Search results for: image quality metrics

Authors: Stephen Olusanmi Akintayo

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Access to safe drinking water remains a major challenge in Nigeria, and where available, the quality of the water is often in doubt. An alternative to the inadequate clean drinking water is being found in treated drinking water packaged in electrically heated sealed nylon and commonly referred to as “sachet water”. “Sachet water” is a common thing in Nigeria as the selling price is within the reach of members of the low socio- economic class and the setting up of a production unit does not require huge capital input. The bacteriological quality of selected “sachet water” stored at room temperature over a period of 56 days was determined to evaluate the safety of the sachet drinking water. Test for the detection of coliform bacteria was performed, and the result showed no coliform bacteria that indicates the absence of fecal contamination throughout 56 days. Heterotrophic plate count (HPC) was done at an interval 14 days, and the samples showed HPC between 0 cfu/mL and 64 cfu/mL. The highest count was observed on day 1. The count decreased between day 1 and 28, while no growths were observed between day 42 and 56. The decrease in HPC suggested the presence of residual disinfectant in the water. The organisms isolated were identified as Staphylococcus epidermis and S. aureus. The presence of these microorganisms in sachet water is indicative for contamination during processing and handling.

Keywords: coliform, heterotrophic plate count, sachet water, Staphyloccocus aureus, Staphyloccocus epidermidis

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Authors: Carol Anne Hargreaves

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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: Laura E. Hall, Joel Monárrez-Espino, Luz María Tejada Tayabas

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College students are at risk of weight gain and poor dietary habits, and health behaviours established during this period have been shown to track into midlife. They may therefore be an important target group for health promotion strategies, yet there is a lack of literature regarding dietary intakes and associated factors in this group, particularly in middle-income countries such as Mexico. The aim of this exploratory research was to describe and compare reported dietary intakes among nursing and nutrition college students at two public universities in Mexico, and to explore the relationship between demographic, behavioural and other health-related factors and the risk of low diet quality. Mexican college students (n=444) majoring in nutrition or nursing at two urban universities completed questionnaires regarding dietary and health-related behaviours and risks. Dietary intake was assessed via 24-hour recall. Weight, height and abdominal circumference were measured. Descriptive statistics were reported and nutrient intakes were compared between colleges and study tracks using Student’s t tests, odds ratios and Pearson chi square tests. Two dietary quality scores were constructed to explore the relationship between demographic, behavioural and other health-related factors and the diet quality scores using binary logistic regression. Analysis was performed using SPSS statistics, with differences considered statistically significant at p<0.05. The response rate to the survey was 91%. When macronutrients were considered as a percentage of total energy, the majority of students had protein intakes within recommended ranges, however one quarter of students had carbohydrate and fat intakes exceeding recommended levels. Three quarters had fibre intakes that were below recommendations. More than half of the students reported intakes of magnesium, zinc, vitamin A, folate and vitamin E that were below estimated average requirements. Students studying nutrition reported macronutrient and micronutrient intakes that were more compliant with recommendations compared to nursing students, and students studying in central-north Mexico were more compliant than those studying in southeast Mexico. Breakfast skipping (Adjusted Odds Ratio (OR) = 5.3; 95% Confidence Interval (CI) = 1.2-22.7), risk of anxiety (OR = 2.3; CI = 1.3-4.4), and university location (OR = 1.6; CI = 1.03-2.6) were associated with a greater risk of having a low macronutrient score. Caloric intakes <1800kcal (OR = 5.8; CI = 3.5-9.7), breakfast skipping (OR = 3.7; CI = 1.4-10.3), vigorous exercise ≤1h/week (OR = 2.6; CI = 1.3-5.2), soda consumption >250mls/day (OR = 2.0; CI = 1.2-3.3), unhealthy diet perception (OR = 1.9; CI = 1.2-3.0), and university location (OR = 1.8; CI = 1.1-2.8) were significantly associated with greater odds of having a low micronutrient score. College students studying nursing and nutrition did not report ideal diets, and these students should not be overlooked in public health interventions. Differences in dietary intakes between universities and study tracks were evident, with more favourable profiles evident in nutrition compared to nursing, and North-central compared to Southeast students. Further, demographic, behavioural and other health-related factors were associated with diet quality scores, warranting further research.

Keywords: college student, diet quality, nutrient intake, young adult

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Authors: Vahid Bayrami Rad

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Ever since humans developed a collective way of life to the development of urbanization, the concern of security has always been considered one of the most important challenges of life. To protect property, locks have always been a practical tool. With the advancement of technology, the form of locks has changed from mechanical to electric. One of the most widely used fields of using artificial intelligence is its application in the technology of surveillance security systems. Currently, the technologies used in smart anti-theft door handles are one of the most potential fields for using artificial intelligence. Artificial intelligence has the possibility to learn, calculate, interpret and process by analyzing data with the help of algorithms and mathematical models and make smart decisions. We will use Arduino board to process data.

Keywords: arduino board, artificial intelligence, image processing, solenoid lock

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Authors: Xiaoyan Dai, Hsieh Yisan

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Barcode processing of captured images is a huge challenge, as different shooting conditions can result in different barcode appearances. This paper proposes a deep learning-based barcode detection using synthetic-to-real data augmentation. We first augment barcodes themselves; we then augment images containing the barcodes to generate a large variety of data that is close to the actual shooting environments. Comparisons with previous works and evaluations with our original data show that this approach achieves state-of-the-art performance in various real images. In addition, the system uses hybrid resolution for barcode “scan” and is applicable to real-time applications.

