Search results for: Amparo Iris Zavaleta

Authors: Gina Zavaleta-Espejo, Segundo R. Jáuregui-Rosas, Fanny V. Samanamud-Moreno, José Saldaña Jiménez, Anibal Felix-Quintero, Víctor Montero-Del Aguila, Elsi Mejía-Uriarte

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Vicugnapacos "alpaca" fabrics are considered special for their finesse, and the garments in the textile market are very luxurious. It has many special characteristics such as antiallergic, soft, hygroscopic, among others. In this sense, the research aimed to evaluate the antimicrobial activity of alpaca fabrics functionalized with silver nanoparticles on the bacteria Escherichia coli ATCC 25922 and Staphylococcus aureus ATCC 25923. For the functionalization of the fabrics, AgNO3 and different concentrations of trisodium citrate (TSC) 2, 6, and 10 mg. Tissue characterization was performed using Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). The determination of the antimicrobial activity of the alpaca tissues was made by the Kirby-Bauer method with alpaca tissue discs functionalized with silver nanoparticles, an experimental design was made in completely randomized blocks with three treatments and a negative control with three repetitions. The results showed that inhibition halos were formed for both bacteria, therefore, the functionalized tissues have a high antimicrobial activity, whose mechanism of action is attributed to the free radicals (ROS) generated by the nanoparticles that cause oxidative damage to the bacteria. proteins and lipids of the bacterial cell wall.

Keywords: antimicrobial, animal fibers, fabrics, functionalization, trisodium citrate

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Authors: Iris Lavalle Acejo, Helen Sampson

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Drawing from the perspectives of female seafarers, this article offers an analysis of an empirical investigation of the mechanisms by which women are excluded from working on board cargo ships. Female seafarers currently make up about 1% of seafarers in the global cargo shipping industry. As female presence onboard continues to constitute a small proportion of the total crew, we consider their professional advancement in comparison with their male counterparts and the ways in which they are discouraged from entering, or remining within, the industry. With interactions at work severely constrained by the traditionally masculine working culture of the ship, the study hopes to provide insights on the mechanisms in which they face and navigate barriers as they both accommodate and resist gendered differences onboard.

Keywords: female seafarers, glasswalls, genderbarriers, genderedworkplaces

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Authors: Shabir Ahmad Sofi, Shubham Aggarwal, Sanyam Singhal, Roohie Naaz

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Biometric recognition refers to an automatic recognition of individuals based on a feature vector(s) derived from their physiological and/or behavioral characteristic. Biometric recognition systems should provide a reliable personal recognition schemes to either confirm or determine the identity of an individual. These features are used to provide an authentication for computer based security systems. Applications of such a system include computer systems security, secure electronic banking, mobile phones, credit cards, secure access to buildings, health and social services. By using biometrics a person could be identified based on 'who she/he is' rather than 'what she/he has' (card, token, key) or 'what she/he knows' (password, PIN). In this paper, a brief overview of biometric methods, both unimodal and multimodal and their advantages and disadvantages, will be presented.

Keywords: biometric, DNA, fingerprint, ear, face, retina scan, gait, iris, voice recognition, unimodal biometric, multimodal biometric

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Authors: Stylianos Kampakis

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This paper presents a new algorithm for neural networks called “Input Dropout with Aggressive Re-weighting” (IDAR) aimed specifically at datasets with many useless features. IDAR combines two techniques (dropout of input neurons and aggressive re weighting) in order to eliminate the influence of noisy features. The technique can be seen as a generalization of dropout. The algorithm is tested on two different benchmark data sets: a noisy version of the iris dataset and the MADELON data set. Its performance is compared against three other popular techniques for dealing with useless features: L2 regularization, LASSO and random forests. The results demonstrate that IDAR can be an effective technique for handling data sets with many useless features.

Keywords: neural networks, feature selection, regularization, aggressive reweighting

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Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin

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This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.

Keywords: neural network, self-organizing map, rule extraction, rule insertion

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Authors: Walid Cherif

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Data mining has, over recent years, seen big advances because of the spread of internet, which generates everyday a tremendous volume of data, and also the immense advances in technologies which facilitate the analysis of these data. In particular, classification techniques are a subdomain of Data Mining which determines in which group each data instance is related within a given dataset. It is used to classify data into different classes according to desired criteria. Generally, a classification technique is either statistical or machine learning. Each type of these techniques has its own limits. Nowadays, current data are becoming increasingly heterogeneous; consequently, current classification techniques are encountering many difficulties. This paper defines new measure functions to quantify the resemblance between instances and then combines them in a new approach which is different from actual algorithms by its reliability computations. Results of the proposed approach exceeded most common classification techniques with an f-measure exceeding 97% on the IRIS Dataset.

