Search results for: climatic classification

Authors: Md. Royhanur Islam, Thomas Cansse, Md. Sahidul Islam, Atiqur Rahman Sunny

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The geographical location of Bangladesh makes it one of the most vulnerable countries to climate change. Climate-induced phenomena mainly affect the south-central region of Bangladesh (Laxmipur district) where they have begun to occur more frequently. The aim of the study was to identify the hydro-climatic factors that lead to weather-related disasters in the coastal areas and analyse the consequences of these factors on coastal livelihoods, with possible adaptation options using participatory rural appraisal (PRA) tools. The present study showed several disasters such as land erosion, depressions and cyclones, coastal flooding, storm surge, and precipitation. The frequency of these disasters is of a noticeable rate. Surveys have also discovered that land erosion is ongoing. Tidal water is being introduced directly into the mainland, and as a result of the salt intrusion, production capacity is declining. The coastal belt is an important area for fishing activities, but due to changed fishing times and a lack of Alternative Income Generating Activities (AIGAs), people have been forced to search for alternative livelihood options by taking both short-term and long-term adaptation options. Therefore, in order to increase awareness and minimize the losses, vulnerable communities must be fully incorporated into disaster response strategies. The government as well as national and international donor organizations should come forward and resolve the present situation of these vulnerable groups since otherwise, they will have to endure endless and miserable suffering due to the effects of climate change ahead in their lives.

Keywords: adaptation, community, fishery development, livelihood

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Authors: Chaima Babi, Said Gadri

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The rapid increase in fake news continues to grow at a very fast rate; this requires implementing efficient techniques that allow testing the re-liability of online content. For that, the current research strives to illuminate the fake news problem using deep learning DL and machine learning ML ap-proaches. We have developed the traditional LSTM (Long short-term memory), and the bidirectional BiLSTM model. A such process is to perform a training task on almost of samples of the dataset, validate the model on a subset called the test set to provide an unbiased evaluation of the final model fit on the training dataset, then compute the accuracy of detecting classifica-tion and comparing the results. For the programming stage, we used Tensor-Flow and Keras libraries on Python to support Graphical Processing Units (GPUs) that are being used for developing deep learning applications.

Keywords: machine learning, deep learning, natural language, fake news, Bi-LSTM, LSTM, multiclass classification

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Authors: Petra Hurbišová, Monika Davidová

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The article deals with the readiness of military professionals for challenging situations. It discusses higher requirements on the psychical endurance of military professionals arising from the specific nature of the military occupation, which is typical for being very difficult to maintain regularity, which is in accordance with the hygiene of work alternated by relaxation. The soldier must be able to serve in the long term and constantly intense performance that goes beyond human tolerance to stress situations. A challenging situation is always associated with overcoming difficulties, obstacles and complicated circumstances or using unusual methods, ways and means to achieve the desired (expected) objectives, performing a given task or satisfying an important need. This paper describes the categories of challenging situations, their classification and characteristics. Attention is also paid to the formation of personality in challenging situations, coping with stress in challenging situations, Phases of solutions of stressful situations, resistance to challenging life situations and its factors. Finally, the article is focused on increasing the readiness of military professionals for challenging situations.

Keywords: coping, challenging situations, stress, stressful situations, military professionals, resilience

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Authors: Jindong Gu, Matthias Schubert, Volker Tresp

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In many outlier detection tasks, only training data belonging to one class, i.e., the positive class, is available. The task is then to predict a new data point as belonging either to the positive class or to the negative class, in which case the data point is considered an outlier. For this task, we propose a novel corrupted Generative Adversarial Network (CorGAN). In the adversarial process of training CorGAN, the Generator generates outlier samples for the negative class, and the Discriminator is trained to distinguish the positive training data from the generated negative data. The proposed framework is evaluated using an image dataset and a real-world network intrusion dataset. Our outlier-detection method achieves state-of-the-art performance on both tasks.

Keywords: one-class classification, outlier detection, generative adversary networks, semi-supervised learning

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Authors: Thang V. Kieu, Long P. Nguyen

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Kernelized Correlation Filter (KCF) based trackers have gained a lot of attention recently because of their accuracy and fast calculation speed. However, this algorithm is not robust in cases where the object is lost by a sudden change of direction, being obscured or going out of view. In order to improve KCF performance in long-term tracking, this paper proposes an anomaly detection method for target loss warning by analyzing the response map of each frame, and a classification algorithm for reliable target re-locating mechanism by using Random fern. Being tested with Visual Tracker Benchmark and Visual Object Tracking datasets, the experimental results indicated that the precision and success rate of the proposed algorithm were 2.92 and 2.61 times higher than that of the original KCF algorithm, respectively. Moreover, the proposed tracker handles occlusion better than many state-of-the-art long-term tracking methods while running at 60 frames per second.