Keywords: barcode detection, data augmentation, deep learning, image-based processing

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Authors: Spanova Yerkezhan, Amantay Ayan, Alimzhanova Laura

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This article discusses the concept of rebranding and its relationship to cybersecurity. Rebranding is the process of changing the appearance and image of a company or organization in order to appeal to new customers or change the perception of a company. It can be a powerful tool for businesses looking to renew their reputation or expand into new markets. In today's digital age, companies increasingly rely on technology and the internet to conduct business; rebranding can also present significant cybersecurity risks. This is because a rebranding effort can create new vulnerabilities for companies, particularly in terms of their online presence. This article explores the potential hazards associated with rebranding and provides recommendations for mitigating those risks. It also highlights the importance of considering cybersecurity in the rebranding process and how it can be integrated into the overall strategy for a successful and secure rebranding.

Keywords: rebranding, cybersecurity, cyberattack, logo, vulnerability

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Authors: Gaddafi Sani Shehu, Tankut Yalcınoz, Abdullahi Bala Kunya

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Multilevel inverters such as flying capacitor, diode-clamped, and cascaded H-bridge inverters are very popular particularly in medium and high power applications. This paper focuses on a cascaded H-bridge module using a single direct current (DC) source in order to generate an 11-level output voltage. The noble approach reduces the number of switches and gate drivers, in comparison with a conventional method. The anticipated topology produces more accurate result with an isolation transformer at high switching frequency. Different modulation techniques can be used for the multilevel inverter, but this work features modulation techniques known as selective harmonic elimination (SHE).This modulation approach reduces the number of carriers with reduction in Switching Losses, Total Harmonic Distortion (THD), and thereby increasing Power Quality (PQ). Based on the simulation result obtained, it appears SHE has the ability to eliminate selected harmonics by chopping off the fundamental output component. The performance evaluation of the proposed cascaded multilevel inverter is performed using PSIM simulation package and THD of 0.94% is obtained.

Keywords: cascaded H-bridge multilevel inverter, power quality, selective harmonic elimination

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Authors: M. Jebali, M. Jemni

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This work is the part of vision based hand gesture recognition system for Natural Human Computer Interface. Hand tracking and segmentation are the primary steps for any hand gesture recognition system. The aim of this paper is to develop robust and efficient hand segmentation algorithm such as an input to another system which attempt to bring the HCI performance nearby the human-human interaction, by modeling an intelligent sign language recognition system based on prediction in the context of dialogue between the system (avatar) and the interlocutor. For the purpose of hand segmentation, an overcoming occlusion approach has been proposed for superior results for detection of hand from an image.

Keywords: HCI, sign language recognition, object tracking, hand segmentation

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Authors: Nayden Chivarov, Denis Chikurtev, Kaloyan Yovchev, Nedko Shivarov

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This paper represents methods for improving the efficiency and precision of service mobile robot. This robot is used for increasing the quality of life of elderly and disabled people. The key concept of the proposed Intelligent Service Mobile Robot is its easier adaptability to achieve services for a wide range of Elderly or Disabled Person’s needs, by performing different tasks for supporting Elderly or Disabled Persons care. We developed robot autonomous navigation and computer vision systems in order to recognize different objects and bring them to the people. Web based user interface is developed to provide easy access and tele-control of the robot by any device through the internet. In this study algorithms for object recognition and localization are proposed for providing successful object recognition and accuracy in the positioning. Different methods for sending movement commands to the mobile robot system are proposed and evaluated. After executing some experiments to show the results of the research, we can summarize that these systems and algorithms provide good control of the service mobile robot and it will be more useful to help the elderly and disabled persons.

Keywords: service robot, mobile robot, autonomous navigation, computer vision, web user interface, ROS

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Authors: Muhammad Raqib Rasul, Tavga Sulaiman Rashid

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Fertilization increases efficiency and obtains better quality of product recovery in agricultural activities. However, fertilizer consumption increased exponentially throughout the world, causing severe environmental problems. Biofertilizers can be a practical approach to minimize chemical fertilizer sources and ultimately develop soil fertility. This study was carried out to isolate, identify and characterize bacteria from medicinal plant (Rumex tuberosus L. and Verbascum sp.) rhizosphere for in vivo screening. 25 bacterial isolates were isolated and several biochemical tests were performed. Two isolates that were positive for most biochemical tests were chosen for the field experiment. The isolates were identified as Go1 Alcaligenes faecalis (Accession No. OP001725) and T11 (Bacillus sp.) based on the 16S rRNA sequence analysis that was compared with related bacteria in GenBank database using MEGA 6.1. For the field trial isolate GO1 and T11 (separately and mixed), NPK as a positive control was used. Both isolates increased plant height, chlorophyll content, number of tubers, and tuber’s weight. The results demonstrated that these two isolates of bacteria can potentially replace with chemical fertilizers for potato production.

