Search results for: satellite imagery classification

Authors: Thel Phyu Phyu Soe

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Myanmar started its new political movement in 2011, opening up to trade, encouraging foreign investment, deepening its financial sectors. The tourism is one of the key sectors to make reform process from the perspective of green economy and green growth. The Inle Lake, second largest lake, famous for broad diversity of cultural and natural assets, become one of the country’s main tourism destination. In the study area, local livelihoods are based on a combination of farming (mainly floating garden) wage labor, tourism, and small business. But the Inle lake water body or water surface area decreased by 96.44 km² within 20 years, from 67.98 km² in 1990 to 56.63 km² in 2010. Floating garden cultivation (hydro phonic farm) is a distinguished characteristic of Inle Lake. Two adjacent villages (A and B) were selected to compare the relationship between tourism access and agricultural production. Ground truthing, focus group discussion, and in-depth questionnaires with floating gardeners were carried out. In A village, 57% of the respondents relied tourism as their major income sources, while almost all the households in B village relied floating gardens as major livelihood. Both satellite image interpretation and community studies highlighted that around 80% of the floating garden become fallow after severe drought in 2010 and easy income access to tourism related activities. The villagers can get 20-30 US$ for round trip guiding to major tourist attraction places.Even though tourism is the major livelihood options for the A village, the poorest households (less than 1500 US$ per year) are those who didn’t own transportation property for tourism related activities. In B village, more than 70% of the households relied floating gardens as their major income sources and less participated in tourism related activities because they don’t have motorboat stand connected to the major tourist attraction areas. Access to tourism related activities (having boat stand where they can guide tourists by boat and sell local products and souvenirs) have much impacted on changes in local people livelihood options. However, tourism may have impacts that are beneficial for one group of a society, but which are negative for another. Income inequality and negative impacts can only be managed effectively if they have been identified, measured and evaluated. The severe drought in 2010, instability of lake water level, high expenses for agriculture assisted the local people to participate in easy access tourism related activities.

Keywords: diminishing, floating garden, livelihood, tourism-related income

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Authors: Yagahira E. Castro-Sesquen, Chloe Kim, Robert H. Gilman, David J. Sullivan, Peter C. Searson

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Diagnosis of severe malaria is particularly important in highly endemic regions since most patients are positive for parasitemia and treatment differs from non-severe malaria. Diagnosis can be challenging due to the prevalence of diseases with similar symptoms. Accurate diagnosis is increasingly important to avoid overprescribing antimalarial drugs, minimize drug resistance, and minimize costs. A nanoparticle-based assay for detection and quantification of Plasmodium falciparum histidine-rich protein 2 (HRP2) in urine and serum is reported. The assay uses magnetic beads conjugated with anti-HRP2 antibody for protein capture and concentration, and antibody-conjugated quantum dots for optical detection. Western Blot analysis demonstrated that magnetic beads allows the concentration of HRP2 protein in urine by 20-fold. The concentration effect was achieved because large volume of urine can be incubated with beads, and magnetic separation can be easily performed in minutes to isolate beads containing HRP2 protein. Magnetic beads and Quantum Dots 525 conjugated to anti-HRP2 antibodies allows the detection of low concentration of HRP2 protein (0.5 ng mL-1), and quantification in the range of 33 to 2,000 ng mL-1 corresponding to the range associated with non-severe to severe malaria. This assay can be easily adapted to a non-invasive point-of-care test for classification of severe malaria.

Keywords: HRP2 protein, malaria, magnetic beads, Quantum dots

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Authors: Goodness Onwuka, Khaled Abou-El-Hossein

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Borosilicate-crown (BK7) glass has found broad application in the optic and automotive industries and the growing demands for nanometric surface finishes is becoming a necessity in such applications. Thus, it has become paramount to optimize the parameters influencing the surface roughness of this precision lens. The research was carried out on a 4-axes Nanoform 250 precision lathe machine with an ultra-high precision grinding spindle. The experiment varied the machining parameters of feed rate, wheel speed and depth of cut at three levels for different combinations using Box Behnken design of experiment and the resulting surface roughness values were measured using a Taylor Hobson Dimension XL optical profiler. Acoustic emission monitoring technique was applied at a high sampling rate to monitor the machining process while further signal processing and feature extraction methods were implemented to generate the input to a neural network algorithm. This paper highlights the training and development of a back propagation neural network prediction algorithm through careful selection of parameters and the result show a better classification accuracy when compared to a previously developed response surface model with very similar machining parameters. Hence artificial neural network algorithms provide better surface roughness prediction accuracy in the ultra-high precision grinding of BK7 glass.