Keywords: correlation filter, long-term tracking, random fern, real-time tracking

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Authors: Musaab Riyadh, Norwati Mustapha, Dina Riyadh

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Trajectory similarity can be defined as the cost of transforming one trajectory into another based on certain similarity method. It is the core of numerous mining tasks such as clustering, classification, and indexing. Various approaches have been suggested to measure similarity based on the geometric and dynamic properties of trajectory, the overlapping between trajectory segments, and the confined area between entire trajectories. In this article, an evaluation of these approaches has been done based on computational cost, usage memory, accuracy, and the amount of data which is needed in advance to determine its suitability to stream mining applications. The evaluation results show that the stream mining applications support similarity methods which have low computational cost and memory, single scan on data, and free of mathematical complexity due to the high-speed generation of data.

Keywords: global distance measure, local distance measure, semantic trajectory, spatial dimension, stream data mining

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Authors: Walid Chakroun, Sorour Alotaibi, Nesreen Ghaddar, Kamel Ghali

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This study aims at determining the extent to which occupant control of microenvironment influences, improves thermal sensation and comfort, and saves energy in spaces equipped with ceiling personalized ventilation (CPV) system assisted by chair fans (CF) and desk fans (DF) in 2 experiments in a climatic chamber equipped with two-station CPV systems, one that allows control of fan flow rate and the other is set to the fan speed of the selected participant in control. Each experiment included two participants each entering the cooled space from transitional environment at a conventional mixed ventilation (MV) at 24 °C. For CPV diffuser, fresh air was delivered at a rate of 20 Cubic feet per minute (CFM) and a temperature of 16 °C while the recirculated air was delivered at the same temperature but at a flow rate 150 CFM. The macroclimate air of the space was at 26 °C. The full speed flow rates for both the CFs and DFs were at 5 CFM and 20 CFM, respectively. Occupant 1 was allowed to operate the CFs or the DFs at (1/3 of the full speed, 2/3 of the full speed, and the full speed) while occupant 2 had no control on the fan speed and their fan speed was selected by occupant 1. Furthermore, a parametric study was conducted to study the effect of increasing the fresh air flow rate on the occupants’ thermal comfort and whole body sensations. The results showed that most occupants in the CPV+CFs, who did not control the CF flow rate, felt comfortable 6 minutes. The participants, who controlled the CF speeds, felt comfortable in around 24 minutes because they were preoccupied with the CFs. For the DF speed control experiments, most participants who did not control the DFs felt comfortable within the first 8 minutes. Similarly to the CPV+CFs, the participants who controlled the DF flow rates felt comfortable at around 26 minutes. When the CPV system was either supported by CFs or DFs, 93% of participants in both cases reached thermal comfort. Participants in the parametric study felt more comfortable when the fresh air flow rate was low, and felt cold when as the flow rate increased.

Keywords: PMV, thermal comfort, thermal environment, thermal sensation

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Authors: Farshideh Einsele, Hassan Foroosh

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In this paper, we present a robust algorithm to recognize extracted text from grocery product images captured by mobile phone cameras. Recognition of such text is challenging since text in grocery product images varies in its size, orientation, style, illumination, and can suffer from perspective distortion. Pre-processing is performed to make the characters scale and rotation invariant. Since text degradations can not be appropriately defined using wellknown geometric transformations such as translation, rotation, affine transformation and shearing, we use the whole character black pixels as our feature vector. Classification is performed with minimum distance classifier using the maximum likelihood criterion, which delivers very promising Character Recognition Rate (CRR) of 89%. We achieve considerably higher Word Recognition Rate (WRR) of 99% when using lower level linguistic knowledge about product words during the recognition process.

Keywords: camera-based OCR, feature extraction, document, image processing, grocery products

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Authors: Jerald Ruta, Ricardo Villar, Jojemar Bantugan, Nycel Barbadillo, Jigg Pelayo

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Streams are important in providing water supply for industrial, agricultural and human consumption, In short when there are streams there are lives. Identifying streams are essential since many developed cities are situated in the vicinity of these bodies of water and in flood management, it serves as basin for surface runoff within the area. This study aims to process and generate features from high-resolution digital terrain model (DTM) with 1-meter resolution using Hydrology Tools of ArcGIS. The raster was then filled, processed flow direction and accumulation, then raster calculate and provide stream order, converted to vector, and clearing undesirable features using the ancillary or google earth. In field validation streams were classified whether perennial, intermittent or ephemeral. Results show more than 90% of the extracted feature were accurate in assessment through field validation.