Keywords: biofertilizer, Bacillus subtilis, Alcaligenes faecalis, potato tubers, in vivo screening

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Authors: Halison da Silva Pereira, Ciro Sobrinho Campolina Martins, Vitor Mainenti Leal Lopes

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Long range performance is a goal for aircraft configuration optimization. Blended Wing Body (BWB) is presented in many works of literature as the most aerodynamically efficient design for a fixed-wing aircraft. Because of its high weight to thrust ratio, BWB is the ideal configuration for many Unmanned Aerial Vehicle (UAV) missions on geomatics applications. In this work, a BWB aerodynamic design for typical light geomatics payload is presented. Aerodynamic non-dimensional coefficients are predicted using low Reynolds number computational techniques (3D Panel Method) and wing parameters like aspect ratio, taper ratio, wing twist and sweep are optimized for high cruise performance and flight quality. The methodology of this work is a summary of tailless aircraft wing design and its application, with appropriate computational schemes, to light UAV subjected to low Reynolds number flows leads to conclusions like the higher performance and flight quality of thicker airfoils in the airframe body and the benefits of using aerodynamic twist rather than just geometric.

Keywords: blended wing body, low Reynolds number, panel method, UAV

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Authors: Margaret K. Spoo-Chupka

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The Metropolitan Water District of Southern California (MWDSC) manages surface water reservoirs that are a source of drinking water for more than 19 million people in Southern California. These reservoirs experience periodic planktonic cyanobacteria blooms that can impact water quality. MWDSC imports water from two sources – the Colorado River (CR) and the State Water Project (SWP). The SWP brings supplies from the Sacramento-San Joaquin Delta that are characterized as having higher nutrients than CR water. Above average precipitation in 2017 after five years of drought allowed the majority of the reservoirs to fill. Phytoplankton was analyzed during the drought and after the drought at three reservoirs: Diamond Valley Lake (DVL), which receives SWP water exclusively, Lake Skinner, which can receive a blend of SWP and CR water, and Lake Mathews, which generally receives only CR water. DVL experienced a significant increase in water elevation in 2017 due to large SWP inflows, and there were no significant changes to total phytoplankton biomass, Shannon-Wiener diversity of the phytoplankton, or cyanobacteria biomass in 2017 compared to previous drought years despite the higher nutrient loads. The biomass of cyanobacteria that could potentially impact DVL water quality (Microcystis spp., Aphanizomenon flos-aquae, Dolichospermum spp., and Limnoraphis birgei) did not differ significantly between the heavy precipitation year and drought years. Compared to the other reservoirs, DVL generally has the highest concentration of cyanobacteria due to the water supply having greater nutrients. Lake Mathews’ water levels were similar in drought and wet years due to a reliable supply of CR water and there were no significant changes in the total phytoplankton biomass, phytoplankton diversity, or cyanobacteria biomass in 2017 compared to previous drought years. The biomass of cyanobacteria that could potentially impact water quality at Lake Mathews (L. birgei and Microcystis spp.) did not differ significantly between 2017 and previous drought years. Lake Mathews generally had the lowest cyanobacteria biomass due to the water supply having lower nutrients. The CR supplied most of the water to Lake Skinner during drought years, while the SWP was the primary source during 2017. This change in water source resulted in a significant increase in phytoplankton biomass in 2017, no significant change in diversity, and a significant increase in cyanobacteria biomass. Cyanobacteria that could potentially impact water quality at Skinner included: Microcystis spp., Dolichospermum spp., and A.flos-aquae. There was no significant difference in Microcystis spp. biomass in 2017 compared to previous drought years, but biomass of Dolichospermum spp. and A.flos-aquae were significantly greater in 2017 compared to previous drought years. Dolichospermum sp. and A. flos-aquae are two cyanobacteria that are more sensitive to nutrients than Microcystis spp., which are more sensitive to temperature. Patterns in problem cyanobacteria abundance among Southern California reservoirs as a result of above-average precipitation after more than five years of drought were most closely related to nutrient loading.

Keywords: drought, reservoirs, cyanobacteria, and phytoplankton ecology

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Authors: Jau-Shya Lee, Rossita Shapawi, Vin Cent Pua

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Tilapia is a popular cultured fresh-water fish in Malaysia. The highly perishable nature of the fish and increasing demand for high-quality ready-to-cook fish has intensified the search for better fish preservation method. Chitosan edible coating has been evident to extend the shelf life of fish fillet. This work was attempted to explore the potential of ascorbic acid in enhancing the shelf life extension ability of chitosan coated Tilapia fillet under refrigeration condition (4 ± 1oC). A 3 2 Factorial Design which comprising of three concentrations of chitosan (1, 1.5 and 2%) and two concentrations of ascorbic acids (2.5 and 5%) was used. The fish fillets were analyzed for total viable count, thiobarbituric acid (TBA) value, pH, aw and colour changes at 3-day interval over 15-day storage. The shelf life of chitosan coated (1.5% and 2%) fillet was increased to 15 days as compared to uncoated fish fillet which can only last for nine days. The inhibition of microbial growth of fish fillet was enhanced with the addition of 5% of ascorbic acids in 2% of chitosan. The TBA value, pH and aw for chitosan coated samples were found lower than that of uncoated sample (p<0.05). The colour stability of the fish fillet was also improved by the composite coating. Overall, 2% of chitosan and 5% of ascorbic acid formed the most effective coating to enhance the quality and to lengthen the shelf life of refrigerated Tilapia fillet.