Keywords: acoustic emission technique, artificial neural network, surface roughness, ultra-high precision grinding

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Authors: Nabat Gojaeva, Mikayil Naghiyev, Sultan Jafarov, Gular Mikayilova

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Chovdar ore area is located in the contact of Dashkesan caldera and Shamkir horst-graben uplift, which comprises the central part of Lok-Karabakh Island arcs of South Caucasus metallogenic province in terms of regional tectonics. One of the main structural features of formation of the Mereh and Aghyokhush group of low sulfidation epithermal gold deposits, locating in the north peripheric part of the ore area, is involving the crossing areas of ore-hosting and ore-forming Pan-Caucasian-direction structurally-compound faults with the meridional, rhombically shaped faults. In addition, another significant feature is the temporally two- or three-stage ore formation. In the first stage -an early phase of Upper Bathonian age, sulfides are the dominant minerals, in the second stage- late ‘productive’ phase of Upper Bathonian age, mainly gold mineralization is formed. Also, in the Upper Jurassic – Lower Cretaceous ages, rarely-encountered Cu-polymetallic ore formations are documented. Finally, in the last stage, the re-dislocation of ore-formation is foreseen in the previously-formed mineralization areas. The faults in the strike and dip directions formed shearing, brecciation, sulfide mineralization aureoles, and hydrothermal alteration zones in the wall rocks along with the local depression blocks. The geological-structural analysis of the area shows that multiple and various morphogenetic volcano-tectonically fault systems have developed in the area. These fault systems have played a trap role for ore-formation in the intersected parts of faults mentioned above. Thus, in the referred parts, mostly predominance of felsic volcanism and metasomatic alteration (silicification, argillitic, etc.) of wall rocks, as well as the products of this volcanism, account for the inclusion of hydrothermal ore-forming fluids along these faults. It is possible to determine temporally and lithological-structural connection between the ore-formation along with local depression blocks and faults as borders for products of felsic volcanism of Upper Cretaceous-Lesser Jurassic ages, in the results of the replacement of hydrothermal alteration zones with relatively low-temperature metasomatic alterations while moving from the felsic parts to the margins, and due to being non-ore bearing intermediate and intermediate-felsic magmatic facies.

Keywords: Aghyokhush, fault, gold deposit, Mereh

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Authors: S. Shankar Bharathi

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Inspection of surface defects on metallic components has always been challenging due to its specular property. Occurrences of defects such as scratches, rust, pitting are very common in metallic surfaces during the manufacturing process. These defects if unchecked can hamper the performance and reduce the life time of such component. Many of the conventional image processing algorithms in detecting the surface defects generally involve segmentation techniques, based on thresholding, edge detection, watershed segmentation and textural segmentation. They later employ other suitable algorithms based on morphology, region growing, shape analysis, neural networks for classification purpose. In this paper the work has been focused only towards detecting scratches. Global and other thresholding techniques were used to extract the defects, but it proved to be inaccurate in extracting the defects alone. However, this paper does not focus on comparison of different segmentation techniques, but rather describes a novel approach towards segmentation combined with hausdorff dilation distance. The proposed algorithm is based on the distribution of the intensity levels, that is, whether a certain gray level is concentrated or evenly distributed. The algorithm is based on extraction of such concentrated pixels. Defective images showed higher level of concentration of some gray level, whereas in non-defective image, there seemed to be no concentration, but were evenly distributed. This formed the basis in detecting the defects in the proposed algorithm. Hausdorff dilation distance based on mathematical morphology was used to strengthen the segmentation of the defects.

Keywords: metallic surface, scratches, segmentation, hausdorff dilation distance, machine vision

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Authors: Mehwish Asghar

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Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.

Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence

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Authors: Vesna Bosilj Vukšić, Lucija Ivančić, Dalia Suša Vugec

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While struggling to succeed in today’s complex market environment and provide better customer experience and services, enterprises encompass digital transformation as a means for reaching competitiveness and foster value creation. A digital transformation process consists of information technology implementation projects, as well as organizational factors such as top management support, digital transformation strategy, and organizational changes. However, to the best of our knowledge, there is little evidence about digital transformation endeavors in organizations and how they perceive it – is it only about digital technologies adoption or a true organizational shift is needed? In order to address this issue and as the first step in our research project, a literature review is conducted. The analysis included case study papers from Scopus and Web of Science databases. The following attributes are considered for classification and analysis of papers: time component; country of case origin; case industry and; digital transformation concept comprehension, i.e. focus. Research showed that organizations – public, as well as private ones, are aware of change necessity and employ digital transformation projects. Also, the changes concerning digital transformation affect both manufacturing and service-based industries. Furthermore, we discovered that organizations understand that besides technologies implementation, organizational changes must also be adopted. However, with only 29 relevant papers identified, research positioned digital transformation as an unexplored and emerging phenomenon in information systems research. The scarcity of evidence-based papers calls for further examination of this topic on cases from practice.