Keywords: digital terrain models, hydrology tools, strahler method, stream classification

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Authors: Omonov Jahongir Mahmatkulovic

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Purpose: To study the significance of D-dimer (DD), prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), and fibrinogen coagulation parameters (Fg) in predicting the course, severity and prognosis of COVID-19. Source and method of research: From September 15, 2021, to November 5, 2021, 93 patients aged 25 to 60 with suspected COVID-19, who are under inpatient treatment at the multidisciplinary clinic of the Tashkent Medical Academy, were retrospectively examined. DD, PT, APTT, and Fg were studied in dynamics and studied changes. Results: Coagulation disorders occurred in the early stages of COVID-19 infection with an increase in DD in 54 (58%) patients and an increase in Fg in 93 (100%) patients. DD and Fg levels are associated with the clinical classification. Of the 33 patients who died, 21 had an increase in DD in the first laboratory study, 27 had an increase in DD in the second and third laboratory studies, and 15 had an increase in PT in the third test. The results of the ROC analysis of mortality showed that the AUC DD was three times 0.721, 0.801, and 0.844, respectively; PT was 0.703, 0.845, and 0.972. (P<0:01). Conclusion”: Coagulation dysfunction is more common in patients with severe and critical conditions. DD and PT can be used as important predictors of mortality from COVID-19.

Keywords: Covid19, DD, PT, Coagulogram analysis, APTT

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Authors: Amany Haridy, Ahmed Elseragy, Fahd Omar

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The issue of temperature increase in the urban microclimate has been at the center of attention recently, especially in dense urban areas, such as the City of Alexandria in Egypt, where building surfaces have become the dominant element (more than green areas and streets). Temperatures have been rising during daytime as well as nighttime, however, the research focused on the rise of air temperature at night, a phenomenon known as the urban heat island. This phenomenon has many effects on ecological life, as well as human health. This study provided evidence of the possibility of reducing the urban heat island by using a green building envelope (green wall and green roof) in Alexandria, Egypt. This City has witnessed a boom in growth in its urban fabric and population. A simulation analysis using the Envi-met software to find the ratio of air temperature reduction was performed. The simulation depended on the orientation of the green areas and their density, which was defined through a process of climatic analysis made by the Diva plugin using the Grasshopper software. Results showed that the reduction in air temperature varies from 0.8–2.0 °C, increasing with the increasing density of green areas. Many systems of green wall and green roof can be found in the local market. However, treating an existing building requires a careful choice of system to fit the building construction load and the surrounding nature. Among the systems of choice, there was the ‘geometric system’ of vertical greening that can be fixed on a light aluminum structure for walls and the extensive green system for roofs. Finally, native plants were the best choice in the long term because they fare well in the local climate.

Keywords: envi-met, green building envelope, urban heat island, urban microclimate

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Authors: Kamel Laidi, Khelifa Benmansour, Ouahid Bouchhida

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Neural networks-based approach for 2-cells serial converter has been developed and implemented. The approach is based on a behavioural description of the different operating modes of the converter. Each operating mode represents a well-defined configuration, and for which is matched an operating zone satisfying given invariance conditions, depending on the capacitors' voltages and the load current of the converter. For each mode, a control vector whose components are the control signals to be applied to the converter switches has been associated. Therefore, the problem is reduced to a classification task of the different operating modes of the converter. The artificial neural nets-based approach, which constitutes a powerful tool for this kind of task, has been adopted and implemented. The application to a 2-cells chopper has allowed ensuring efficient and robust control of the load current and a high capacitors voltages balancing.

Keywords: neural nets, control, multicellular converters, 2-cells chopper

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Authors: Emad A. Mohammed

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Utilizing the capabilities of Data Mining and Artificial Intelligence in the prediction of the minimum miscibility pressure (MMP) required for multi-contact miscible (MCM) displacement of reservoir petroleum by hydrocarbon gas flooding using Fuzzy Logic models and Artificial Neural Network models will help a lot in giving accurate results. The factors affecting the (MMP) as it is proved from the literature and from the dataset are as follows: XC2-6: Intermediate composition in the oil-containing C2-6, CO2 and H2S, in mole %, XC1: Amount of methane in the oil (%),T: Temperature (°C), MwC7+: Molecular weight of C7+ (g/mol), YC2+: Mole percent of C2+ composition in injected gas (%), MwC2+: Molecular weight of C2+ in injected gas. Fuzzy Logic and Neural Networks have been used widely in prediction and classification, with relatively high accuracy, in different fields of study. It is well known that the Fuzzy Inference system can handle uncertainty within the inputs such as in our case. The results of this work showed that our proposed models perform better with higher performance indices than other emprical correlations.

