounter globalization and decentralization pressures to monitor VT performance. Hence, organization is regularly limited due to misalignment between the behavioral capabilities of the team’s dispersed competences and knowledge capabilities and how trust issues interplay and influence these VT dimensions and the effects of such exchanges. In fact, the future success of business depends on the extent to which VTs are managing efficiently their dispersed expertise, skills and knowledge to stimulate VT creativity. Transactive memory system (TMS) may enhance VT creativity using its three dimensons: knowledge specialization, credibility and knowledge coordination. TMS can be understood as a composition of both a structural component residing of individual knowledge and a set of communication processes among individuals. The individual knowledge is shared while being retrieved, applied and the learning is coordinated. TMS is driven by the central concept that the system is built on the distinction between internal and external memory encoding. A VT learns something new and catalogs it in memory for future retrieval and use. TMS uses the role of information technology to explain VT behaviors by offering VT members the possibility to encode, store, and retrieve information. TMS considers the members of a team as a processing system in which the location of expertise both enhances knowledge coordination and builds trust among members over time. We build on TMS dimensions to hypothesize the effects of specialization, coordination, and credibility on VT creativity. In fact, VTs consist of dispersed expertise, skills and knowledge that can positively enhance coordination and collaboration. Ultimately, this team composition may lead to recognition of both who has expertise and where that expertise is located; over time, the team composition may also build trust among VT members over time developing the ability to coordinate their knowledge which can stimulate creativity. We also assess the reciprocal relationship between TMS dimensions and VT creativity. We wish to use TMS to provide researchers with a theoretically driven model that is empirically validated through survey evidence. We propose that TMS provides a new way to enhance and balance VT creativity. This study also provides researchers insight into the use of TMS to influence positively VT creativity. In addition to our research contributions, we provide several managerial insights into how TMS components can be used to increase performance within dispersed VTs.

Keywords: virtual team creativity, transactive memory systems, specialization, credibility, coordination

Procedia PDF Downloads 142

Authors: Mustafa Alhamdi

Abstract:

Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

Procedia PDF Downloads 123

Authors: Nurlaila Effendy

Abstract:

Companies in Asia face a number of constraints in tight competitiveness in ASEAN Economic Community 2015 and globalization. An economic capitalism system as an integral part of globalization processing brings broad impacts. They need to improve business performance in globalization and ASEAN Economic Community. Organizational development has quite clearly demonstrated that aligning individual’s personal goals with the goals of the organization translates into measurable and sustained performance improvement. Human capital is a key to achieve company performance. Employee Engagement (EE) creates and expresses themselves physically, cognitively and emotionally to achieve company goals and individual goals. One will experience a total involvement when they undertake their jobs and feel a self integration to their job and organization. A leader plays key role in attaining the goals and objectives of a company/organization. Any Manager in a company needs to have leadership competence and global mindset. As one the of positive organizational behavior developments, psychological capital (PsyCap) is assumed to be one of the most important capitals in the global mindset, in addition to intellectual capital and social capital. Textile companies also need to face a number of constraints in tight competitiveness in regional and global. This research involved 42 managers in two textiles and a spinning companies in a group, in Central Java, Indonesia. It is a quantitative research with Partial Least Squares (PLS) studying job resource (Social Support & Organizational Climate) and Personal Resource (4 dimensions of Psychological Capital & Leadership Competence) as prediction of Employee Engagement, also Employee Engagement and leadership competence as prediction of leader’s performance. The performance of a leader is measured by means of achievement on objective strategies in terms of 4 perspectives (financial and non-financial perspectives) in a Balanced Score Card (BSC). It took one year during a business plan of year 2014, from January to December 2014. The result of this research is there is correlation between Job Resource (coefficient value of Social Support is 0.036 & coefficient value of organizational climate is 0.220) and Personal Resource (coefficient value of PsyCap is 0.513 & coefficient value of Leadership Competence is 0.249) with employee engagement. There is correlation between employee engagement (coefficient value is 0.279) and leadership competence (coefficient value is 0.581) with performance.