Keywords: digital strategy, digital technologies, digital transformation, literature review

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Authors: Taleb Odeh, Nizar Abu-Jaber, Nour Khries

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The southern part of Wadi Al Yarmouk catchment area covers north of Jordan. It locates within latitudes 32° 20’ to 32° 45’N and longitudes 35° 42’ to 36° 23’ E and has an area of about 1426 km2. However, it has high relief topography where the elevation varies between 50 to 1100 meter above sea level. The variations in the topography causes different units of landforms, climatic zones, land covers and plant species. As a results of these different landscapes units exists in that region. Spatial planning is a major challenge in such a vital area for Jordan which could not be achieved without determining landscape units. However, an integrated approach of remote sensing and geographic information Systems (GIS) is an optimized tool to investigate and map landscape units of such a complicated area. Remote sensing has the capability to collect different land surface data, of large landscape areas, accurately and in different time periods. GIS has the ability of storage these land surface data, analyzing them spatially and present them in form of professional maps. We generated a geo-land surface data that include land cover, rock units, soil units, plant species and digital elevation model using ASTER image and Google Earth while analyzing geo-data spatially were done by ArcGIS 10.2 software. We found that there are twenty two different landscape units in the study area which they have to be considered for any spatial planning in order to avoid and environmental problems.

Keywords: landscape, spatial planning, GIS, spatial analysis, remote sensing

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Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

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Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: computer-aided system, detection, image segmentation, morphology

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Authors: P. Akbartehrani, M. Khaledi Pour, M. Amini, M. Khani, M. Mohajeri Tehrani, E. Ghasemi, P. Charipoor, B. Shokri

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A common problem between diabetic patients is foot ulcers which are chronic and require specialized treatment. Previous studies illustrate that Cold atmospheric plasma (CAP) has beneficial effects on wound healing and infection. Nevertheless, the comparison of different cap exposure protocols in diabetic ulcer wound healing remained to be studied. This study aims to determine the effect of two different exposure protocols on wound healing in diabetic ulcers. A prospective, randomized clinical trial was conducted at two clinics. Diabetic patients with G1 and G2 wanger classification diabetic foot ulcers were divided into two groups of study. One group was treated by the first protocol, which was treating wounds by argon-generated cold atmospheric plasma jet once a week for five weeks in a row. The other group was treated by the second protocol, which was treating wounds every three days for five weeks in a row. The wounds were treated for 40 seconds/cubic centimeter, while the nozzle tip was moved nonlocalized 1 cm above the wounds. A patient with one or more wounds could participate in different groups as wounds were separately randomized, which allow a participant to be treated several times during the study. The study's significant findings were two different reductions rate in wound size, microbial load, and two different healing speeds. This study concludes that CAP therapy by the second protocol yields more effective healing speeds, reduction in wound sizes, and microbial loads of foot ulcers in diabetic patients.

Keywords: wound healing, diabetic ulcers, cold atmospheric plasma, cold argon jet

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Authors: Filipa Cortez, Vanessa Pereira

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Introduction: The main challenge of obesity treatment is long-term weight loss maintenance. The 3 phases method is a weight loss program that combines a low carb and moderately high-protein diet, food supplements and a weekly one-to-one consultation with a certified nutritionist. Sustained weight control is the ultimate goal of phase 3. Success criterion was the minimum loss of 10% of initial weight and its maintenance after 12 months. Objective: The aim of this study was to identify factors associated with successful weight loss maintenance after 12 months at the end of 3 phases method. Methods: The study included 199 subjects that achieved their weight loss goal (phase 3). Weight and body mass index (BMI) were obtained at the baseline and every week until the end of the program. Therapeutic adherence was measured weekly on a Likert scale from 1 to 5. Subjects were considered in compliance with nutritional recommendation and supplementation when their classification was ≥ 4. After 12 months of the method, the current weight and number of previous weight-loss attempts were collected by telephone interview. The statistical significance was assumed at p-values < 0.05. Statistical analyses were performed using SPSS TM software v.21. Results: 65.3% of subjects met the success criterion. The factors which displayed a significant weight loss maintenance prediction were: greater initial percentage weight loss (OR=1.44) during the weight loss intervention and a higher number of consultations in phase 3 (OR=1.10). Conclusion: These findings suggest that the percentage weight loss during the weight loss intervention and the number of consultations in phase 3 may facilitate maintenance of weight loss after the 3 phases method.