Keywords: ascorbic acid, chitosan, edible coating, fish fillet

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Authors: Szymon Rutkowski, Tomasz Korbak

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We present a reinforcement-learning-based method of training neural machine translation models without parallel corpora. The standard encoder-decoder approach to machine translation suffers from two problems we aim to address. First, it needs parallel corpora, which are scarce, especially for low-resource languages. Second, it lacks psychological plausibility of learning procedure: learning a foreign language is about learning to communicate useful information, not merely learning to transduce from one language’s 'encoding' to another. We instead pose the problem of learning to translate as learning a policy in a communication game between two agents: the translator and the classifier. The classifier is trained beforehand on a natural language inference task (determining the entailment relation between a premise and a hypothesis) in the target language. The translator produces a sequence of actions that correspond to generating translations of both the hypothesis and premise, which are then passed to the classifier. The translator is rewarded for classifier’s performance on determining entailment between sentences translated by the translator to disciple’s native language. Translator’s performance thus reflects its ability to communicate useful information to the classifier. In effect, we train a machine translation model without the need for parallel corpora altogether. While similar reinforcement learning formulations for zero-shot translation were proposed before, there is a number of improvements we introduce. While prior research aimed at grounding the translation task in the physical world by evaluating agents on an image captioning task, we found that using a linguistic task is more sample-efficient. Natural language inference (also known as recognizing textual entailment) captures semantic properties of sentence pairs that are poorly correlated with semantic similarity, thus enforcing basic understanding of the role played by compositionality. It has been shown that models trained recognizing textual entailment produce high-quality general-purpose sentence embeddings transferrable to other tasks. We use stanford natural language inference (SNLI) dataset as well as its analogous datasets for French (XNLI) and Polish (CDSCorpus). Textual entailment corpora can be obtained relatively easily for any language, which makes our approach more extensible to low-resource languages than traditional approaches based on parallel corpora. We evaluated a number of reinforcement learning algorithms (including policy gradients and actor-critic) to solve the problem of translator’s policy optimization and found that our attempts yield some promising improvements over previous approaches to reinforcement-learning based zero-shot machine translation.

Keywords: agent-based language learning, low-resource translation, natural language inference, neural machine translation, reinforcement learning

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Authors: Sevket Ceyhun Cetin, Mehmet Oren

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According to existing educational research studies, students learn better with high teacher quality. Therefore, professional development has become a crucial way of increasing the quality of novices and veteran in-service teachers by providing support regarding content and pedagogy. To answer what makes PD effective, researchers have studied different PD models and revealed some critical elements that need to be considered, such as duration of a PD and the manner of delivery (e.g., lecture vs. engaging). Also, it has been pointed out that if PDs are prepared as one-size-fits-all, they most likely be ineffective in addressing teachers’ needs toward improving instructional quality. Instead, teachers’ voices need to be heard, and the foci of PDs should be determined based on their specific needs. Thus, this study was conducted to identify professional development needs of middle school mathematics teachers based on their self-evaluation of their performances in light of teaching standards. This study also aimed to explore whether the PD needs with respect to years of teaching experience (novice vs. veteran). These teachers had participated in a federally-funded research grant, which aimed to improve the competencies of 6-9 grade-level mathematics teachers in pedagogy and content areas. In the research project, the participants had consistently videoed their lessons throughout a school year and reflected on their performances, using Teacher Advanced Program (TAPTM) rubric, which was based on the best practices of teaching. Particularly, they scored their performances in the following areas and provided evidence as the justifications of their scores: Standards and Objectives, Presenting Instructional Content, Lesson Structure and Pacing, Activities and Materials, Academic Feedback, Grouping Students, and Questioning. The rating scale of the rubric is 1 through 5 (i.e., 1=Unsatisfactory [performance], 3=Proficient, and 5=Exemplary). For each area mentioned above, the numerical scores of 77 written reports (for 77 videoed lessons) of 24 teachers (nnovices=12 and nveteran=12) were averaged. Overall, the average score of each area was below 3 (ranging between 2.43 and 2.86); in other words, teachers judged their performances incompetent across the seven areas. In the second step of the data analysis, the lowest three areas in which novice and veteran teachers performed poorly were selected for further qualitative analysis. According to the preliminary results, the lowest three areas for the novice teachers were: Questioning, Grouping Students, and Academic Feedback. Grouping Students was also one of the lowest areas of the veteran teachers, but the other two areas for this group were: Lesson Structure & Pacing, and Standards & Objectives. Identifying in-service teachers’ needs based on their reflective practitioner experiences provides educators very crucial information that can be used to create more effective PD that improves teacher quality.

Keywords: mathematics teacher, professional development, self-reflection, video data

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Authors: Mehdi Shekarzadeh, Pejman Taghipour Birgani

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In this paper, the effect of mass and height of tip on the flexural vibration modes of an atomic force microscope (AFM) rectangular cantilever is analyzed. A closed-form expression for the sensitivity of vibration modes is derived using the relationship between the resonant frequency and contact stiffness of cantilever and sample. Each mode has a different sensitivity to variations in surface stiffness. This sensitivity directly controls the image resolution. It is obtained an AFM cantilever is more sensitive when the mass of tip is lower and the first mode is the most sensitive mode. Also, the effect of changes of tip height on the flexural sensitivity is negligible.