Keywords: data mining, knowledge discovery, machine learning, similarity measurement, supervised classification

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Authors: Iris Käppler, Paul Matthäi, Chokri Cherif

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

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

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Authors: Eya Hentati, Mona Lamine, Jalel Bouzid

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In this study, a laboratory-scale was designed and fabricated to treat single house greywater in the north of Tunisia with a combination of physical and natural treatments systems. The combined system includes a bio-filter composed of LECA® (lightweight expanded clay aggregate) followed by a vertical up-flow constructed wetland planted with Iris pseudacorus and Typha Latifolia. Applied two hydraulic retention times (HRTs) with two different plants types showed that a bio-filter planted with Typha Latifolia has an optimum removal efficiency for degradation of organic matter and transformation of nitrogen and phosphate at HRT of 30 h. The optimum removal efficiency of biochemical oxygen demand (BOD), chemical oxygen demand (COD), and suspended solids (SS) ranged between 48-65%, between while the nutrients removal was in the range of 70% to 90%. Fecal coliforms dropped by three to four orders of magnitude from their initial concentration, but this steel does not meet current regulations for unlimited irrigation. Hence further improvement procedures are suggested.

Keywords: constructed wetland, greywater treatment, nutriments, organics

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Authors: I. Benmehdi, O. Hasnaoui, N. Hachemi, M. Bouazza

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The Understanding of the mechanisms structuring of plant diversity in the region of Tlemcen (western Algeria) is a related problem. The current floristic composition of different groups in Pistacia lentiscus L. resulting from the combination of human and climate action. This study is devoted to biodiversity inventory and phytogeographic characterization of Pistacia lentiscus groups in the Honaine coastal (western Algeria). The floristic inventory (150 levels) made in three stations of the study area allowed to count a 109 species belonging to 44 families of vascular plants. The biogeographical analysis of the Pistacia lentiscus groups reveals the most representative elements. The Mediterranean elements are numerically the most dominant with 39.45% represented by: Pistacia lentiscus, Cistus monspeliensis, Plantago lagopus, Linum strictum, Echium vulgare; followed by the western Mediterranean elements with 10.09% and are represented by: Chamaerops humilis, Lavandula dentata, Ampelodesma mauritanicum and Iris xyphium. However, this phytotaxonomic wealth is exposed to anthropogenic impact causing its disruption see its decline.

Keywords: Pistacia lentiscus L., phytodiversity, phytogeography, honaine, western Algeria

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Authors: Celia Marilia Martins, Sonia I. V. Guilundo, Iris M. Victorino, Antonio O. Quilambo

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In Mozambique rapid industrialization (mining, aluminium and cement activities) and urbanization processes has led to the incorporation of heavy metals on soil, thus degrading not only the quality of the environment, but also affecting plants, animals and human healthy. Several methods have been used to remediate contaminated soils, but most of them are costly and difficult to get optimum results. Currently, phytoremediation is an effective and affordable technological solution used to extract or remove inactive metals from contaminated soil. Phytoremediation is the use of plants to clean up a contamination from soils, sediments, and water. This technology is environmental friendly and potentially cost effective. The present investigation summarised the potential of edible vegetable to grow under the high level of heavy metals such as lead and zinc. The plants used in these studies include Tomatoes, lettuce and Soya beans. The studies have shown that edible plants can be grown under the high level of heavy metals on the soil. Further investigations are identifying mechanisms used by plants to ensure a safe and sustainable use for remediation of contaminated soils by heavy metals.

Keywords: contaminated soil, edible plants, heavy metals, phytoremediation

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Authors: Edgard Barki, Tânia Modesto Veludo-de-Oliveira, Felipe Zambaldi

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The social enterprise sector can be characterized as organizations that aim to solve social problems with financial sustainability and using market mechanisms. This sector has shown an increasing interest worldwide. Despite the growth and relevance of the sector, there is still a gap regarding the assessment of the social impact resulting from the initiatives of the organizations in this field. A number of metrics have been designed worldwide to evaluate the impact of social enterprises (e.g., IRIS, GIIRS, BACO), as well as some ad hoc studies that have been carried out, mainly in the microcredit sector, but there is still a gap to be filled in the development of research in social impact evaluation. Therefore, this research seeks to evaluate the social impact of two social enterprises (Terra Nova and Vivenda) in the area of housing in Brazil. To evaluate these impacts and their dimensions, we conducted an exploratory research, through three focus groups, thirty in-depth interviews and a survey with beneficiaries of both organizations. The results allowed us to evaluate how the two organizations were able to create a deep social impact in the populations served. Terra Nova has a more collective perspective, with a clear benefit of social inclusion and improvement of the community’s infrastructure, while Vivenda has a more individualized perspective, improving self-esteem, sociability and family coexistence.