Keywords: obesity, weight maintenance, low-carbohydrate diet, dietary supplements

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Authors: Nasreen Basoudan, Andrea Tales, Frederic Boy

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Non-clinical anxiety may be comprised of state anxiety - temporarily experienced anxiety related to a specific situation, and trait anxiety - a longer lasting response or a general disposition to anxiety. While temporary and occasional anxiety whether as a mood state or personality dimension is normal, nonclinical anxiety may influence many more components of information processing than previously recognized. In ageing and dementia-related research, disease characterization now involves attempts to understand a much wider range of brain function such as loss of inhibitory control, as against the more common focus on memory and cognition. However, in many studies, the tendency has been to include individuals with clinical anxiety disorders while excluding persons with lower levels of state or trait anxiety. Loss of inhibitory cognitive control can lead to behaviors such as aggression, reduced sensitivity to others, sociopathic thoughts and actions. Anxiety has also been linked to inhibitory control, with research suggesting that people with anxiety are less capable of inhibiting their emotions than the average person. This study investigates the relationship between anxiety and loss of inhibitory control in younger and older adults, using a variety of questionnaires and computers-based tests. Based on the premise that irrespective of classification, anxiety is associated with a wide range of physical, affective, and cognitive responses, this study explores evidence indicative of the potential influence anxiety per se on loss of inhibitory control, in order to contribute to discussion and appropriate consideration of anxiety-related factors in methodological practice.

Keywords: anxiety, ageing, dementia, inhibitory control

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Authors: Prabha Rohatgi

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To obtain an efficient control over a huge amount of inventory of drugs in pharmacy department of any hospital, generally, the medicines are categorized on the basis of their cost ‘ABC’ (Always Better Control), first and then categorize on the basis of their criticality ‘VED’ (Vital, Essential, desirable) for prioritization. About one-third of the annual expenditure of a hospital is spent on medicines. To minimize the inventory investment, the hospital management may like to keep the medicines inventory low, as medicines are perishable items. The main aim of each and every hospital is to provide better services to the patients under certain limited resources. To achieve the satisfactory level of health care services to outdoor patients, a hospital has to keep eye on the wastage of medicines because expiry date of medicines causes a great loss of money though it was limited and allocated for a particular period of time. The objectives of this study are to identify the categories of medicines requiring incentive managerial control. In this paper, to minimize the total inventory cost and the cost associated with the wastage of money due to expiry of medicines, an inventory control model is used as an estimation tool and then nonlinear programming technique is used under limited budget and fixed number of orders to be placed in a limited time period. Numerical computations have been given and shown that by using scientific methods in hospital services, we can give more effective way of inventory management under limited resources and can provide better health care services. The secondary data has been collected from a hospital to give empirical evidence.

Keywords: ABC-VED inventory classification, multi item inventory problem, nonlinear programming technique, optimization of EOQ

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Authors: Stephen O. Amiandamhen, Martina Meinken, Luvuyo Tyhoda

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The properties of Hemp (Cannabis sativa) in phosphate bonded composites were investigated in this research. Hemp hurds were collected from the Hemporium institute for research, South Africa. The hurds were air-dried and shredded using a hammer mill. The shives were screened into different particle sizes and were treated separately with 5% solution of acetic anhydride and sodium hydroxide. The binding matrix was prepared using a reactive magnesia, phosphoric acid, class S fly ash and unslaked lime. The treated and untreated hemp fibers were mixed thoroughly in different ratios with the inorganic matrix. Boric acid and excess water were used to retard and control the rate of the reaction and the setting of the binder. The Hemp composite was formed in a rectangular mold and compressed at room temperature at a pressure of 100KPa. After de-molding the composites, they were cured in a conditioning room for 96 h. Physical and mechanical tests were conducted to evaluate the properties of the composites. A central composite design (CCD) was used to determine the best conditions to optimize the performance of the composites. Thereafter, these combinations were applied in the production of the composites, and the properties were evaluated. Scanning electron microscopy (SEM) was used to carry out the advance examination of the behavior of the composites while X-ray diffractometry (XRD) was used to analyze the reaction pathway in the composites. The results revealed that all properties of phosphate bonded Hemp composites exceeded the LD-1 grade classification of particle boards. The proposed product can be used for ceiling, partitioning, wall claddings and underlayment.