Keywords: atomic force microscope, AFM, vibration analysis, flexural vibration, cantilever

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Authors: Catariny C. Aleman, Flavio B. Campos, Matheus A. Caliman, Everardo C. Mantovani

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The seedling production stage is a critical point in the vegetable production system. Obtaining high-quality seedlings is a prerequisite for subsequent cropping to occur well and productivity optimization is required. The water management is an important step in agriculture production. The adequate water requirement in horticulture seedlings can provide higher quality and increase field production. The practice of irrigation is indispensable and requires a duly adjusted quality irrigation system, together with a specific water management plan to meet the water demand of the crop. Irrigation management in seedling management requires a great deal of specific information, especially when it involves the use of inputs such as hydrorentering polymers and automation technologies of the data acquisition and irrigation system. The experiment was conducted in a greenhouse at the Federal University of Viçosa, Viçosa - MG. Tomato seedlings (Lycopersicon esculentum Mill) were produced in plastic trays of 128 cells, suspended at 1.25 m from the ground. The seedlings were irrigated by 4 micro sprinklers of fixed jet 360º per tray, duly isolated by sideboards, following the methodology developed for this work. During Phase 1, in January / February 2017 (duration of 24 days), the cultivation coefficient (Kc) of seedlings cultured in the presence and absence of hydrogel was evaluated by weighing lysimeter. In Phase 2, September 2017 (duration of 25 days), the seedlings were submitted to 4 irrigation managements (Kc, timer, 0.50 ETo, and 1.00 ETo), in the presence and absence of hydrogel and then evaluated in relation to quality parameters. The microclimate inside the greenhouse was monitored with the use of air temperature, relative humidity and global radiation sensors connected to a microcontroller that performed hourly calculations of reference evapotranspiration by Penman-Monteith standard method FAO56 modified for the balance of long waves according to Walker, Aldrich, Short (1983), and conducted water balance and irrigation decision making for each experimental treatment. Kc of seedlings cultured on a substrate with hydrogel (1.55) was higher than Kc on a pure substrate (1.39). The use of the hydrogel was a differential for the production of earlier tomato seedlings, with higher final height, the larger diameter of the colon, greater accumulation of a dry mass of shoot, a larger area of crown projection and greater the rate of relative growth. The handling 1.00 ETo promoted higher relative growth rate.

Keywords: automatic system; efficiency of water use; precision irrigation, micro sprinkler.

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Authors: El Hadji Mamadou Sonko, Mbaye Mbéguéré, Cheikh Diop, Linda Strande

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In new approaches that are being developed for the treatment of sludge, the valorization of by-product is increasingly encouraged. In this perspective, Echinochloa pyramidalis has been successfully tested in Cameroon. Echinochloa pyramidalis is an efficient forage plant in the treatment of faecal sludge. It provides high removal rates and biosolids of high agronomic value. Thus in order to advise the use of this plant in planted drying beds in Senegal its comparison with the plants long been used in the field deserves to be carried out. That is the aim of this study showing the influence of the nature of the plants on the drainage, the purifying performances and the quality of the biosolids. Echinochloa pyramidalis, Typha australis, and Phragmites australis are the three macrophytes used in this study. The drainage properties of the beds were monitored through the frequency of clogging, the percentage of recovered leachate and the dryness of the accumulated sludge. The development of plants was followed through the measurement of the density. The purification performances were evaluated from the incoming raw sludge flows and the outflows of leachate for parameters such as Total Solids (TS), Total Suspended Solids (TSS), Total Volatile Solids (TVS), Chemical Oxygen Demand (COD), Total Kjeldahl Nitrogen (TKN), Ammonia (NH₄⁺), Nitrate (NO₃⁻), Total Phosphorus (TP), Orthophosphorus (PO₄³⁻) and Ascaris eggs. The quality of the biosolids accumulated on the beds was measured after 3 months of maturation for parameters such as dryness, C/N ratio NH₄⁺/NO₃⁻ ratio, ammonia, Ascaris eggs. The results have shown that the recovered leachate volume is about 40.4%; 45.6% and 47.3%; the dryness about 41.7%; 38.7% and 28.7%, and clogging frequencies about 6.7%; 8.2% and 14.2% on average for the beds planted with Echinochloa pyramidalis, Typha australis and Phragmites australis respectively. The plants of Echinochloa pyramidalis (198.6 plants/m²) and Phragmites australis (138 plants/m²) have higher densities than Typha australis (90.3 plants/m²). The nature of the plants has no influence on the purification performance with reduction percentages around 80% or more for all the parameters followed whatever the nature of the plants. However, the concentrations of these various leachate pollutants are above the limit values of the Senegalese standard NS 05-061 for the release into the environment. The biosolids harvested after 3 months of maturation are all mature with C/N ratios around 10 for all the macrophytes. The NH₄⁺/NO₃⁻ ratio is lower than 1 except for the biosolids originating from the Echinochloa pyramidalis beds. The ammonia is also less than 0.4 g/kg except for biosolids from Typha australis beds. Biosolids are also rich in mineral elements. Their concentrations of Ascaris eggs are higher than the WHO recommendations despite a percentage of inactivation around 80%. These biosolids must be stored for an additional time or composted. From these results, the use of Echinochloa pyramidalis as the main macrophyte can be recommended in the various drying beds planted in sub-Saharan climate conditions.