Keywords: MMP, gas flooding, artificial intelligence, correlation

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Authors: Arya Farjand

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This study delves into the Early Pleistocene fauna of the Yuanmou Basin, highlighting two significant findings. The first is the discovery of exceptionally well-preserved canid coprolites, which provide a rare glimpse into the diet and ecological niche of these ancient carnivores. The analysis of these coprolites has revealed a diet rich in diverse prey species, suggesting a complex food web and a dynamic ecological environment. This discovery not only sheds light on the dietary habits of these canids but also offers broader insights into the region's ecological dynamics during the Early Pleistocene. Additionally, the preservation of these coprolites allows for detailed study of the carnivore's role in the ecosystem, including their interactions with other species and the overall health of the environment. The second major finding is the identification of a mustelid species, Eirictis yuanmouensis, from the same fossil horizon as the coprolites. This discovery is crucial for understanding the diversity and evolution of Mustelidae in the region. The detailed analysis of cranial and dental morphology of Eirictis yuanmouensis indicates unique adaptations that suggest a specialized ecological niche. This finding, in conjunction with the coprolite analysis, provides a comprehensive view of the ecological niches occupied by both mustelids and hyenas, enhancing our understanding of their adaptations and interactions within this paleoenvironment. The study's significance is further amplified by the analysis of pollen data from the same horizon, which indicates a paleoenvironment characterized by rapid climatic changes and a dominant semiarid climate. This combination of faunal and floral data paints a detailed picture of the Early Pleistocene environment in the Yuanmou Basin, offering valuable insights into the interactions between different carnivore species and their adaptation strategies in response to changing environmental conditions.

Keywords: Yuanmou Basin, coprolite, Hyaena, eirictis yuanmouensis, early pleistocene

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Authors: Claudia Pimentel, Nuno Resende, Maria Fatima Lambert

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In the present time, catastrophe seems to be inevitable, and individuals are permanently overwhelmed with challenges that test one’s ability to cope with reality. Undoubtedly, photography surpassed the barrier of efficient communication in a world filled with omnifarious narratives. It wandered an outing shorter than words and younger than other sciences but became, nowadays, imperative in the context of several fields of knowledge, namely Heritage studies. Heritage and photography thus emerge as unapologetically related concepts, a fact that makes them equally relevant in today's society. Political, economic, social and humanitarian challenges alter the way in which the relationship with the past is managed and the way in which identities and ideas for the future are constructed. Ruins and destruction have become part of aesthetics discourse since the 18th century and are an area of interest when we discuss cultural heritage preservation. The image proves to be a unique way of revealing the event details when we refer to a catastrophic situation, whether it be anthropic, social or climatic. Like poetry, which has a challenging connection with silence, image is capable of creating spaces of sound and silence, and it is often these “pseudo-voids” that capture the attention of the spectator, of the one who sees/observes/contacts with the photography. The way we look at the catastrophe, how we describe it, and the images we keep in our memory will determine the record/capture/news of the event. We, thus, have a visual record, a document that will contribute to the creation of individual and collective identity, in a jigsaw puzzle of memories, pseudo memories and post memories. Based on photographic records in the Portuguese press, we intend to rethink the earthquake at Angra do Heroísmo – Azores in 1980, exploring the viewer´s perspective on the catastrophe’s iconography under the perspective of aesthetics and genealogy of the catastrophe.

Keywords: photography, aesthetics, catastrophe, Portugal

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Authors: Mercedes Bertotto, Marcelo Bello, Hector Goicoechea, Veronica Fusca

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The National Service of Agri-Food Health and Quality (SENASA), controls honey to detect contamination by synthetic or natural chemical substances and establishes and controls the traceability of the product. The utility of near-infrared spectroscopy for the detection of adulteration of honey with high fructose corn syrup (HFCS) was investigated. First of all, a mixture of different authentic artisanal Argentinian honey was prepared to cover as much heterogeneity as possible. Then, mixtures were prepared by adding different concentrations of high fructose corn syrup (HFCS) to samples of the honey pool. 237 samples were used, 108 of them were authentic honey and 129 samples corresponded to honey adulterated with HFCS between 1 and 10%. They were stored unrefrigerated from time of production until scanning and were not filtered after receipt in the laboratory. Immediately prior to spectral collection, honey was incubated at 40°C overnight to dissolve any crystalline material, manually stirred to achieve homogeneity and adjusted to a standard solids content (70° Brix) with distilled water. Adulterant solutions were also adjusted to 70° Brix. Samples were measured by NIR spectroscopy in the range of 650 to 7000 cm⁻¹. The technique of specular reflectance was used, with a lens aperture range of 150 mm. Pretreatment of the spectra was performed by Standard Normal Variate (SNV). The ant colony optimization genetic algorithm sample selection (ACOGASS) graphical interface was used, using MATLAB version 5.3, to select the variables with the greatest discriminating power. The data set was divided into a validation set and a calibration set, using the Kennard-Stone (KS) algorithm. A combined method of Potential Functions (PF) was chosen together with Partial Least Square Linear Discriminant Analysis (PLS-DA). Different estimators of the predictive capacity of the model were compared, which were obtained using a decreasing number of groups, which implies more demanding validation conditions. The optimal number of latent variables was selected as the number associated with the minimum error and the smallest number of unassigned samples. Once the optimal number of latent variables was defined, we proceeded to apply the model to the training samples. With the calibrated model for the training samples, we proceeded to study the validation samples. The calibrated model that combines the potential function methods and PLSDA can be considered reliable and stable since its performance in future samples is expected to be comparable to that achieved for the training samples. By use of Potential Functions (PF) and Partial Least Square Linear Discriminant Analysis (PLS-DA) classification, authentic honey and honey adulterated with HFCS could be identified with a correct classification rate of 97.9%. The results showed that NIR in combination with the PT and PLS-DS methods can be a simple, fast and low-cost technique for the detection of HFCS in honey with high sensitivity and power of discrimination.