Keywords: CCD, fly ash, magnesia, phosphate bonded hemp composites, phosphoric acid, unslaked lime

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Authors: Catalina Sau Man Ng

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Workplace bullying is generally defined as a form of direct and indirect maltreatment at work including harassing, offending, socially isolating someone or negatively affecting someone’s work tasks. Workplace bullying is unfortunately commonplace around the world, which makes it a social phenomenon worth researching. However, the measurements and estimation methods of workplace bullying seem to be diverse in different studies, leading to dubious results. Hence, this paper attempts to examine the prevalence of workplace bullying in Hong Kong using the latent class analysis approach. It is often argued that the traditional classification of workplace bullying into the dichotomous 'victims' and 'non-victims' may not be able to fully represent the complex phenomenon of bullying. By treating workplace bullying as one latent variable and examining the potential categorical distribution within the latent variable, a more thorough understanding of workplace bullying in real-life situations may hence be provided. As a result, this study adopts a latent class analysis method, which was tested to demonstrate higher construct and higher predictive validity previously. In the present study, a representative sample of 2814 employees (Male: 54.7%, Female: 45.3%) in Hong Kong was recruited. The participants were asked to fill in a self-reported questionnaire which included measurements such as Chinese Workplace Bullying Scale (CWBS) and Chinese Version of Depression Anxiety Stress Scale (DASS). It is estimated that four latent classes will emerge: 'non-victims', 'seldom bullied', 'sometimes bullied', and 'victims'. The results of each latent class and implications of the study will also be discussed in this working paper.

Keywords: latent class analysis, prevalence, survey, workplace bullying

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Authors: Rui Liu, Klaus Greve

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The navigation information is a kind of dynamic geographic information, and the navigation information system is a kind of special geographic information system. At present, there are many researches on the application of centralized management and cross-integration application of basic geographic information. However, the idea of information integration and sharing is not deeply applied into the research of navigation information service. And the imperfection of navigation target coordination and navigation information sharing mechanism under certain navigation tasks has greatly affected the reliability and scientificity of navigation service such as path planning. Considering this, the project intends to study the multi-source information fusion and multi-objective united navigation information interaction mechanism: first of all, investigate the actual needs of navigation users in different areas, and establish the preliminary navigation information classification and importance level model; and then analyze the characteristics of the remote sensing and GIS vector data, and design the fusion algorithm from the aspect of improving the positioning accuracy and extracting the navigation environment data. At last, the project intends to analyze the feature of navigation information of the land, sea and air navigation targets, and design the united navigation data standard and navigation information sharing model under certain navigation tasks, and establish a test navigation system for united navigation simulation experiment. The aim of this study is to explore the theory of united navigation service and optimize the navigation information service model, which will lay the theory and technology foundation for the united navigation of land, sea and air targets.

Keywords: information fusion, united navigation, dynamic path planning, navigation information visualization

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Authors: Ivandic Kreso, Spiranec Miljenko, Kavur Boris, Strelec Stjepan

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This article discusses the possibility of using dilatometer tests (DMT) together with in situ seismic tests (MASW) in order to get the shape of G-g degradation curve in cohesive soils (clay, silty clay, silt, clayey silt and sandy silt). MASW test provides the small soil stiffness (G_o from v_s) at very small strains and DMT provides the stiffness of the soil at ‘work strains’ (M_DMT). At different test locations, dilatometer shear stiffness of the soil has been determined by the theory of elasticity. Dilatometer shear stiffness has been compared with the theoretical G-g degradation curve in order to determine the typical range of shear deformation for different types of cohesive soil. The analysis also includes factors that influence the shape of the degradation curve (G-g) and dilatometer modulus (M_DMT), such as the overconsolidation ratio (OCR), plasticity index (IP) and the vertical effective stress in the soil (s_vo'). Parametric study in this article defines the range of shear strain g_DMT and G_DMT/G_o relation depending on the classification of a cohesive soil (clay, silty clay, clayey silt, silt and sandy silt), function of density (loose, medium dense and dense) and the stiffness of the soil (soft, medium hard and hard). The article illustrates the potential of using MASW and DMT to obtain G-g degradation curve in cohesive soils.

Keywords: dilatometer testing, MASW testing, shear wave, soil stiffness, stiffness reduction, shear strain

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Authors: Boualla Nabila

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The increasing demand on water, either for the drinkable water supply, or for the agricultural and industrial custom, requires a very thorough hydrochemical study to protect better and manage this resource. Oran is relatively a city with the worst quality of the water. Recently, the growing populations may put stress on natural waters by impairing the quality of the water. Campaign of water sampling of 55 points capturing different levels of the aquifer system was done for chemical analyzes of nutriments elements. The results allowed us to approach the problem of contamination based on the largely uniform nationwide approach LAWA (LänderarbeitsgruppeWasser), based on the EU CIS guidance, has been applied for the identification of pressures and impacts, allowing for easy comparison. Groundwater samples were analyzed, also, for physico-chemical parameters such as pH, sodium, potassium, calcium, magnesium, chloride, sulphate, carbonate and bicarbonate. The analytical results obtained in this hydrochemistry study were interpreted using Durov diagram. Based on these representations, the anomaly of high groundwater salinity observed in Oran Sebkha basin was explained by the high chloride concentration and to the presence of inverse cation exchange reaction. Durov diagram plot revealed that the groundwater has been evolved from Ca-HCO3 recharge water through mixing with the pre-existing groundwater to give mixed water of Mg-SO4 and Mg-Cl types that eventually reached a final stage of evolution represented by a Na-Cl water type.