Keywords: organizational climate, social support, psychological capital leadership competence, employee engagement, performance, integrated textile companies

Procedia PDF Downloads 413

Authors: Amnah M. A. Alsuhaibani, Amal N. Al-Kuraieef

Abstract:

Introduction: In the recent decades, production of low-calorie jams is needed for diabetics that comprise low calorie fruits and low calorie sweeteners. Object: the research aimed to prepare low calorie formulated pumpkin jams (fructose, stevia and aspartame) incorporated with soy bean and evaluate the jams through chemical analysis and sensory evaluation after storage for six month. Moreover, the possible effect of consumption of low calorie jams on diabetic rats was investigated. Methods: Five formulas of pumpkin jam with different sucrose, fructose, stevia and aspartame sweeteners and soy bean were prepared and stored at 10 oC for six month compared to ordinary pumpkin jam. Chemical composition and sensory evaluation of formulated jams were evaluated at zero time, 3 month and 6 month of storage. The best three acceptable pumpkin jams were taken for biological study on diabetic rats. Rats divided into group (1) served as negative control and streptozotocin induce diabetes four rat groups that were positive diabetic control (group2), rats fed on standard diet with 10% sucrose soybean jam, fructose soybean jam and stevia soybean jam (group 3, 4&5), respectively. Results: The content of protein, fat, ash and fiber were increased but carbohydrate was decreased in low calorie formulated pumpkin jams compared to ordinary jam. Production of aspartame soybean pumpkin jam had lower score of all sensory attributes compared to other jam then followed by stevia soybean Pumpkin jam. Using non nutritive sweeteners (stevia & aspartame) with soybean in processing jam could lower the score of the sensory attributes after storage for 3 and 6 months. The highest score was recorded for sucrose and fructose soybean jams followed by stevia soybean jam while aspartame soybean jam recorded the lowest score significantly. The biological evaluation showed a significant improvement in body weight and FER of rats after six weeks of consumption of standard diet with jams (Group 3,4&5) compared to Group1. Rats consumed 10% low calorie jam with nutrient sweetener (fructose) and non nutrient sweetener (stevia) soybean jam (group 4& 5) showed significant decrease in glucose level, liver function enzymes activity, and liver cholesterol & total lipids in addition of significant increase of insulin and glycogen compared to the levels of group 2. Conclusion: low calorie pumpkin jams can be prepared by low calorie sweeteners and soybean and also storage for 3 months at 10oC without change sensory attributes. Consumption of stevia pumpkin jam fortified with soybean had positive health effects on streptozoticin induced diabetes in rats.

Keywords: pumpkin jam, HFCS, aspartame, stevia, storage

Procedia PDF Downloads 156

Authors: Manju Bala Jassi

Abstract:

The Covid 19 pandemic has badly mauled Dubai’s GDP heavily dependent on hospitality, tourism, entertainment, logistics, property and the retail sectors. In the context of the World Health protocols on social distancing for better maintenance of health and hygiene, the revival of the battered tourism and hospitality sectors has serious lessons for designers- interiors and public places. The tangible and intangible aesthetic elements and design –ambiance, materials, furnishings, colors, lighting and interior with architectural design issues of tourism and hospitality need a rethink to ensure a memorable tourist experience. Designers ought to experiment with sustainable places of tourism and design, develop, build and projects are aesthetic and leave as little negative impacts on the environment and public as possible. In short, they ought to conceive public spaces that makes use of little untouched materials and energy, and creates pollution and waste that are minimal. The spaces can employ healthier and more resource-efficient prototypes of construction, renovation, operation, maintenance, and demolition and thereby mitigate the environment impacts of the construction activities and it is sustainable These measures encompass the hospitality sector that includes hotels and restaurants which has taken the hardest fall from the pandemic. The paper sought to examine building energy efficiency and materials and design employed in public places, green buildings to achieve constructive sustainability and to establish the benefits of utilizing energy efficiency, green materials and sustainable design; to document diverse policy interventions, design and Spatial dimensions of tourism and hospitality sectors; to examine changes in the hospitality, aviation sector especially from a design perspective regarding infrastructure or operational constraints and additional risk-mitigation measures; to dilate on the nature of implications for interior designers and architects to design public places to facilitate sustainable tourism and hospitality while balancing convenient space and their operations' natural surroundings. The qualitative research approach was adopted for the study. The researcher collected and analyzed data in continuous iteration. Secondary data was collected from articles in journals, trade publications, government reports, newspaper/ magazine articles, policy documents etc. In depth interviews were conducted with diverse stakeholders. Preliminary data indicates that designers have started imagining public places of tourism and hospitality against the backdrop of the government push and WHO guidelines. For instance, with regard to health, safety, hygiene and sanitation, Emirates, the Dubai-based airline has augmented health measures at the Dubai International Airport and on board its aircraft. It has leveraged high tech/ Nano-tech, social distancing to encourage least human contact, flexible design layouts to limit the occupancy. The researcher organized the data into thematic categories and found that the Government of Dubai has initiated comprehensive measures in the hospitality, tourism and aviation sectors in compliance with the WHO guidelines.