Keywords: adulteration, multivariate analysis, potential functions, regression

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Authors: Md. Obidul Haque, Abbasi Khanm

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Port city Chittagong, the commercial capital of Bangladesh, is flourished with fascinating topography and climatic context along with basic resources for livelihood; both shape this city and become living archives of its ecologies. Chittagong has been witnessing numerous urban development measures being taken by city development authority, though some of those seem incomplete because of lack of proper planning. Due to this unplanned trail, the blessings of nature have become the reason of sufferings for city dwellers. One of which is the water clogging due to heavy rainfall, seepage, high tide, absence of well-knit underground drainage system, and so on. The problem has reached such an extent that the first monsoon rain is enough to shut down the entire city and causing immense sufferings to livestock, specially most vulnerable groups such as children and office going people. Study shows that total discharge is higher than present drainage capacity of the canals, thus, resulting in overflow, as major channels are clogged up by dumping waste or illegal encroachment, which are supposed to flush out rain water. This paper aims to address natural and manmade causes behind urban water clogging, adverse socio-environmental hazardous effects, possibilities for probable solutions on basis of local people’s experience and rational urban planning and landscape architectural proposals such as facilitating well planned drainage system, along with waste management policies etc. which can be able to intervene in these movements to activate the mighty port city’s unfulfilled potentials.

Keywords: drainage, high-tide, urban storm water logging (USWL), urban planning, water management

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Authors: Haojie Wang, Xun Li, Rui Yin

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In order to solve the memorization overfitting in the meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels, so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to exponential growth of computation, this paper also proposes a key data extraction method, that only extracts part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: data augmentation, mutex task generation, meta-learning, text classification.

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Authors: Vesna Pungercar, Florian Musso

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Identifying materials that can substitute rare or expensive natural resources is one of the key challenges for improving resource efficiency in the building sector. With a growing world population and rising living standards, more and more salt is produced as waste through seawater desalination and potash mining processes. Unfortunately, most of the salt is directly disposed of into nature, where it causes environmental pollution. On the other hand, salt is affordable, is used therapeutically in various respiratory treatments, and can store humidity and heat. It was, therefore, necessary to determine salt materials already in use in building construction and their hygrothermal properties. This research aims to identify salt materials from different scientific branches and historically, to investigate their properties and prioritize the most promising salt materials for indoor applications in a thermal envelope. This was realized through literature review and classification of salt materials into three groups (raw salt materials, composite salt materials, and processed salt materials). The outcome of this research shows that salt has already been used as a building material for centuries and has a potential for future applications due to its hygrothermal properties in a thermal envelope.

Keywords: salt, building material, hygrothermal properties, environment

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Authors: Milad Mirzaei Aminiyan, Abdolreza Akhgar, Farzad Mirzaei Aminiyan

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Water quality is the critical factor that influence on human health and quantity and quality of grain production in semi-humid and semi-arid area. Pistachio is a main crop that accounts for a considerable portion of Iranian agricultural exports. Give that pistachio tree is a tolerant type of tree to saline and alkaline soil and water conditions, but groundwater and irrigation water quality play important roles in main production this crop. For this purpose, 94 well water samples were taken from 25 wells and samples were analyzed. The results showed give that region’s geological, climatic characteristics, statistical analysis, and based on dominant cations and anions in well water samples (piper diagram); four main types of water were found: Na-Cl, K-Cl, Na-SO4, and K-SO4. It seems that most wells in terms of water quality (salinity and alkalinity) and based on Wilcox diagram have critical status. The analysis suggested that more than eighty-seven percentage of the well water samples have high values of EC that these values are higher than into critical limit EC value for irrigation water, which may be due to the sandy soils in this area. Most groundwater were relatively unsuitable for irrigation but it could be used by application of correct management such as removing and reducing the ion concentrations of Cl‾, SO42‾, Na+ and total hardness in groundwater and also the concentrated deep groundwater was required treatment to reduce the salinity and sodium hazard. Given that irrigation water quality in this area was relatively unsuitable for most agriculture production but pistachio tree was adapted to this area conditions. The integrated management of groundwater for irrigation is the way to solve water quality issues not only in Rafsanjan area, but also in other arid and semi-arid areas.