Keywords: Brazil, housing, social enterprise, social impact evaluation

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Authors: Karol Rodriguez-Peña, Martha L. Macias-Rubalcava, Leticia Rocha-Zavaleta, Sergio Sanchez

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A bioassay-guided study for anti-cancer compounds from endophytes of the Mexican medicinal plant Amphipteryygium adstringens resulted in the isolation of a streptomycete capable of producing a group of compounds with high cytotoxic activity. Microorganisms from surface sterilized samples of various sections of the plant were isolated and all the actinomycetes found were evaluated for their potential to produce compounds with cytotoxic activity against cancer cell lines MCF7 (breast cancer) and HeLa (cervical cancer) as well as the non-tumoural cell line HaCaT (keratinocyte). The most active microorganism was picked for further evaluation. The identification of the microorganism was carried out by 16S rDNA gene sequencing, finding the closest proximity to Streptomyces scabrisporus, but with the additional characteristic that the strain isolated in this study was capable of producing colorful compounds never described for this species. Crude extracts of dichloromethane and ethyl acetate showed IC50 values of 0.29 and 0.96 μg/mL for MCF7, 0.51 and 1.98 μg/mL for HeLa and 0.96 and 2.7 μg/mL for HaCaT. Scaling the fermentation to 10 L in a bioreactor generated 1 g of total crude extract, which was fractionated by silica gel open column to yield 14 fractions. Nine of the fractions showed cytotoxic activity. Fraction 4 was chosen for subsequent purification because of its high activity against cancerous cell lines, lower activity against keratinocytes. HPLC-UV-MS/ESI was used for the evaluation of this fraction, finding at least 10 different compounds with high values of m/z (≈588). Purification of the compounds was carried out by preparative thin-layer chromatography. The prevalent compound was Steffimycin B, a molecule known for its antibiotic and cytotoxic activities and also for its low solubility in aqueous solutions. Along with steffimycin B, another five compounds belonging to the steffimycin family were isolated and at this moment their structures are being elucidated, some of which display better solubility in water: an attractive property for the pharmaceutical industry. As a conclusion to this study, the isolation of endophytes resulted in the discovery of a strain capable of producing compounds with high cytotoxic activity that need to be studied for their possible utilization.

Keywords: amphipterygium adstringens, cytotoxicity, streptomyces scabrisporus, steffimycin

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Authors: Zaida Perez-Bassart, Berta Polanco-Estibalez, Maria Jose Fabra, Amparo Lopez-Rubio, Antonio Martinez-Abad

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Mushroom production has enormously increased in recent years, not only as food products but also for applications in pharmaceuticals, nutraceuticals, and cosmetics. Consequently, interest in its chemical composition, nutritional value, and therapeutic properties has also increased. Fungi are rich in bioactive compounds such as polysaccharides, polyphenols, glycopeptides, and ergosterol, of great medicinal value, but within polysaccharides, β-glucans are the most prominent molecules. They are formed by D-glucose monomers, linked by β-glucosidic bonds β-(1,3) with side chains linked by β-(1,6) bonds. The number and position of the β-(1,6) branches strongly influence the arrangement of the tertiary structure, which, together with the molecular weight, determine the different attributed bioactivities (immunostimulating, anticancer, antimicrobial, prebiotic, etc.) and physico-chemical properties (solubility, bioaccessibility, viscosity or emulsifying). On the other hand, there is a growing interest in the study of fungi as an alternative source of chitin obtained from the by-products of the fungal industry. In this work, a cascade extraction process using aqueous neutral and alkaline treatments was carried out for Grifola frondosa and Lentinula edodes, and the compositional analysis and functional properties of each fraction were characterized. Interestingly, the first fraction obtained by using aqueous treatment at room temperature was the richest in polysaccharides, proteins, and polyphenols, thus obtaining a greater antioxidant capacity than in the other fractions. In contrast, the fractions obtained by alkaline treatments showed a higher degree of β-glucans purification compared to aqueous extractions but a lower extraction yield. Results revealed the different structural recalcitrance of β-glucans, preferentially linked to proteins or chitin depending on the fungus type, which had a direct impact on the functionalities and bioactivities of each fraction.

Keywords: fungi, mushroom, β-glucans, chitin

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Authors: Husnain Mushtaq, Mary Anjum, Muhammad Aleem

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The main objective of this paper is used to develop a high security in Automatic Teller Machine (ATM). In these system bankers will collect the mobile numbers from the customers and then provide a code on their mobile number. In most country existing ATM machine use the magnetic card reader. The customer is identifying by inserting an ATM card with magnetic card that hold unique information such as card number and some security limitations. By entering a personal identification number, first the customer is authenticated then will access bank account in order to make cash withdraw or other services provided by the bank. Cases of card fraud are another problem once the user’s bank card is missing and the password is stolen, or simply steal a customer’s card & PIN the criminal will draw all cash in very short time, which will being great financial losses in customer, this type of fraud has increase worldwide. So to resolve this problem we are going to provide the solution using “Mobile SMS code” and ATM “PIN code” in order to improve the verify the security of customers using ATM system and confidence in the banking area.