Keywords: Covid 19, design, Dubai, hospitality, public spaces, tourism

Procedia PDF Downloads 137

Authors: M. Kharrat, G. Moreau, Z. Aboura

Abstract:

The latest advances in the weaving industry, combined with increasingly sophisticated means of materials processing, have made it possible to produce complex 3D composite structures. Mainly used in aeronautics, composite materials with 3D architecture offer better mechanical properties than 2D reinforced composites. Nevertheless, these materials require a good understanding of their behavior. Because of the complexity of such materials, the damage mechanisms are multiple, and the scenario of their appearance and evolution depends on the nature of the exerted solicitations. The AE technique is a well-established tool for discriminating between the damage mechanisms. Suitable sensors are used during the mechanical test to monitor the structural health of the material. Relevant AE-features are then extracted from the recorded signals, followed by a data analysis using pattern recognition techniques. In order to better understand the damage scenarios of interlock composite materials, a multi-instrumentation was set-up in this work for tracking damage initiation and development, especially in the vicinity of the first significant damage, called macro-damage. The deployed instrumentation includes video-microscopy, Digital Image Correlation, Acoustic Emission (AE) and micro-tomography. In this study, a multi-variable AE data analysis approach was developed for the discrimination between the different signal classes representing the different emission sources during testing. An unsupervised classification technique was adopted to perform AE data clustering without a priori knowledge. The multi-instrumentation and the clustered data served to label the different signal families and to build a learning database. This latter is useful to construct a supervised classifier that can be used for automatic recognition of the AE signals. Several materials with different ingredients were tested under various solicitations in order to feed and enrich the learning database. The methodology presented in this work was useful to refine the damage threshold for the new generation materials. The damage mechanisms around this threshold were highlighted. The obtained signal classes were assigned to the different mechanisms. The isolation of a 'noise' class makes it possible to discriminate between the signals emitted by damages without resorting to spatial filtering or increasing the AE detection threshold. The approach was validated on different material configurations. For the same material and the same type of solicitation, the identified classes are reproducible and little disturbed. The supervised classifier constructed based on the learning database was able to predict the labels of the classified signals.

Keywords: acoustic emission, classifier, damage mechanisms, first damage threshold, interlock composite materials, pattern recognition

Procedia PDF Downloads 135

Authors: N. D'Amico, E. Grossi, B. Colombo, F. Rigiroli, M. Buscema, D. Fazzini, G. Cornalba, S. Papa

Abstract:

Purpose: To characterize, through a radiomic approach, the nature of nodules considered non-specific by expert radiologists, recognized in magnetic resonance mammography (MRm) with T1-weighted (T1w) sequences with paramagnetic contrast. Material and Methods: 47 cases out of 1200 undergoing MRm, in which the MRm assessment gave uncertain classification (non-specific nodules), were admitted to the study. The clinical outcome of the non-specific nodules was later found through follow-up or further exams (biopsy), finding 35 benign and 12 malignant. All MR Images were acquired at 1.5T, a first basal T1w sequence and then four T1w acquisitions after the paramagnetic contrast injection. After a manual segmentation of the lesions, done by a radiologist, and the extraction of 150 radiomic features (30 features per 5 subsequent times) a machine learning (ML) approach was used. An evolutionary algorithm (TWIST system based on KNN algorithm) was used to subdivide the dataset into training and validation test and to select features yielding the maximal amount of information. After this pre-processing, different machine learning systems were applied to develop a predictive model based on a training-testing crossover procedure. 10 cases with a benign nodule (follow-up older than 5 years) and 18 with an evident malignant tumor (clear malignant histological exam) were added to the dataset in order to allow the ML system to better learn from data. Results: NaiveBayes algorithm working on 79 features selected by a TWIST system, resulted to be the best performing ML system with a sensitivity of 96% and a specificity of 78% and a global accuracy of 87% (average values of two training-testing procedures ab-ba). The results showed that in the subset of 47 non-specific nodules, the algorithm predicted the outcome of 45 nodules which an expert radiologist could not identify. Conclusion: In this pilot study we identified a radiomic approach allowing ML systems to perform well in the diagnosis of a non-specific nodule at MR mammography. This algorithm could be a great support for the early diagnosis of malignant breast tumor, in the event the radiologist is not able to identify the kind of lesion and reduces the necessity for long follow-up. Clinical Relevance: This machine learning algorithm could be essential to support the radiologist in early diagnosis of non-specific nodules, in order to avoid strenuous follow-up and painful biopsy for the patient.