Keywords: faecal sludge, nature of plants, quality of biosolids, treatment performances

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Authors: Roberta Guerra, Juan Pablo Pozo Hernandez

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Surface sediments from the coastal lagoon of Pialassa Piomboni in the NW Adriatic Sea were collected and analysed and the potential ecological risks in the area were assessed based on the acid-volatile sulphide (AVS) model. The AVS levels are between 0.03 and 8.8 µmol g-1, with the average at 3.1 µmol g-1. The simultaneously extracted metals (∑SEM), which is the molar sum of Cd, Cu, Ni, Pb, and Zn, range from 0.3 to 6.6 µmol g-1, with the average at 1.7 µmol g-1. Most of the high ∑SEM concentrations are located in the southern area of the lagoon. [SEM]Zn had the comparatively high mean concentration (1.4 µmol g-1), and a maximum value of 6.1 µmol g-1, respectively. Concentrations of [SEM]Cd, [SEM]Cu, [SEM]Ni, and [SEM]Pb were consistently lower, with maximum values of 0.007 µmol g-1, 1.4 µmol g-1, 0.3 µmol g-1 and 0.2 µmol g-1, respectively. Compared to other metals, [SEM]Zn was the dominant component in all samples and accounted for approximately 31 - 93% of the ∑SEM, whereas the contribution of Cd – the most toxic metal studied – to ∑SEM was no more than 1%. According to the USEPA evaluation method, the sediment samples can be divided into the three following categories: category 1, adverse biological effects on aquatic life may be expected when ([SEM]–[AVS])/fOC > 3000; category 2, adverse effects on aquatic life are uncertain when ([SEM]–[AVS])/fOC = 130 to 3,000; and category 3, no indication of adverse effects when ([SEM]–[AVS])/fOC < 130. Most of the surface sediments of the Pialassa Piomboni lagoon (>90%) had no adverse biological effects according to the criterion proposed by the USEPA; while adverse effects were uncertain in few stations (~2%).

Keywords: sediment quality, heavy metals, coastal lagoon, bioavailability, SEM, AVS

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Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

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Authors: Samaneh Nadali, Masrah Azrifah Azmi Murad, Nurfadhlina Mohammad Sharef

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Sarcasm is a common phenomenon in social media which is a nuanced form of language for stating the opposite of what is implied. Due to the intentional ambiguity, analysis of sarcasm is a difficult task not only for a machine but even for a human. Although sarcasm detection has an important effect on sentiment, it is usually ignored in social media analysis because sarcasm analysis is too complicated. While there is a few systems exist which can detect sarcasm, almost no work has been carried out on a study and the review of the existing work in this area. This survey presents a nearly full image of sarcasm detection techniques and the related fields with brief details. The main contributions of this paper include the illustration of the recent trend of research in the sarcasm analysis and we highlight the gaps and propose a new framework that can be explored.

Keywords: sarcasm detection, sentiment analysis, social media, sarcasm analysis

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Authors: Danilo Habermann, Aleksander Medella, Carla Cremon, Yusef Caceres

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This paper aims to analyze the ability of 2d point clouds features to classify different models of helicopters using radars. This method does not need to estimate the blade length, the number of blades of helicopters, and the period of their micro-Doppler signatures. It is also not necessary to generate spectrograms (or any other image based on time and frequency domain). This work transforms a radar return signal into a 2D point cloud and extracts features of it. Three classifiers are used to distinguish 9 different helicopter models in order to analyze the performance of the features used in this work. The high accuracy obtained with each of the classifiers demonstrates that the 2D point clouds features are very useful for classifying helicopters from radar signal.

Keywords: helicopter classification, point clouds features, radar, supervised classifiers

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Authors: Alexander Buhr, Klaus Ehrenfried

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Trackside induced airflow velocities, also known as slipstream velocities, are an important criterion for the design of high-speed trains. The maximum permitted values are given by the Technical Specifications for Interoperability (TSI) and have to be checked in the approval process. For train manufactures it is of great interest to know in advance, how new train geometries would perform in TSI tests. The Reynolds number in moving model experiments is lower compared to full-scale. Especially the limited model length leads to a thinner boundary layer at the rear end. The hypothesis is that the boundary layer rolls up to characteristic flow structures in the train wake, in which the maximum flow velocities can be observed. The idea is to enlarge the boundary layer using roughness elements at the train model head so that the ratio between the boundary layer thickness and the car width at the rear end is comparable to a full-scale train. This may lead to similar flow structures in the wake and better prediction accuracy for TSI tests. In this case, the design of the roughness elements is limited by the moving model rig. Small rectangular roughness shapes are used to get a sufficient effect on the boundary layer, while the elements are robust enough to withstand the high accelerating and decelerating forces during the test runs. For this investigation, High-Speed Particle Image Velocimetry (HS-PIV) measurements on an ICE3 train model have been realized in the moving model rig of the DLR in Göttingen, the so called tunnel simulation facility Göttingen (TSG). The flow velocities within the boundary layer are analysed in a plain parallel to the ground. The height of the plane corresponds to a test position in the EN standard (TSI). Three different shapes of roughness elements are tested. The boundary layer thickness and displacement thickness as well as the momentum thickness and the form factor are calculated along the train model. Conditional sampling is used to analyse the size and dynamics of the flow structures at the time of maximum velocity in the train wake behind the train. As expected, larger roughness elements increase the boundary layer thickness and lead to larger flow velocities in the boundary layer and in the wake flow structures. The boundary layer thickness, displacement thickness and momentum thickness are increased by using larger roughness especially when applied in the height close to the measuring plane. The roughness elements also cause high fluctuations in the form factors of the boundary layer. Behind the roughness elements, the form factors rapidly are approaching toward constant values. This indicates that the boundary layer, while growing slowly along the second half of the train model, has reached a state of equilibrium.