Keywords: PIN, inquiry, biometric, magnetic strip, iris recognition, face recognition

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Authors: Azmi Ilmi Aziz, Wisnu Sadasih, Rizal Fanany

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Purpose: This study describes systemic factors, intraocular lens (IOL), and ocular abnormalities in patients with IOL glistening at a tertiary hospital in Semarang. Methods: A retrospective, with a descriptive approach on patients with IOL glistening who visited the eye clinic between August 2019 to June 2023. Results: Twenty-five patients were examined; 11 patients (44%) had IOL glistening in their right eye, 4 patients (16%) in their left eye, and 10 patients (40%) in both eyes. The gender of patients consisted of 12 male patients (48%) and 13 female patients (52%). The median age of the patients was 68 years. The mean onset was 4.44 years after the first cataract surgery. Hypertension was found in 13 patients (52%), and diabetes was found in 9 patients (36%). Nine patients (36%) were identified with a foldable IOL with a closed loop design, and 1 patient (4%) with a PMMA IOL with an iris-fixated IOL design, while 15 other patients’ IOL were unrecorded. Glaucoma was found in 3 patients (12%). Conclusions: The result of this study showed that more than half of the patients were hypertensive, and some were glaucomatous, which had been discussed relevant in previous studies. Most IOL that could be identified was foldable IOL with a closed loop design. To our knowledge, the design of an IOL to glistening had never been explored. A longer study involving larger subjects is needed to better describe the systemic factors, IOL, and ocular abnormalities in patients with IOL glistening.

Keywords: glistening, intraocular lens, foldable IOL, PMMA IOL

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Authors: Sivia Amado Cordeiro, Bruna Rodrigues, Maria Do Ceu Taveira, Catia Marques, Iris Oliveira, Ana Daniela Silva, Cristina Costa-Lobo

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This work intends to analyse the teaching of Psychology in Portugal and, particularly, the teaching of Career Psychology, reflecting about the changes that have occurred to date. Were analysed the educational offerings of 31 Portuguese higher education institutions, 12 public and 19 private, who teach the course of Psychology. The three degrees of study were considered, namely, bachelors, masters and doctoral. The analysis of the data focused on the curricular plans of the different degrees of studies in Psychology made available online by higher education institutions. Through them, we identified the curricular units with themes related to the teaching of Career Psychology. The results show the existence of 89 higher psychology courses in Portugal, distributed throughout the three degrees of studies. Concerning to the teaching of Career Psychology there were registered 49 curricular units with themes dedicated to this area of knowledge. There were identified 16 curricular units in the bachelor’s degree, 31 in master’s degree, and two in doctoral degree. It was observed a reduction in the number of degrees in Psychology in the last nine years in Portugal. We discuss the current situation of Psychology teaching, particularly the teaching of Career Psychology. The aim is to stimulate reflection about future perspectives of Psychology teaching, and specifically, specialized training in Psychology of Career, in Portugal.

Keywords: career psychology, higher education, psychology, Portugal

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Authors: Offer E. Edelstein, Iris Vered, Orly Sarid

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Background: Physical activity (PA) is considered as a major factor in bone density preservation and fracture prevention. Yet, gaps in understanding exist regarding how ethnocultural backgrounds might shape attitudes, intentions, and actual PA participation. Based on the theory of planned behavior (TPB) for predicting PA, the aims of the current study were: i) to compare attitudes, subjective norms, perceived control, intentions and knowledge, across two ethnocultural groups; ii) to evaluate the fit of the model across two ethnocultural groups of women: Israeli-born Jews and Ethiopian immigrants. Methods: Two hundred women (one hundred from each group), aged > 65, completed valid and reliable questionnaires assessing knowledge, TPB components, and actual PA. Results: The level of knowledge on osteoporosis was relatively low in both groups. Intention to participate in PA was the only variable that directly predicted actual PA. Intention to participate in PA served as a mediator among attitudes, subjective norms, perceived control, and actual PA. The TPB components mediated the link between knowledge and intention to participate in PA. Conclusion: It is important to understand and augment interventions that enhance PA, in the community, and with sensitivity concerning each ethnocultural group.

Keywords: attitudes, ethnocultural groups, knowledge, physical activity

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Authors: Lavanya Srinivasan

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Biometric identification is to identify unique features in a person like fingerprints, iris, ear, and voice recognition that need the subject's permission and physical contact. Gait biometric is used to identify the unique gait of the person by extracting moving features. The main advantage of gait biometric to identify the gait of a person at a distance, without any physical contact. In this work, the gait biometric is used for person re-identification. The person walking naturally compared with the same person walking with bag, coat, and case recorded using longwave infrared, short wave infrared, medium wave infrared, and visible cameras. The videos are recorded in rural and in urban environments. The pre-processing technique includes human identified using YOLO, background subtraction, silhouettes extraction, and synthesis Gait Entropy Image by averaging the silhouettes. The moving features are extracted from the Gait Entropy Energy Image. The extracted features are dimensionality reduced by the principal component analysis and recognised using different classifiers. The comparative results with the different classifier show that linear discriminant analysis outperforms other classifiers with 95.8% for visible in the rural dataset and 94.8% for longwave infrared in the urban dataset.