Keywords: breast, machine learning, MRI, radiomics

Procedia PDF Downloads 250

Authors: Havva Tutar Kahraman, Erol Pehlivan

Abstract:

In recent years, environmental pollution by wastewater rises very critically. Effluents discharged from various industries cause this challenge. Different type of pollutants such as organic compounds, oxyanions, and heavy metal ions create this threat for human bodies and all other living things. However, heavy metals are considered one of the main pollutant groups of wastewater. Therefore, this case creates a great need to apply and enhance the water treatment technologies. Among adopted treatment technologies, adsorption process is one of the methods, which is gaining more and more attention because of its easy operations, the simplicity of design and versatility. Ion exchange process is one of the preferred methods for removal of heavy metal ions from aqueous solutions. It has found widespread application in water remediation technologies, during the past several decades. Therefore, the purpose of this study is to the removal of hexavalent chromium, Cr(VI), from aqueous solutions. Cr(VI) is considered as a well-known highly toxic metal which modifies the DNA transcription process and causes important chromosomic aberrations. The treatment and removal of this heavy metal have received great attention to maintaining its allowed legal standards. The purpose of the present paper is an attempt to investigate some aspects of the use of three anion exchange resins: Eichrom 1-X4, Lewatit Monoplus M800 and Lewatit A8071. Batch adsorption experiments were carried out to evaluate the adsorption capacity of these three commercial resins in the removal of Cr(VI) from aqueous solutions. The chromium solutions used in the experiments were synthetic solutions. The parameters that affect the adsorption, solution pH, adsorbent concentration, contact time, and initial Cr(VI) concentration, were performed at room temperature. High adsorption rates of metal ions for the three resins were reported at the onset, and then plateau values were gradually reached within 60 min. The optimum pH for Cr(VI) adsorption was found as 3.0 for these three resins. The adsorption decreases with the increase in pH for three anion exchangers. The suitability of Freundlich, Langmuir and Scatchard models were investigated for Cr(VI)-resin equilibrium. Results, obtained in this study, demonstrate excellent comparability between three anion exchange resins indicating that Eichrom 1-X4 is more effective and showing highest adsorption capacity for the removal of Cr(VI) ions. Investigated anion exchange resins in this study can be used for the efficient removal of chromium from water and wastewater.

Keywords: adsorption, anion exchange resin, chromium, kinetics

Procedia PDF Downloads 237

Authors: Julie Ramain, Christine Mohr, Ahmad Abu-Akel

Abstract:

Divergent thinking—a cognitive component of creativity—and particularly the ability to generate unique and novel ideas, has been linked to both autistic and schizotypal traits. However, to our knowledge, the concurrent effect of these trait dimensions on divergent thinking has not been investigated. Moreover, it has been suggested that creativity is associated with different types of attention and cognitive control, and consequently how information is processed in a given context. Intriguingly, consistent with the diametric model, autistic and schizotypal traits have been associated with contrasting attentional and cognitive control styles. Positive schizotypal traits have been associated with reactive cognitive control and attentional flexibility, while autistic traits have been associated with proactive cognitive control and the increased focus of attention. The current study investigated the relationship between divergent thinking, autistic and schizotypal traits and cognitive control in a non-clinical sample of 83 individuals (Males = 42%; Mean age = 22.37, SD = 2.93), sufficient to detect a medium effect size. Divergent thinking was evaluated in an adapted version of-of the Figural Torrance Test of Creative Thinking. Crucially, since we were interested in testing divergent thinking productivity across contexts, participants were asked to generate items from basic shapes in four different contexts. The variance of the proportion of unique to total responses across contexts represented a measure of context adaptability, with lower variance indicating increased context adaptability. Cognitive control was estimated with the Behavioral Proactive Index of the AX-CPT task, with higher scores representing the ability to actively maintain goal-relevant information in a sustained/anticipatory manner. Autistic and schizotypal traits were assessed with the Autism Quotient (AQ) and the Community Assessment of Psychic Experiences (CAPE-42). Generalized linear models revealed a 3-way interaction of autistic and positive schizotypal traits, and proactive cognitive control, associated with increased context adaptability. Specifically, the concurrent effect of autistic and positive schizotypal traits on increased context adaptability was moderated by the level of proactive control and was only significant when proactive cognitive control was high. Our study reveals that autistic and positive schizotypal traits interactively facilitate the capacity to generate unique ideas across various contexts. However, this effect depends on cognitive control mechanisms indicative of the ability to proactively maintain attention when needed. The current results point to a unique profile of divergent thinkers who have the ability to respectively tap both systematic and flexible processing modes within and across contexts. This is particularly intriguing as such combination of phenotypes has been proposed to explain the genius of Beethoven, Nash, and Newton.