Keywords: contamination, water quality, nutrients elements, approach LAWA, durov diagram

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Authors: Mohamed Lotfy, Ghada Soliman

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Recognizing Arabic dot-matrix digits is a challenging problem due to the unique characteristics of dot-matrix fonts, such as irregular dot spacing and varying dot sizes. This paper presents an approach for recognizing Arabic digits printed in dot matrix format. The proposed model is based on Convolutional Neural Networks (CNN) that take the dot matrix as input and generate embeddings that are rounded to generate binary representations of the digits. The binary embeddings are then used to perform Optical Character Recognition (OCR) on the digit images. To overcome the challenge of the limited availability of dotted Arabic expiration date images, we developed a True Type Font (TTF) for generating synthetic images of Arabic dot-matrix characters. The model was trained on a synthetic dataset of 3287 images and 658 synthetic images for testing, representing realistic expiration dates from 2019 to 2027 in the format of yyyy/mm/dd. Our model achieved an accuracy of 98.94% on the expiry date recognition with Arabic dot matrix format using fewer parameters and less computational resources than traditional CNN-based models. By investigating and presenting our findings comprehensively, we aim to contribute substantially to the field of OCR and pave the way for advancements in Arabic dot-matrix character recognition. Our proposed approach is not limited to Arabic dot matrix digit recognition but can also be extended to text recognition tasks, such as text classification and sentiment analysis.

Keywords: computer vision, pattern recognition, optical character recognition, deep learning

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Authors: Reza Talebi

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Wheat (Triticum aestivum) is one of the most important food staples in Iran. Understanding genetic variability among the landrace wheat germplasm is important for breeding. Landraces endemic to Iran are a genetic resource that is distinct from other wheat germplasm. In this study, 60 Iranian landrace wheat accessions were characterized AFLP and ISSR markers. Twelve AFLP primer pairs detected 128 polymorphic bands among the sixty genotypes. The mean polymorphism rate based on AFLP data was 31%; however, a wide polymorphism range among primer pairs was observed (22–40%). Polymorphic information content (PIC value) calculated to assess the informativeness of each marker ranged from 0.28 to 0.4, with a mean of 0.37. According to AFLP molecular data, cluster analysis grouped the genotypes in five distinct clusters. .ISSR markers generated 68 bands (average of 6 bands per primer), which 31 were polymorphic (45%) across the 60 wheat genotypes. Polymorphism information content (PIC) value for ISSR markers was calculated in the range of 0.14 to 0.48 with an average of 0.33. Based on data achieved by ISSR-PCR, cluster analysis grouped the genotypes in three distinct clusters. Both AFLP and ISSR markers able to showed that high level of genetic diversity in Iranian landrace wheat accessions has maintained a relatively constant level of genetic diversity during last years.

Keywords: wheat, genetic diversity, AFLP, ISSR

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Authors: Raluca Popescu, Diana Costinel, Elisabeta-Irina Geana, Oana-Romina Botoran, Roxana-Elena Ionete, Yazan Falah Jadee 'Alabedallat, Mihai Botu

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Walnut production is high in Romania, different varieties being cultivated dependent on high yield, disease resistance or quality of produce. Walnuts have a highly nutritional composition, the kernels containing essential fatty acids, where the unsaturated fraction is higher than in other types of nuts, quinones, tannins, minerals. Walnut consumption can lower the cholesterol, improve the arterial function and reduce inflammation. The purpose of this study is to determine and compare the composition of walnuts of indigenous and international varieties all grown in Romania, in order to identify high-quality indigenous varieties. Oil has been extracted from the nuts of 34 varieties, the fatty acids composition and IV (iodine value) being afterwards measured by NMR. Furthermore, δ13C of the extracted oil had been measured by IRMS to find specific isotopic fingerprints that can be used in authenticating the varieties. Chemometrics had been applied to the data in order to identify similarities and differences between the varieties. The total saturated fatty acids content (SFA) varied between n.d. and 23% molar, oleic acid between 17 and 35%, linoleic acid between 38 and 59%, linolenic acid between 8 and 14%, corresponding to iodine values (IV - total amount of unsaturation) ranging from 100 to 135. The varieties separated in four groups according to the fatty acids composition, each group containing an international variety, making possible the classification of the indigenous ones. At both ends of the unsaturation spectrum, international varieties had been found.