Keywords: biometric, gait, silhouettes, YOLO

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Authors: S. Chami, J. Chauvin, T. Demarest, Stan Ng, M. Straus, W. Jahner

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Biometrics tools such as fingerprint and iris are widely used in industry to protect critical assets. However, their vulnerability and lack of robustness raise several worries about the protection of highly critical assets. Biometrics based on Electrocardiographic (ECG) signals is a robust identification tool. However, most of the state-of-the-art techniques have worked on clinical signals, which are of high quality and less noisy, extracted from wearable devices like a smartwatch. In this paper, we are presenting a complete machine learning pipeline that identifies people using ECG extracted from an off-person device. An off-person device is a wearable device that is not used in a medical context such as a smartwatch. In addition, one of the main challenges of ECG biometrics is the variability of the ECG of different persons and different situations. To solve this issue, we proposed two different approaches: per person classifier, and one-for-all classifier. The first approach suggests making binary classifier to distinguish one person from others. The second approach suggests a multi-classifier that distinguishes the selected set of individuals from non-selected individuals (others). The preliminary results, the binary classifier obtained a performance 90% in terms of accuracy within a balanced data. The second approach has reported a log loss of 0.05 as a multi-class score.

Keywords: biometrics, electrocardiographic, machine learning, signals processing

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Authors: M. Amparo Nunez-Andres, Nieves Lantada

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One of the most harmful geological risks is rockfalls. They cause both economic lost, damaged in buildings and infrastructures, and personal ones. Therefore, in order to estimate the risk of the exposed elements, it is necessary to know the mechanism of this kind of events, since the characteristics of the rock walls, to the propagation of fragments generated by the initial detached rock mass. In the framework of the research RockModels project, several inventories of rockfalls were carried out along the northeast of the Spanish peninsula and the Mallorca island. These inventories have general information about the events, although the important fact is that they contained detailed information about fragmentation. Specifically, the IBSD (Insitu Block Size Distribution) is obtained by photogrammetry from drone or TLS (Terrestrial Laser Scanner) and the RBSD (Rock Block Size Distribution) from the volume of the fragment in the deposit measured by hand. In order to share all this information with other scientists, engineers, members of civil protection, and stakeholders, it is necessary a platform accessible from the internet and following interoperable standards. In all the process, open-software have been used: PostGIS 2.1., Geoserver, and OpenLayers library. In the first step, a spatial database was implemented to manage all the information. We have used the data specifications of INSPIRE for natural risks adding specific and detailed data about fragmentation distribution. The next step was to develop a WMS with Geoserver. A previous phase was the creation of several views in PostGIS to show the information at different scales of visualization and with different degrees of detail. In the first view, the sites are identified with a point, and basic information about the rockfall event is facilitated. In the next level of zoom, at medium scale, the convex hull of the rockfall appears with its real shape and the source of the event and fragments are represented by symbols. The queries at this level offer a major detail about the movement. Eventually, the third level shows all elements: deposit, source, and blocks, in their real size, if it is possible, and in their real localization. The last task was the publication of all information in a web mapping site (www.rockdb.upc.edu) with data classified by levels using libraries in JavaScript as OpenLayers.

Keywords: geological risk, web mapping, WMS, rockfalls

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Authors: M. Amparo Núñez-Andrés, Felipe Buill, Albert Prades

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More and more frequently, geomatics techniques such as terrestrial laser scanning or digital photogrammetry, either terrestrial or from drones, are being used to obtain digital terrain models (DTM) used for the monitoring of geological phenomena that cause natural disasters, such as landslides, rockfalls, debris-flow. One of the main multitemporal analyses developed from these models is the quantification of volume changes in the slopes and hillsides, either caused by erosion, fall, or land movement in the source area or sedimentation in the deposition zone. To carry out this task, it is necessary to filter the point clouds of all those elements that do not belong to the slopes. Among these elements, vegetation stands out as it is the one we find with the greatest presence and its constant change, both seasonal and daily, as it is affected by factors such as wind. One of the best-known indexes to detect vegetation on the image is the NVDI (Normalized Difference Vegetation Index), which is obtained from the combination of the infrared and red channels. Therefore it is necessary to have a multispectral camera. These cameras are generally of lower resolution than conventional RGB cameras, while their cost is much higher. Therefore we have to look for alternative indices based on RGB. In this communication, we present the results obtained in Georisk project (PID2019‐103974RB‐I00/MCIN/AEI/10.13039/501100011033) by using the GLI (Green Leaf Index) and ExG (Excessive Greenness), as well as the change to the Hue-Saturation-Value (HSV) color space being the H coordinate the one that gives us the most information for vegetation filtering. These filters are applied both to the images, creating binary masks to be used when applying the SfM algorithms, and to the point cloud obtained directly by the photogrammetric process without any previous filter or the one obtained by TLS (Terrestrial Laser Scanning). In this last case, we have also tried to work with a Riegl VZ400i sensor that allows the reception, as in the aerial LiDAR, of several returns of the signal. Information to be used for the classification on the point cloud. After applying all the techniques in different locations, the results show that the color-based filters allow correct filtering in those areas where the presence of shadows is not excessive and there is a contrast between the color of the slope lithology and the vegetation. As we have advanced in the case of using the HSV color space, it is the H coordinate that responds best for this filtering. Finally, the use of the various returns of the TLS signal allows filtering with some limitations.