Keywords: groundwater quality, irrigation water quality, salinity, alkalinity, Rafsanjan plain, pistachio

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Authors: Dalwinder Singh, Amandeep Verma, Manpreet Kaur, Birmohan Singh

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The detection of pre-cancerous changes using a Pap smear test of cervical cell is the important step for the early diagnosis of cervical cancer. The Pap smear test consists of a sample of human cells taken from the cervix which are analysed to detect cancerous and pre-cancerous stage of the given subject. The manual analysis of these cells is labor intensive and time consuming process which relies on expert cytotechnologist. In this paper, a computer assisted system for the automated analysis of the cervical cells has been proposed. We propose a morphology based approach to the nucleus detection and segmentation of the cytoplasmic region of the given single or multiple overlapped cell. Further, various texture and region based features are calculated from these cells to classify these into normal and abnormal cell. Experimental results on public available dataset show that our system has achieved satisfactory success rate.

Keywords: cervical cancer, cervical tissue, mathematical morphology, texture features

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Authors: Levent Basayigit, Mert Dedeoglu, Fadime Ozogul

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In this study, an application was carried out to determine the Volcanic Soils by using remote sensing.  The study area was located on the Golcuk formation in Isparta-Turkey. The thermal bands of Landsat 7 image were used for processing. The implementation of the climate model that was based on the water index was used in ERDAS Imagine software together with pixel based image classification. Soil Moisture Index (SMI) was modeled by using the surface temperature (Ts) which was obtained from thermal bands and vegetation index (NDVI) derived from Landsat 7. Surface moisture values were grouped and classified by using scoring system. Thematic layers were compared together with the field studies. Consequently, different moisture levels for volcanic soils were indicator for determination and separation. Those thermal wavelengths are preferable bands for separation of volcanic soils using moisture and temperature models.

Keywords: Landsat 7, soil moisture index, temperature models, volcanic soils

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Authors: Fereshteh M. Haskouei, Habib Alimohammadian

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Magnetic susceptibility (χ) is operational to identify of late quaternary glacial-interglacial cycles in loess-paleosol sequences. It is well accepted that many loess-paleosol sequences bear witness to cold-dry/warm-humid periods, well known as glacial-interglacial cycles, respectively. For this study, loess-paleosol sequence of north-east of Iran was magnetically investigated. The study area is situated at about 8 km away of Neka city, on the main road of Sari-Behshahr, in Mazandaran Province, north of Iran. The youngest deposits of study area are the late Quaternary wind-blown accumulations. In this study, the total number of 117 samples was collected from loess-paleosols units. After that, the natural remnant magnetization (NRM) and magnetic susceptibility (MS) of the samples were measured. Variation of MS of more than 110 loess samples was plotted to reveal the correlation of the MS and paleoclimatic changes. This study aims reconstruction of climatic changes (glacial-interglacial and stadials-interstadials cycles). To confirm our results we compared MS (χ) and the curves of other investigations in paleoclimatology. This correspondence abled us to recognize worldly events in the study area such as: Younger Dryas, the Last Glacial Maximum (LGM), deglaciation of Northern Hemisphere etc. The obtained magnetic data indicate that during almost 50 ka, at least two glacial-interglacial periods occurred in north-east of Iran. Further, variation of χ values revealed short period of climatically cycles known as stadials-interstadials. We recognized 4 stadials and a single stadial as colder sub-periods for S₀ (recently soil-paleosol) and S₂ (lower paleosol), respectively, Moreover, we recognized 6 warmer sub-periods (interstadials) for L₁ (upper loess) and one interstadial L₂ (lower loess).

Keywords: glacial-interglacial cycles, Iran, last glacial maximum (LGM), loess, magnetic susceptibility (χ), Neka, stadials-interstadials sub-periods, younger dryas

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Authors: Wahab Ali, Oyebade K. Oyedotun, Adnan Khashman

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Breast cancer remains a threat to the woman’s world in view of survival rates, it early diagnosis and mortality statistics. So far, research has shown that many survivors of breast cancer cases are in the ones with early diagnosis. Breast cancer is usually categorized into stages which indicates its severity and corresponding survival rates for patients. Investigations show that the farther into the stages before diagnosis the lesser the chance of survival; hence the early diagnosis of breast cancer becomes imperative, and consequently the application of novel technologies to achieving this. Over the year, mammograms have used in the diagnosis of breast cancer, but the inconclusive deductions made from such scans lead to either false negative cases where cancer patients may be left untreated or false positive where unnecessary biopsies are carried out. This paper presents the application of artificial neural networks in the prediction of severity of breast tumour (whether benign or malignant) using mammography reports and other factors that are related to breast cancer.