Keywords: δ13C-IRMS, fatty acids composition, 1H-NMR, walnut varieties

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Authors: Ru-Yin Yang, Chi Wu, Cheng-Yu Tsai, Yin-Tzu Lin, Wen-Te Liu

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Background: Sleep breathing disorder (SDB) is a condition demonstrated by recurrent episodes of the airway obstruction leading to intermittent hypoxia and quality fragmentation during sleep time. However, the procedures for SDB severity examination remain complicated and costly. Objective: The objective of this study is to establish a simplified examination method for SDB by the respiratory impendence pattern sensor combining the signal processing and machine learning model. Methodologies: We records heart rate variability by the electrocardiogram and respiratory pattern by impendence. After the polysomnography (PSG) been done with the diagnosis of SDB by the apnea and hypopnea index (AHI), we calculate the episodes with the absence of flow and arousal index (AI) from device record. Subjects were divided into training and testing groups. Neuron network was used to establish a prediction model to classify the severity of the SDB by the AI, episodes, and body profiles. The performance was evaluated by classification in the testing group compared with PSG. Results: In this study, we enrolled 66 subjects (Male/Female: 37/29; Age:49.9±13.2) with the diagnosis of SDB in a sleep center in Taipei city, Taiwan, from 2015 to 2016. The accuracy from the confusion matrix on the test group by NN is 71.94 %. Conclusion: Based on the models, we established a prediction model for SDB by means of the wearable sensor. With more cases incoming and training, this system may be used to rapidly and automatically screen the risk of SDB in the future.

Keywords: sleep breathing disorder, apnea and hypopnea index, body parameters, neuron network

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Authors: Oindrila Nath, S. Sridharan

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Long-term (2002-2012) temperature and ozone measurements by Sounding of Atmosphere by Broadband Emission Radiometry (SABER) instrument onboard Thermosphere, Ionosphere, Mesosphere Energetics and Dynamics (TIMED) satellite zonally averaged over 10°N-15°N are used to study their long-term changes and their responses to solar cycle, quasi-biennial oscillation and El Nino Southern Oscillation. The region is selected to provide more accurate long-term trends and variabilities, which were not possible earlier with lidar measurements over Gadanki (13.5°N, 79.2°E), which are limited to cloud-free nights, whereas continuous data sets of SABER temperature and ozone are available. Regression analysis of temperature shows a cooling trend of 0.5K/decade in the stratosphere and that of 3K/decade in the mesosphere. Ozone shows a statistically significant decreasing trend of 1.3 ppmv per decade in the mesosphere although there is a small positive trend in stratosphere at 25 km. Other than this no significant ozone trend is observed in stratosphere. Negative ozone-QBO response (0.02ppmv/QBO), positive ozone-solar cycle (0.91ppmv/100SFU) and negative response to ENSO (0.51ppmv/SOI) have been found more in mesosphere whereas positive ozone response to ENSO (0.23ppmv/SOI) is pronounced in stratosphere (20-30 km). The temperature response to solar cycle is more positive (3.74K/100SFU) in the upper mesosphere and its response to ENSO is negative around 80 km and positive around 90-100 km and its response to QBO is insignificant at most of the heights. Composite monthly mean of ozone volume mixing ratio shows maximum values during pre-monsoon and post-monsoon season in middle stratosphere (25-30 km) and in upper mesosphere (85-95 km) around 10 ppmv. Composite monthly mean of temperature shows semi-annual variation with large values (~250-260 K) in equinox months and less values in solstice months in upper stratosphere and lower mesosphere (40-55 km) whereas the SAO becomes weaker above 55 km. The semi-annual variation again appears at 80-90 km, with large values in spring equinox and winter months. In the upper mesosphere (90-100 km), less temperature (~170-190 K) prevails in all the months except during September, when the temperature is slightly more. The height profiles of amplitudes of semi-annual and annual oscillations in ozone show maximum values of 6 ppmv and 2.5 ppmv respectively in upper mesosphere (80-100 km), whereas SAO and AO in temperature show maximum values of 5.8 K and 4.6 K in lower and middle mesosphere around 60-85 km. The phase profiles of both SAO and AO show downward progressions. These results are being compared with long-term lidar temperature measurements over Gadanki (13.5°N, 79.2°E) and the results obtained will be presented during the meeting.