Keywords: boundary layer, high-speed PIV, ICE3, moving train model, roughness elements

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Authors: Nji Clement Bang, Rosemary Shafack M., Kum Henry Asei, Yaro Loveline Y

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Scholars perceive learner-centered teaching-learning reform as roles and resources in teacher education (TE) and professional outcome with transformative learning (TL) continuum dimensions. But, teaching-learning reform is fast proliferating amidst debilitating stakeholder systemic dichotomies, resources, commitment, resistance and poor quality outcome that necessitate stronger TE and professional continuums. Scholars keep seeking greater understanding of themes in teaching-learning reform, TE and professional outcome as continuums and how policymakers, student-teachers, teacher trainers and local communities concerned with initial TE can promote continuous holistic quality performance. To sustain the debate continuum and answer the overarching question, we use mixed-methods research-design with diverse literature and 409 sample-data. Onset text, interview and questionnaire analyses reveal debilitating teaching-learning reform in TE continuums that need TL revival. Follow-up focus group discussion and teaching considering TL insights reinforce holistic teaching-learning in TE. Therefore, significant increase in diverse prior-experience articulation1; critical reflection-discourse engagement2; teaching-practice interaction3; complex-activity constrain control4 and formative outcome- reintegration5 reinforce teaching-learning in learning-to-teach role-resource pathways and outcomes. Themes reiterate complex teaching-learning in TE programs that suits TL journeys and student-teachers and students cum teachers, workers/citizens become akin, transformative-learners who evolve personal and collective roles-resources towards holistic-lifelong-learning outcomes. The article could assist debate about quality teaching-learning reform through TL dimensions as TE and professional role-resource continuums.

Keywords: transformative learning perspectives, teacher education, initial teacher education, learner-centered pedagogical reform, life-long learning

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Authors: Regina Maria M. Castilho, Isabela M. Morita, Ana Carolina T. Malavolta, Maximiliano K. Pagliarini

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An essential factor for flower production is solar radiation, which is part of plant vital processes. As excess as shortage of light can harm the development of the culture leading to loss in product quality, Unfeasible or decreasing their commercial value. The objective of this research was to evaluate different light levels and their influence on Amaryllis (Hippeastrum X hybridum Hort.) development and flowering. The experiment was conducted at UNESP, São Paulo State, Brazil from August to October 2014. The bulbs were placed in black vases of 1.2 L filled with commercial substrate and divided into 4 different lighting environments (treatments): T1–greenhouse, T2–greenhouse with shade cloth (50%), T3–low lights indoor (until 500 lx) and T4–medium lights indoor (between 500–1000 lx). The used design was completely randomized with ten repetitions and three vessels (bulbs), totalling 30 vessels (bulbs) per treatment. The evaluated characteristics were: Chlorophyll content, number of leaves, length of leaf, number of simultaneous rods, rod length, rod diameter, number of flowers, flowers diameter, beginning of flowering and flowering duration. The results showed that in greenhouse provided Amaryllis better quality plants.

Keywords: açucena, bulbs, light, ornamental plants

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Authors: Mohammad Reza Dawoudi

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With the increasing rate of patients suffering from chronic pain, several methods for evaluating of chronic pain are suggested. Motion of morbid has been defined as the rate of pine and it is linked with various co-morbid conditions. This study provides a summary of procedure useful to statistics performing direct behavioral observation in hospital settings. We describe the need for and usefulness of comprehensive “morbid motions” observations; provide a primer on the identification, definition, and assessment of morbid behaviors; and outline and discuss specific statistical procedures, including formulating referral motions, describing and conducting the observation. We also provide practical devices for observing and analyzing the obtained information into a report that guides clinical intervention.

Keywords: assessing pain, DNA modeling, image matching technique, pain scale

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Authors: Justyna Humięcka-Jakubowska

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1. Background in music analysis. Traditionally, when we think about a composer’s sketches, the chances are that we are thinking in terms of the working out of detail, rather than the evolution of an overall concept. Since music is a “time art’, it follows that questions of a form cannot be entirely detached from considerations of time. One could say that composers tend to regard time either as a place gradually and partially intuitively filled, or they can look for a specific strategy to occupy it. In my opinion, one thing that sheds light on Stockhausen's compositional thinking is his frequent use of 'form schemas', that is often a single-page representation of the entire structure of a piece. 2. Background in music technology. Sonic Visualiser is a program used to study a musical recording. It is an open source application for viewing, analysing, and annotating music audio files. It contains a number of visualisation tools, which are designed with useful default parameters for musical analysis. Additionally, the Vamp plugin format of SV supports to provide analysis such as for example structural segmentation. 3. Aims. The aim of my paper is to show how SV may be used to obtain a better understanding of the specific musical work, and how the compositional strategy does impact on musical structures and musical surfaces. I want to show that ‘traditional” music analytic methods don’t allow to indicate interrelationships between musical surface (which is perceived) and underlying musical/acoustical structure. 4. Main Contribution. Stockhausen had dealt with the most diverse musical problems by the most varied methods. A characteristic which he had never ceased to be placed at the center of his thought and works, it was the quest for a new balance founded upon an acute connection between speculation and intuition. In the case with Mikrophonie I (1964) for tam-tam and 6 players Stockhausen makes a distinction between the "connection scheme", which indicates the ground rules underlying all versions, and the form scheme, which is associated with a particular version. The preface to the published score includes both the connection scheme, and a single instance of a "form scheme", which is what one can hear on the CD recording. In the current study, the insight into the compositional strategy chosen by Stockhausen was been compared with auditory image, that is, with the perceived musical surface. Stockhausen's musical work is analyzed both in terms of melodic/voice and timbre evolution. 5. Implications The current study shows how musical structures have determined of musical surface. My general assumption is this, that while listening to music we can extract basic kinds of musical information from musical surfaces. It is shown that an interactive strategies of musical structure analysis can offer a very fruitful way of looking directly into certain structural features of music.