Keywords: RGB index, TLS, photogrammetry, multispectral camera, point cloud

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Authors: David P. Tantua, Abdulkader Helwan

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Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

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Authors: Rachell Denise S. Concepcion, Chantelle Vianca D. L. Cobarrubias, Kimberly B. Coloma, Celina Renee R. Colorado, Charlene S. Constantino, Huette Iris C. Consulta

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AIMS: This study determined the effect of motivational video in increasing the level of self-motivation among first year nursing students to pursue their nursing career. METHODS: A quantitative quasi experimental one-group pretest-posttest research design was used and purposive sampling technique was utilized. Motivation for Choosing Nursing as a Career Questionnaire was used in determining the level of motivation before and after using the motivational video. The of motivational video entitled, “Testimonials from Nurses” was used as the intervention wherein testimonials from successful Thomasian nursing graduates was considered and viewed by the students in order to inspire them to take nursing as their career. The subjects are nursing students who obtained a score ranging from 21-40 in the questionnaire. Before the viewing, the researchers provided a brief introduction and background to enable the participants to fully understand the contents. After which, debriefing was done. The data gathered was analyzed using the Paired T-Test using SPSS version 21.0. The Pre-test and Post-test scores were compared, which further statistically, differentiated by mean, standard deviation and t-test scores. Results: The t-test value is -17.221 and p value of 0.00 < 0.05 which indicates that there is a statistically significant change in the level of self-motivation of first year nursing students before and after viewing the motivational video. Conclusion: It was therefore concluded that motivational video entitled, “Testimonials From Nurses is an effective intervention in increasing the level of self-motivation of first year nursing students to pursue their nursing career.

Keywords: motivational video, freshmen, self-motivation, nursing career

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Authors: Mohhamed El Habib Labdouni

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Introduction: Co-infection with VIH and tuberculosis poses one of the major ongoing challenges for global TB and AIDS prevention and control. The objective of this study is to raise the issue of the resurgence of TB, in People living with VIH supported in a referent center in western Algeria. Its epidemiological, clinical, biological and radiological new trends, and to compare the mortality rate between early and delayed ART. Methods: It was a prospective study, during 36 months from the 01st/01/2012 to 31st/12/2014, by identifying and analyzing cases of TB-VIH co-infection. Our population was devised in two groups/ early ART and delayed ART. The primary and secondary endpoints were analyzed with Kaplan-Meier curves and log-rank test the period of follow up, which was fixed at 300 weeks. Results: Sixty cases of co-infection TB -VIH were enrolled in our study: 78.3% had pulmonary tuberculosis associated with extra-pulmonary, 13.3% had only pulmonary tuberculosis and 08.3% presented strictly extra-pulmonary TB. The clinical particularity of this co-infection is the frequency of serious localization such us: pleural 23.3%, peritoneal 31.7%, and meningeal suffusion 13.3%.y-.biologicaly we notice the predominance both of pancytopenia and leucoanemia, hyponatremia in 38,6% and hypokalemia in 19,3%. By analyzing Kaplan-Meier survival curves, we notice that early ART initiation is associated with a significant reduction of all-cause mortality (p = 0,000), and we have identified several prognostic factors such as hypokalemia hyponatremia, leukocytosis thrombopenemia leucothrombopenia (p = 0,005). Conclusion: Our study confirms most of the results reported in the literature. Early ART initiation reduces the rate of all-cause mortality, despite the probability of the occurrence of TB-IRIS.

Keywords: TB-HIV co-infection, early ART, hyponatremia, extrapulmonary tuberculosis

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Authors: Kristian Bautista, Ruben A. Idoy

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A bio-inspired metaheuristic algorithm inspired by the theory of collective animal behavior (CAB) was integrated to density-based clustering modeled as multimodal optimization problem. The algorithm was tested on synthetic, Iris, Glass, Pima and Thyroid data sets in order to measure its effectiveness relative to CDE-based Clustering algorithm. Upon preliminary testing, it was found out that one of the parameter settings used was ineffective in performing clustering when applied to the algorithm prompting the researcher to do an investigation. It was revealed that fine tuning distance δ3 that determines the extent to which a given data point will be clustered helped improve the quality of cluster output. Even though the modification of distance δ3 significantly improved the solution quality and cluster output of the algorithm, results suggest that there is no difference between the population mean of the solutions obtained using the original and modified parameter setting for all data sets. This implies that using either the original or modified parameter setting will not have any effect towards obtaining the best global and local animal positions. Results also suggest that CDE-based clustering algorithm is better than CAB-density clustering algorithm for all data sets. Nevertheless, CAB-density clustering algorithm is still a good clustering algorithm because it has correctly identified the number of classes of some data sets more frequently in a thirty trial run with a much smaller standard deviation, a potential in clustering high dimensional data sets. Thus, the researcher recommends further investigation in the post-processing stage of the algorithm.