Keywords: breast cancer, intelligent classification, neural networks, mammography

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Authors: B. Niez, B. Moulia, J. Dlouha, E. Badel

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Trees adjust their development to the environmental conditions they experience. Storms events of last decades showed that acclimation of trees to mechanical stresses due to wind is a very important process that allows the trees to sustain for long years. In the future, trees will experience new wind patterns, namely, more often strong winds and fewer daily moderate winds. Moreover, these patterns will go along with drought periods that may interact with the capacity of trees to adjust their growth to mechanical stresses due to wind. It is necessary to understand the mechanisms of wood functional acclimations to environmental conditions in order to predict their behaviour and in order to give foresters and breeders the relevant tools to adapt their forest management. This work aims to study how trees adjust the mechanical and hydraulic functions of their wood to environmental stresses and how this acclimation may be beneficial for the tree to resist to future stresses. In this work, young poplars were grown under controlled climatic conditions that include permanent environmental stress (daily mechanical stress of the stem by bending and/or hydric stress). Then, the properties of wood formed under these stressed conditions were characterized. First, hydraulic conductivity and sensibility to cavitation were measured at the tissue level in order to evaluate the changes in water transport capacity. Secondly, bending tests and Charpy impact tests were carried out at the millimetric scale to locally measure mechanical parameters such as elastic modulus, elastic limit or rupture energy. These experimental data allow evaluating the impacts of mechanical and water stress on the wood material. At the stem level, they will be merged in an integrative model in order to evaluate the beneficial aspect of wood acclimation for trees.

Keywords: acclimation, environmental stresses, hydraulics, mechanics, wood

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Authors: Lakhminandan Kakati, Merenjungla Jamir

Abstract:

Rearing of six strains of Samia ricini (eri silk worm) i.e. Yellow plain (YP), Yellow spotted (YS), Yellow Zebra (YZ), Greenish blue plain (GBP), Greenish blue spotted (GBS) and Greenish blue zebra (GBZ) was conducted on Ricinus communis (Castor), Heteropanax fragrans (Kesseru), Evodia fraxinifolia (Payam) and Manihot utilissima (Tapioca) to evaluate the effect of seasonal pattern on larval duration and cocoon parameters in Nagaland, India. Larval duration during spring season was maximum in all strains in all food plants; however minimum for all strains was recorded during summer season on Castor, Kesseru and Tapioca. Cocoon weight was recorded to be minimum (2.8 ± 2 0.55 gm) in YP on Kesseru and maximum (4.06 ± 0.68 gm) in GBZ on Castor during spring season; shell weight fluctuated between 0.34 ± 0.08 gm during spring in GBS on Kesseru and 0.58 ± 0.09 gm during summer in YZ on Castor and percentage of silk ratio was found to be minimum and maximum in YP on Payam during spring (11.37 ± 1.29) and in GBS on Castor during summer (16.05 ± 1.59) respectively. The variation in larval duration and cocoon parameters reflected variation in nutrient composition of food plants and dynamic environment conditions prevailing in different seasons of the year. Payam and Tapioca plants could be fed either singly or alternately with Castor or Kesseru to attain the commercial advantage to ensure more value added production. While there were differences in the productivity parameters with respect to strains and seasons, the present study shows that all the strains on four host plants expressed adaptability and suitability for commercial rearing under Nagaland climatic condition.

Keywords: alternative food plants, Larval and cocoon parameters, Nagaland Inia, six strains of Samia ricini

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Authors: Laxmi Versain, R. S. Banshtu

Abstract:

Landslides are found to be the most commonly occurring geological hazards in the mountainous regions of the Himalaya. This mountainous zone is facing large number of seismic turbulences, climatic changes, and topography changes due to increasing urbanization. That eventually has lead several researchers working for best suitable methodologies to infer the ultimate results. Landslide Hazard Zonation has widely come as suitable method to know the appropriate factors that trigger the lansdslide phenomenon on higher reaches. Most vulnerable zones or zones of weaknesses are indentified and safe mitigation measures are to be suggested to mitigate and channelize the study of an effected area. Use of Landslide Hazard Zonation methodology in relative zones of weaknesses depend upon the data available for the particular site. The causative factors are identified and data is made available to infer the results. Factors like seismicity in mountainous region have closely associated to make the zones of thrust and faults or lineaments more vulnerable. Data related to soil, terrain, rainfall, geology, slope, nature of terrain, are found to be varied for various landforms and areas. Thus, the relative causes are to be identified and classified by giving specific weightage to each parameter. Factors which cause the instability of slopes are several and can be grouped to infer the potential modes of failure. The triggering factors of the landslides on the mountains are not uniform. The urbanization has crawled like ladder and emergence of concrete jungles are in a very fast pace on hilly region of Himalayas. The local terrains has largely been modified and hence instability of several zones are triggering at very fast pace. More strategic and pronounced methods are required to reduce the effect of landslide.