Keywords: autism, schizotypy, creativity, cognitive control

Procedia PDF Downloads 113

Authors: Temitayo Abayomi Ewemoje, Oluwamayowa Oluwafemi Oluwaniyi

Abstract:

Agriculture and food processing, industry are among the largest industrial sectors that uses large amount of energy. Thus, a larger amount of gases from their fuel combustion technologies is being released into the environment. The choice of input energy supply not only directly having affects the environment, but also poses a threat to human health. The study was therefore designed to assess each unit production processes in order to identify hotspots using life cycle assessments (LCA) approach in South-western Nigeria. Data such as machine power rating, operation duration, inputs and outputs of shea butter materials for unit processes obtained at site were used to modelled Life Cycle Impact Analysis on GaBi6 (Holistic Balancing) software. Four scenarios were drawn for the impact assessments. Material sourcing from Kaiama, Scenarios 1, 3 and Minna Scenarios 2, 4 but different heat supply sources (Liquefied Petroleum Gas ‘LPG’ Scenarios 1, 2 and 10.8 kW Diesel Heater, scenarios 3, 4). Modelling of shea butter production on GaBi6 was for 1kg functional unit of shea butter produced and the Tool for the Reduction and Assessment of Chemical and other Environmental Impacts (TRACI) midpoint assessment was tool used to was analyse the life cycle inventories of the four scenarios. Eight categories in all four Scenarios were observed out of which three impact categories; Global Warming Potential (GWP) (0.613, 0.751, 0.661, 0.799) kg CO2¬-Equiv., Acidification Potential (AP) (0.112, 0.132, 0.129, 0.149) kg H+ moles-Equiv., and Smog (0.044, 0.059, 0.049, 0.063) kg O3-Equiv., categories had the greater impacts on the environment in Scenarios 1-4 respectively. Impacts from transportation activities was also seen to contribute more to these environmental impact categories due to large volume of petrol combusted leading to releases of gases such as CO2, CH4, N2O, SO2, and NOx into the environment during the transportation of raw shea kernel purchased. The ratio of transportation distance from Minna and Kaiama to production site was approximately 3.5. Shea butter unit processes with greater impacts in all categories was the packaging, milling and with the churning processes in ascending order of magnitude was identified as hotspots that may require attention. From the 1kg shea butter functional unit, it was inferred that locating production site at the shortest travelling distance to raw material sourcing and combustion of LPG for heating would reduce all the impact categories assessed on the environment.

Keywords: GaBi6, Life cycle assessment, shea butter production, TRACI

Procedia PDF Downloads 289

Authors: Glykeria A. Visvini, George N. Mathioudakis, Amaia Soto Beobide, Aris E. Giannakas, George A. Voyiatzis

Abstract:

Polymeric nanocomposites have generated considerable interest in both academic research and industry because their properties can be tailored by adjusting the type & concentration of nano-inclusions, resulting in complementary and adaptable characteristics. The exceptional and/or unique properties of the nanocomposites, including the high mechanical strength and stiffness, the ease of processing, and their lightweight nature, are attributed to the high surface area, the electrical and/or thermal conductivity of the nano-fillers, which make them appealing materials for a wide range of engineering applications. Polymeric «breathable» membranes enabling water vapor permeability (WVP) can be designed either by using micro/nano-fillers with the ability to interrupt the continuity of the polymer phase generating micro/nano-porous structures or/and by creating micro/nano-pores into the composite material by uniaxial/biaxial stretching. Among the nanofillers, carbon nanotubes (CNTs) exhibit particular high WVP and for this reason, they have already been proposed for gas separation membranes. In a similar context, they could prove to be promising alternative/complementary filler nano-materials, for the development of "breathable" products. Polypropylene (PP) is a commonly utilized thermoplastic polymer matrix in the development of composite films, due to its easy processability and low price, combined with its good chemical & physical properties. PP is known to present several crystalline phases (α, β and γ), depending on the applied treatment process, which have a significant impact on its final properties, particularly in terms of WVP. Specifically, the development of the β-phase in PP in combination with stretching is anticipated to modify the crystalline behavior and extend the microporosity of the polymer matrix exhibiting enhanced WVP. The primary objective of this study is to develop breathable nano-carbon based (functionalized MWCNTs) PP composite membranes, potentially also avoiding the stretching process. This proposed alternative is expected to have a better performance/cost ratio over current stretched PP/CaCO3 composite benchmark membranes. The focus is to investigate the impact of both β-nucleator(s) and nano-carbon fillers on water vapor transmission rate properties of relevant PP nanocomposites.

Keywords: carbon nanotubes, nanocomposites, nucleating agents, polypropylene, water vapor permeability

Procedia PDF Downloads 48

Authors: Eugene Y. J. Aw, J. W. Koh, S. H. Chew, K. E. Chua, P. L. Goh, Grace H. B. Foo, M. L. Leong

Abstract:

This paper presents the evaluation of various soil testing methods such as the four-probe soil electrical resistivity method and cone penetration test (CPT) that can complement a newly developed novel rapid soil classification scheme using computer vision, to improve the accuracy and productivity of on-site classification of excavated soil. In Singapore, excavated soils from the local construction industry are transported to Staging Grounds (SGs) to be reused as fill material for land reclamation. Excavated soils are mainly categorized into two groups (“Good Earth” and “Soft Clay”) based on particle size distribution (PSD) and water content (w) from soil investigation reports and on-site visual survey, such that proper treatment and usage can be exercised. However, this process is time-consuming and labor-intensive. Thus, a rapid classification method is needed at the SGs. Four-probe soil electrical resistivity and CPT were evaluated for their feasibility as suitable additions to the computer vision system to further develop this innovative non-destructive and instantaneous classification method. The computer vision technique comprises soil image acquisition using an industrial-grade camera; image processing and analysis via calculation of Grey Level Co-occurrence Matrix (GLCM) textural parameters; and decision-making using an Artificial Neural Network (ANN). It was found from the previous study that the ANN model coupled with ρ can classify soils into “Good Earth” and “Soft Clay” in less than a minute, with an accuracy of 85% based on selected representative soil images. To further improve the technique, the following three items were targeted to be added onto the computer vision scheme: the apparent electrical resistivity of soil (ρ) measured using a set of four probes arranged in Wenner’s array, the soil strength measured using a modified mini cone penetrometer, and w measured using a set of time-domain reflectometry (TDR) probes. Laboratory proof-of-concept was conducted through a series of seven tests with three types of soils – “Good Earth”, “Soft Clay,” and a mix of the two. Validation was performed against the PSD and w of each soil type obtained from conventional laboratory tests. The results show that ρ, w and CPT measurements can be collectively analyzed to classify soils into “Good Earth” or “Soft Clay” and are feasible as complementing methods to the computer vision system.

Keywords: computer vision technique, cone penetration test, electrical resistivity, rapid and non-destructive, soil classification

Procedia PDF Downloads 214

Authors: Tim Bolle, Franziska Kreimendahl, Thomas Gries, Stefan Jockenhoevel

Abstract:

The therapeutic treatment of extensive, deep wounds is limited. Autologous split-skin grafts are used as a so-called ‘gold standard’. Most common deficits are the defects at the donor site, the risk of scarring as well as the limited availability and quality of the autologous grafts. The aim of this project is a tissue engineered dermal-epidermal skin replacement to overcome the limitations of the gold standard. A key requirement for the development of such a three-dimensional implant is the formation of a functional capillary-like network inside the implant to ensure a sufficient nutrient and gas supply. Tailored three-dimensional warp knitted spacer fabrics are used to reinforce the mechanically week fibrin gel-based scaffold and further to create a directed in vitro pre-vascularization along the parallel-oriented pile yarns within a co-culture. In this study various three-dimensional warp knitted spacer fabrics were developed in a factorial design to analyze the influence of the machine parameters such as the stitch density and the pattern of the fabric on the scaffold performance and further to determine suitable parameters for a successful fibrin gel-incorporation and a physiological performance of the scaffold. The fabrics were manufactured on a Karl Mayer double-bar raschel machine DR 16 EEC/EAC. A fine machine gauge of E30 was used to ensure a high pile yarn density for sufficient nutrient, gas and waste exchange. In order to ensure a high mechanical stability of the graft, the fabrics were made of biocompatible PVDF yarns. Key parameters such as the pore size, porosity and stress/strain behavior were investigated under standardized, controlled climate conditions. The influence of the input parameters on the mechanical and morphological properties as well as the ability of fibrin gel incorporation into the spacer fabric was analyzed. Subsequently, the pile yarns of the spacer fabrics were colonized with Human Umbilical Vein Endothelial Cells (HUVEC) to analyze the ability of the fabric to further function as a guiding structure for a directed vascularization. The cells were stained with DAPI and investigated using fluorescence microscopy. The analysis revealed that the stitch density and the binding pattern have a strong influence on both the mechanical and morphological properties of the fabric. As expected, the incorporation of the fibrin gel was significantly improved with higher pore sizes and porosities, whereas the mechanical strength decreases. Furthermore, the colonization trials revealed a high cell distribution and density on the pile yarns of the spacer fabrics. For a tailored reinforcing structure, the minimum porosity and pore size needs to be evaluated which still ensures a complete incorporation of the reinforcing structure into the fibrin gel matrix. That will enable a mechanically stable dermal graft with a dense vascular network for a sufficient nutrient and oxygen supply of the cells. The results are promising for subsequent research in the field of reinforcing mechanically weak biological scaffolds and develop functional three-dimensional scaffolds with an oriented pre-vascularization.

Keywords: fibrin-gel, skin replacement, spacer fabric, pre-vascularization

Procedia PDF Downloads 231

Authors: Michelle E. Taylor, Clare E. Morrall

Abstract:

Microplastics are small particles produced for industrial purposes or formed by breakdown of anthropogenic debris. Caribbean nations import large quantities of plastic products. The Caribbean region is vulnerable to natural disasters and Climate Change is predicted to bring multiple additional challenges to island nations. Microplastics have been found in an array of marine environments and in a diversity of marine species. Occurrence of microplastic in the intestinal tracts of marine fish is a concern to human and ecosystem health as pollutants and pathogens can associate with plastics. Studies have shown that the incidence of microplastics in marine fish varies with species and location. Prevalence of microplastics (≤ 5 mm) in fish species from Grenadian waters (representing pelagic, semi-pelagic and demersal lifestyles) harvested for human consumption have been investigated via gut analysis. Harvested tissue was digested in 10% KOH and particles retained on a 0.177 mm sieve were examined. Microplastics identified have been classified according to type, colour and size. Over 97% of fish examined thus far (n=34) contained microplastics. Current and future work includes examining the invasive Lionfish (Pterois spp.) for microplastics, investigating marine invertebrate species as well as examining environmental sources of microplastics (i.e. rivers, coastal waters and sand). Owing to concerns of pollutant accumulation on microplastics and potential migration into organismal tissues, we plan to analyse fish tissue for mercury and other persistent pollutants. Despite having ~110,000 inhabitants, the island nation of Grenada imported approximately 33 million plastic bottles in 2013, of which it is estimated less than 5% were recycled. Over 30% of the imported bottles were ‘unmanaged’, and as such are potential litter/marine debris. A revised Litter Abatement Act passed into law in Grenada in 2015, but little enforcement of the law is evident to date. A local Non-governmental organization (NGO) ‘The Grenada Green Group’ (G3) is focused on reducing litter in Grenada through lobbying government to implement the revised act and running sessions in schools, community groups and on local media and social media to raise awareness of the problems associated with plastics. A local private company has indicated willingness to support an Anti-Litter Campaign in 2018 and local awareness of the need for a reduction of single use plastic use and litter seems to be high. The Government of Grenada have called for a Sustainable Waste Management Strategy and a ban on both Styrofoam and plastic grocery bags are among recommendations recently submitted. A Styrofoam ban will be in place at the St. George’s University campus from January 1st, 2018 and many local businesses have already voluntarily moved away from Styrofoam. Our findings underscore the importance of continuing investigations into microplastics in marine life; this will contribute to understanding the associated health risks. Furthermore, our findings support action to mitigate the volume of plastics entering the world’s oceans. We hope that Grenada’s future will involve a lot less plastic. This research was supported by the Caribbean Node of the Global Partnership on Marine Litter.