Keywords: clustering, metaheuristics, collective animal behavior algorithm, density-based clustering, multimodal optimization

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Authors: Arvind Srivastav, Tarun Kanti Bhattacharyya

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The north-eastern, Himalayan, and Eastern Ghats Belt of India comprise of earthquake-prone, remote, and hilly terrains. Earthquakes have caused enormous damages in these regions in the past. A wireless sensor network based earthquake early warning system (EEWS) is being developed to mitigate the damages caused by earthquakes. It consists of sensor nodes, distributed over the region, that perform majority voting of the output of the seismic sensors in the vicinity, and relay a message to a base station to alert the residents when an earthquake is detected. At the heart of the EEWS is a low-power two-stage seismic sensor that continuously tracks seismic events from incoming three-axis accelerometer signal at the first-stage, and, in the presence of a seismic event, triggers the second-stage P-wave detector that detects the onset of P-wave in an earthquake event. The parameters of the P-wave detector have been optimized for minimizing detection time and maximizing the accuracy of detection.Working of the sensor scheme has been verified with seven earthquakes data retrieved from IRIS. In all test cases, the scheme detected the onset of P-wave accurately. Also, it has been established that the P-wave onset detection time reduces linearly with the sampling rate. It has been verified with test data; the detection time for data sampled at 10Hz was around 2 seconds which reduced to 0.3 second for the data sampled at 100Hz.

Keywords: earthquake early warning system, EEWS, STA/LTA, polarization, wavelet, event detector, P-wave detector

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Authors: Amparo Camacho

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ABET accredited programs must assess the development of student learning outcomes (SOs) in engineering programs. Different institutions implement different strategies for this assessment, and they are usually designed “in house.” This paper presents a proposal for including standardized tests to complement the ABET assessment model in an engineering college made up of six distinct engineering programs. The engineering college formulated a model of quality assurance in education to be implemented throughout the six engineering programs to regularly assess and evaluate the achievement of SOs in each program offered. The model uses diverse techniques and sources of data to assess student performance and to implement actions of improvement based on the results of this assessment. The model is called “Assessment Process Model” and it includes SOs A through K, as defined by ABET. SOs can be divided into two categories: “hard skills” and “professional skills” (soft skills). The first includes abilities, such as: applying knowledge of mathematics, science, and engineering and designing and conducting experiments, as well as analyzing and interpreting data. The second category, “professional skills”, includes communicating effectively, and understanding professional and ethnical responsibility. Within the Assessment Process Model, various tools were used to assess SOs, related to both “hard” as well as “soft” skills. The assessment tools designed included: rubrics, surveys, questionnaires, and portfolios. In addition to these instruments, the Engineering College decided to use tools that systematically gather consistent quantitative data. For this reason, an in-house exam was designed and implemented, based on the curriculum of each program. Even though this exam was administered during various academic periods, it is not currently considered standardized. In 2017, the Engineering College included three standardized tests: one to assess mathematical and scientific reasoning and two more to assess reading and writing abilities. With these exams, the college hopes to obtain complementary information that can help better measure the development of both hard and soft skills of students in the different engineering programs. In the first semester of 2017, the three exams were given to three sample groups of students from the six different engineering programs. Students in the sample groups were either from the first, fifth, and tenth semester cohorts. At the time of submission of this paper, the engineering college has descriptive statistical data and is working with various statisticians to have a more in-depth and detailed analysis of the sample group of students’ achievement on the three exams. The overall objective of including standardized exams in the assessment model is to identify more precisely the least developed SOs in order to define and implement educational strategies necessary for students to achieve them in each engineering program.

Keywords: assessment, hard skills, soft skills, standardized tests

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Authors: Ansah Iris Baffour, Dong-Ho Kim, Sung-Gyu Park

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The ongoing COVID-19 pandemic, caused by the SARS-CoV-2 virus and is gradually shifting to an endemic phase which implies the outbreak is far from over and will be difficult to eradicate. Global cooperation has led to unified precautions that aim to suppress epidemiological spread (e.g., through travel restrictions) and reach herd immunity (through vaccinations); however, the primary strategy to restrain the spread of the virus in mass populations relies on screening protocols that enable rapid on-site diagnosis of infections. Herein, we employed surface enhanced Raman spectroscopy (SERS) for the rapid detection of SARS-CoV-2 lysate on an Au-modified Au nanodimple(AuND)electrode. Through in situone-pot Au electrodeposition on the AuND electrode, Au-lysate nanocomposites were synthesized, generating3D internal hotspots for large SERS signal enhancements within 30 s of the deposition. The capture of lysate into newly generated plasmonic nanogaps within the nanocomposite structures enhanced metal-spike protein contact in 3D spaces and served as hotspots for sensitive detection. The limit of detection of SARS-CoV-2 lysate was 5 x 10-2 PFU/mL. Interestingly, ultrasensitive detection of the lysates of influenza A/H1N1 and respiratory syncytial virus (RSV) was possible, but the method showed ultimate selectivity for SARS-CoV-2 in lysate solution mixtures. We investigated the practical application of the approach for rapid on-site diagnosis by detecting SARS-CoV-2 lysate spiked in normal human saliva at ultralow concentrations. The results presented demonstrate the reliability and sensitivity of the assay for rapid diagnosis of COVID-19.