Keywords: zonation, LHZ, susceptible, weightages, methodology

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Authors: A. H. Nanher, N. P. Singh

Abstract:

In India, Agriculture is largely in rice- based cropping system. It has indicated decline in factor productivity along with emergence of multi - nutrient deficiency, buildup of soil pathogen and weed flora because it operates and removes nutrients from the same rooting depth. In designing alternative cropping systems, the common approaches are crop intensification, crop diversification and cultivar options. The intensification leads to the diversification of the cropping system. Intensification is achieved by introducing an additional component crop in a pre-dominant sequential system by desirable adjustments in cultivars of one or all the component crops. Invariably, this results in higher land use efficiency and productivity per unit time Crop Diversification through such crop and inclusion of fodder crops help to improve the economic situation of small and marginal farmers because of higher income. Inclusion of crops in sequential and intercropping systems reduces some obnoxious weeds through formation of canopies due to competitive planting pattern and thus provides an opportunity to utilize cropping systems as a tool of weed management with non-chemical means. Use of organic source not only acts as supplement for fertilizer (nitrogen) but also improve the physico-chemical properties of soils. Production and use of nitrogen rich biomass offer better prospect for supplementing chemical fertilizers on regular basis. Such biological diversity brings yield and economic stability because of its potential for compensation among components of the system. In a particular agro-climatic and resource condition, the identification of most suitable crop sequence is based on its productivity, stability, land use efficiency as well as production efficiency and its performance is chiefly judged in terms of productivity and net return.

Keywords: integrated farming systems, sustainable intensification, system of crop intensification, wheat

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Authors: Aleksandra Jonas, Aleksandra Gronowska, Maciej Ścigacz, Szymon Jadczak

Abstract:

Exact Data is a smart tool which helps with meaningful marketing content creation. It helps marketers achieve this by analyzing the text of an advertisement before and after its publication on social media sites like Facebook or Instagram. In our research we focus on four areas of natural language processing (NLP): grammar correction, sentiment analysis, irony detection and advertisement interpretation. Our research has identified a considerable lack of NLP tools for the Polish language, which specifically aid online marketers. In light of this, our research team has set out to create a robust and versatile NLP tool for the Polish language. The primary objective of our research is to develop a tool that can perform a range of language processing tasks in this language, such as sentiment analysis, text classification, text correction and text interpretation. Our team has been working diligently to create a tool that is accurate, reliable, and adaptable to the specific linguistic features of Polish, and that can provide valuable insights for a wide range of marketers needs. In addition to the Polish language version, we are also developing an English version of the tool, which will enable us to expand the reach and impact of our research to a wider audience. Another area of focus in our research involves tackling the challenge of the limited availability of linguistically diverse corpora for non-English languages, which presents a significant barrier in the development of NLP applications. One approach we have been pursuing is the translation of existing English corpora, which would enable us to use the wealth of linguistic resources available in English for other languages. Furthermore, we are looking into other methods, such as gathering language samples from social media platforms. By analyzing the language used in social media posts, we can collect a wide range of data that reflects the unique linguistic characteristics of specific regions and communities, which can then be used to enhance the accuracy and performance of NLP algorithms for non-English languages. In doing so, we hope to broaden the scope and capabilities of NLP applications. Our research focuses on several key NLP techniques including sentiment analysis, text classification, text interpretation and text correction. To ensure that we can achieve the best possible performance for these techniques, we are evaluating and comparing different approaches and strategies for implementing them. We are exploring a range of different methods, including transformers and convolutional neural networks (CNNs), to determine which ones are most effective for different types of NLP tasks. By analyzing the strengths and weaknesses of each approach, we can identify the most effective techniques for specific use cases, and further enhance the performance of our tool. Our research aims to create a tool, which can provide a comprehensive analysis of advertising effectiveness, allowing marketers to identify areas for improvement and optimize their advertising strategies. The results of this study suggest that a smart tool for advertisement analysis can provide valuable insights for businesses seeking to create effective advertising campaigns.

Keywords: NLP, AI, IT, language, marketing, analysis

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Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

Abstract:

Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

Procedia PDF Downloads 116