Keywords: Caribbean, microplastics, pollution, small island developing nation

Procedia PDF Downloads 184

Authors: Ju-Hong Lee, Ching-Wei Liao

Abstract:

An adaptive array beamformer is designed for automatically preserving the desired signals while cancelling interference and noise. Providing robustness against model mismatches and tracking possible environment changes calls for robust adaptive beamforming techniques. The design criterion yields the well-known generalized sidelobe canceller (GSC) beamformer. In practice, the knowledge of the desired steering vector can be imprecise, which often occurs due to estimation errors in the DOA of the desired signal or imperfect array calibration. In these situations, the SOI is considered as interference, and the performance of the GSC beamformer is known to degrade. This undesired behavior results in a reduction of the array output signal-to-interference plus-noise-ratio (SINR). Therefore, it is worth developing robust techniques to deal with the problem due to local scattering environments. As to the implementation of adaptive beamforming, the required computational complexity is enormous when the array beamformer is equipped with massive antenna array sensors. To alleviate this difficulty, a generalized sidelobe canceller (GSC) with partially adaptivity for less adaptive degrees of freedom and faster adaptive response has been proposed in the literature. Unfortunately, it has been shown that the conventional GSC-based adaptive beamformers are usually very sensitive to the mismatch problems due to local scattering situations. In this paper, we present an effective GSC-based beamformer against the mismatch problems mentioned above. The proposed GSC-based array beamformer adaptively estimates the actual direction of the desired signal by using the presumed steering vector and the received array data snapshots. We utilize the predefined steering vector and a presumed angle tolerance range to carry out the required estimation for obtaining an appropriate steering vector. A matrix associated with the direction vector of signal sources is first created. Then projection matrices related to the matrix are generated and are utilized to iteratively estimate the actual direction vector of the desired signal. As a result, the quiescent weight vector and the required signal blocking matrix required for performing adaptive beamforming can be easily found. By utilizing the proposed GSC-based beamformer, we find that the performance degradation due to the considered local scattering environments can be effectively mitigated. To further enhance the beamforming performance, a signal subspace projection matrix is also introduced into the proposed GSC-based beamformer. Several computer simulation examples show that the proposed GSC-based beamformer outperforms the existing robust techniques.

Keywords: adaptive antenna beamforming, local scattering, signal blocking, steering mismatch

Procedia PDF Downloads 86

Authors: X. Wang

Abstract:

Timely and accurate information on urban building damage caused by earthquake is important basis for disaster assessment and emergency relief. Very high resolution (VHR) remotely sensed imagery containing abundant fine-scale information offers a large quantity of data for detecting and assessing urban building damage in the aftermath of earthquake disasters. However, the accuracy obtained using spectral features alone is comparatively low, since building damage, intact buildings and pavements are spectrally similar. Therefore, it is of great significance to detect urban building damage effectively using multi-source data. Considering that in general height or geometric structure of buildings change dramatically in the devastated areas, a novel multi-stage urban building damage detection method, using bi-temporal spectral, height and corner information, was proposed in this study. The pre-event height information was generated using stereo VHR images acquired from two different satellites, while the post-event height information was produced from airborne LiDAR data. The corner information was extracted from pre- and post-event panchromatic images. The proposed method can be summarized as follows. To reduce the classification errors caused by spectral similarity and errors in extracting height information, ground surface, shadows, and vegetation were first extracted using the post-event VHR image and height data and were masked out. Two different types of building damage were then extracted from the remaining areas: the height difference between pre- and post-event was used for detecting building damage showing significant height change; the difference in the density of corners between pre- and post-event was used for extracting building damage showing drastic change in geometric structure. The initial building damage result was generated by combining above two building damage results. Finally, a post-processing procedure was adopted to refine the obtained initial result. The proposed method was quantitatively evaluated and compared to two existing methods in Port au Prince, Haiti, which was heavily hit by an earthquake in January 2010, using pre-event GeoEye-1 image, pre-event WorldView-2 image, post-event QuickBird image and post-event LiDAR data. The results showed that the method proposed in this study significantly outperformed the two comparative methods in terms of urban building damage extraction accuracy. The proposed method provides a fast and reliable method to detect urban building collapse, which is also applicable to relevant applications.

Keywords: building damage, corner, earthquake, height, very high resolution (VHR)

Procedia PDF Downloads 189