Keywords: label-free detection, nanocomposites, SARS-CoV-2, surface-enhanced raman spectroscopy

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Authors: Marcela De Oliveira, Marina P. Da Silva, Fernando C. G. Da Rocha, Jorge M. Santos, Jaime S. Cardoso, Paulo N. Lisboa-Filho

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Multiple Sclerosis (MS) is an immune-mediated disease of the central nervous system characterized by neurodegeneration, inflammation, demyelination, and axonal loss. Magnetic resonance imaging (MRI), due to the richness in the information details provided, is the gold standard exam for diagnosis and follow-up of neurodegenerative diseases, such as MS. Brain atrophy, the gradual loss of brain volume, is quite extensive in multiple sclerosis, nearly 0.5-1.35% per year, far off the limits of normal aging. Thus, the brain volume quantification becomes an essential task for future analysis of the occurrence atrophy. The analysis of MRI has become a tedious and complex task for clinicians, who have to manually extract important information. This manual analysis is prone to errors and is time consuming due to various intra- and inter-operator variability. Nowadays, computerized methods for MRI segmentation have been extensively used to assist doctors in quantitative analyzes for disease diagnosis and monitoring. Thus, the purpose of this work was to evaluate the brain volume in MRI of MS patients. We used MRI scans with 30 slices of the five patients diagnosed with multiple sclerosis according to the McDonald criteria. The computational methods for the analysis of images were carried out in two steps: segmentation of the brain and brain volume quantification. The first image processing step was to perform brain extraction by skull stripping from the original image. In the skull stripper for MRI images of the brain, the algorithm registers a grayscale atlas image to the grayscale patient image. The associated brain mask is propagated using the registration transformation. Then this mask is eroded and used for a refined brain extraction based on level-sets (edge of the brain-skull border with dedicated expansion, curvature, and advection terms). In the second step, the brain volume quantification was performed by counting the voxels belonging to the segmentation mask and converted in cc. We observed an average brain volume of 1469.5 cc. We concluded that the automatic method applied in this work can be used for the brain extraction process and brain volume quantification in MRI. The development and use of computer programs can contribute to assist health professionals in the diagnosis and monitoring of patients with neurodegenerative diseases. In future works, we expect to implement more automated methods for the assessment of cerebral atrophy and brain lesions quantification, including machine-learning approaches. Acknowledgements: This work was supported by a grant from Brazilian agency Fundação de Amparo à Pesquisa do Estado de São Paulo (number 2019/16362-5).

Keywords: brain volume, magnetic resonance imaging, multiple sclerosis, skull stripper

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Authors: Adjmal Ghaur, Christoph Peschel, Iris Dienwiebel, Lukas Haneke, Leilei Du , Laurin Profanter, Tobias Placke, Martin Winter

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In recent years, lithium-ion batteries (LIBs)are widely used in electric vehicles (EVs) and mobile energy storage devices (ESDs), which has led to higher requirements for energy density. To fulfill these requirements, tremendous attention has been paid to design advanced LIBs with various siliconactive materials as alternative negative electrodes to replace graphite (372 mAh g⁻¹)due to their high theoretical gravimetric capacity (4200mAh g⁻¹). However, silicon as potential anode material suffers from huge volume changes during charging and discharging and has poor electronicconductivity which negatively impacts the long-term performance and preventshigh silicon contents from practical application. Additionally, an unstable crystalline silicon structure tends to pulverization during the (de)lithiation process. To compensate for the volume changes, alleviate pulverization, and maintain high electronicconductivity, silicon-doped graphite composites with protecting coating layers are a promising approach. In this context, phosphazene compounds are investigated concerning their silicon protecting properties in silicon-doped graphite composites. In detail, electrochemical performance measurements in pouch full-cells(NCM523||SiOx/C), supressing gas formation properties, and post-mortem analyzes were carried out to characterize phosphazene compounds as additive materials. The introduction of the dual-additive approach in state-of-the-art electrolytes leads to synergistic effects between FEC and phosphazene compounds which accelerate the durability of silicon particles and results in enhanced electrochemical performance.

Keywords: silicon, phosphazene, solid electrolyte interphase, electrolyte, gasmeasurements

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