Keywords: automated analysis, composer's strategy, mikrophonie I, musical surface, stockhausen

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Authors: Myagmarsuren Soronzonjav, N. Togtokhbayar, L. Davaahuu, B. Minjigdorj, Seong Gu Hwang

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The number of natural or organic product consumers is increased in recent years and this healthy demand pushes to increase usage of healthy meat. At the same time, consumers pay more attention on the healthy fat, especially on unsaturated fatty acids. These long chain carbohydrates reduce heart diseases, improve memory and eye sight and activate the immune system. One of the important issues to be solved for our Mongolia’s food security is to provide healthy, fresh, widely available and cheap meat for the population. Thus, an importance of the Selenge breed meat production is increasing in order to supply the quality meat food security since the Selenge breed cattle are rapidly multiplied, beneficial in term of income, the same quality as Mongolian breed, and well digested for human body. We researched the lipid, unsaturated and saturated fatty acid contents of meat of Selenge breed younger cattle by their muscle types. Result of our research reveals that 11 saturated fatty acids are detected. For the content of palmitic acid among saturated fatty acids, 23.61% was in the sirloin meat, 24.01% was in the round and chuck meat, and 24.83% was in the short loin meat.

Keywords: chromatogram, gas chromatography, organic resolving, saturated and unsaturated fatty acids

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Authors: P. M. Sreekanth

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Teak (Tectona grandis L. f.) is a tree species indigenous to India and other Southeastern countries. It produces high-value timber and is easily established in plantations. Reforestation requires a constant supply of high quality seeds. Seed Production Areas (SPA) of teak are improved stands used for collection of open-pollinated quality seeds in large quantities. Information on the genetic diversity of major teak SPAs in India is scanty. The genetic structure of four important seed production areas of Kerala State in Southern India was analyzed employing amplified fragment length polymorphism markers using ten selective primer combinations on 80 samples (4 populations X 20 trees). The study revealed that the gene diversity of the SPAs varied from 0.169 (Konni SPA) to 0.203 (Wayanad SPA). The percentage of polymorphic loci ranged from 74.42 (Parambikulam SPA) to 84.06 (Konni SPA). The mean total gene diversity index (HT) of all the four SPAs was 0.2296 ±0.02. A high proportion of genetic diversity was observed within the populations (83%) while diversity between populations was lower (17%) (GST = 0.17). Principal coordinate analysis and STRUCTURE analysis of the genotypes indicated that the pattern of clustering was in accordance with the origin and geographic location of SPAs, indicating specific identity of each population. A UPGMA dendrogram was prepared and showed that all the twenty samples from each of Konni and Parambikulam SPAs clustered into two separate groups, respectively. However, five Nilambur genotypes and one Wayanad genotype intruded into the Konni cluster. The higher gene flow estimated (Nm = 2.4) reflected the inclusion of Konni origin planting stock in the Nilambur and Wayanad plantations. Evidence for population structure investigated using 3D Principal Coordinate Analysis of FAMD software 1.30 indicated that the pattern of clustering was in accordance with the origin of SPAs. The present study showed that assessment of genetic diversity in seed production plantations can be achieved using AFLP markers. The AFLP fingerprinting was also capable of identifying the geographical origin of planting stock and there by revealing the occurrence of the errors in genotype labeling. Molecular marker-based selective culling of genetically similar trees from a stand so as to increase the genetic base of seed production areas could be a new proposition to improve quality of seeds required for raising commercial plantations of teak. The technique can also be used to assess the genetic diversity status of plus trees within provenances during their selection for raising clonal seed orchards for assuring the quality of seeds available for raising future plantations.

Keywords: AFLP, genetic structure, spa, teak

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Authors: Eric Muñoz de la Torre, Julián González Trinidad, Efrén González Ramírez

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Rain varies greatly in its duration, intensity, and spatial coverage, it is important to have sub-daily rainfall data for various applications, including risk prevention. However, the ground measurements are limited by the low and irregular density of rain gauges. An alternative to this problem are the Satellite Precipitation Products (SPPs) that use passive microwave and infrared sensors to estimate rainfall, as IMERG, however, these SPPs have to be validated before their application. The aim of this study is to evaluate the performance of the IMERG: Integrated Multi-satellitE Retrievals for Global Precipitation Measurament final run V06B SPP in a semi-arid region of Mexico, using 4 automatic rain gauges (pluviographs) sub-daily data of October 2019 and June to September 2021, using the Minimum inter-event Time (MIT) criterion to separate unique rain events with a dry period of 10 hrs. for the purpose of evaluating the rainfall properties (depth, duration and intensity). Point to pixel analysis, continuous, categorical, and volumetric statistical metrics were used. Results show that IMERG is capable to estimate the rainfall depth with a slight overestimation but is unable to identify the real duration and intensity of the rain events, showing large overestimations and underestimations, respectively. The study zone presented 80 to 85 % of convective rain events, the rest were stratiform rain events, classified by the depth magnitude variation of IMERG pixels and pluviographs. IMERG showed poorer performance at detecting the first ones but had a good performance at estimating stratiform rain events that are originated by Cold Fronts.

Keywords: IMERG, rainfall, rain gauge, remote sensing, statistical evaluation

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