Keywords: trends, QBO, solar cycle, ENSO, ozone, temperature

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Authors: Javid Iqbal, Zhu Shifan

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The development in the construction of unconventional ships and the implementation of lightweight materials have shown a large impulse towards finite element (FE) method, making it a general tool for ship design. This paper briefly presents the modeling and analysis techniques of ship structures using FE method for complex boundary conditions which are difficult to analyze by existing Ship Classification Societies rules. During operation, all ships experience complex loading conditions. These loads are general categories into thermal loads, linear static, dynamic and non-linear loads. General strength of the ship structure is analyzed using static FE analysis. FE method is also suitable to consider the local loads generated by ballast tanks and cargo in addition to hydrostatic and hydrodynamic loads. Vibration analysis of a ship structure and its components can be performed using FE method which helps in obtaining the dynamic stability of the ship. FE method has developed better techniques for calculation of natural frequencies and different mode shapes of ship structure to avoid resonance both globally and locally. There is a lot of development towards the ideal design in ship industry over the past few years for solving complex engineering problems by employing the data stored in the FE model. This paper provides an overview of ship modeling methodology for FE analysis and its general application. Historical background, the basic concept of FE, advantages, and disadvantages of FE analysis are also reported along with examples related to hull strength and structural components.

Keywords: dynamic analysis, finite element methods, ship structure, vibration analysis

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Authors: Ashlie Latiolais

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Architecture, as a discipline, is on a trajectory of extension beyond the boundaries of buildings and, more increasingly, is coupled with research that connects to alternative and typically disjointed disciplines. A “both/and” approach and (expanded) definition of architecture, as depicted here, expands the margins that contain the profession. Figuratively, architecture is a series of edges, events, and occurrences that establishes a choreography or stage by which humanity exists. The way in which architecture controls and suggests the movement through these spaces, being within a landscape, city, or building, can be viewed as a datum by which the “dance” of everyday life occurs. This submission views the realm of architecture through the lens of movement and dance as a cross-fertilizer of collaboration, tectonic, and spatial geometry investigations. “Designing on digital programs puts architects at a distance from the spaces they imagine. While this has obvious advantages, it also means that they lose the lived, embodied experience of feeling what is needed in space—meaning that some design ideas that work in theory ultimately fail in practice.” By studying the body in motion through real-time performance, a more holistic understanding of architectural space surfaces and new prospects for theoretical teaching pedagogies emerge. The atypical intersection rethinks how architecture is considered, created, and tested, similar to how “dance artists often do this by thinking through the body, opening pathways and possibilities that might not otherwise be accessible” –this is the essence of this poster submission as explained through unFOLDED, a creative performance work. A new languageismaterialized through unFOLDED, a dynamic occupiable installation by which architecture is investigated through dance, movement, and body analysis. The entry unfolds a collaboration of an architect, dance choreographer, musicians, video artist, and lighting designers to re-create one of the first documented avant-garde performing arts collaborations (Matisse, Satie, Massine, Picasso) from the Ballet Russes in 1917, entitled Parade. Architecturally, this interdisciplinary project orients and suggests motion through structure, tectonic, lightness, darkness, and shadow as it questions the navigation of the dark space (stage) surrounding the installation. Artificial light via theatrical lighting and video graphics brought the blank canvas to life – where the sensitive mix of musicality coordinated with the structure’s movement sequencing was certainly a challenge. The upstage light from the video projections created both flickered contextual imagery and shadowed figures. When the dancers were either upstage or downstage of the structure, both silhouetted figures and revealed bodies are experienced as dancer-controlled installation manipulations occurred throughout the performance. The experimental performance, through structure, prompted moving (dancing) bodies in space, where the architecture served as a key component to the choreography itself. The tectonic of the delicate steel structure allowed for the dancers to interact with the installation, which created a variety of spatial conditions – the contained box of three-dimensional space, to a wall, and various abstracted geometries in between. The development of this research unveils the new role of an Architect as a Choreographer of the built environment.

Keywords: dance, architecture, choreography, installation, architect, choreographer, space

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Authors: Bamikole J. Adeyemi, Prashant Jadhawar, Lateef Akanji

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Theoretically, there exist two mathematical interfaces (fluid-solid and fluid-fluid) when a liquid film is present on solid surfaces. These interfaces overlap if the mineral surface is oil-wet or mixed wet, and therefore, the effects of disjoining pressure are significant on both boundaries. Hence, dewetting is a necessary process that could detach oil from the mineral surface. However, if the thickness of the thin water film directly in contact with the surface is large enough, disjoining pressure can be thought to be zero at the liquid-liquid interface. Recent studies show that the integration of fluid-fluid interactions with fluid-rock interactions is an important step towards a holistic approach to understanding smart water effects. Experiments have shown that the brine solution can alter the micro forces at oil-water interfaces, and these ion-specific interactions lead to oil emulsion formation. The natural emulsifiers present in crude oil behave as polyelectrolytes when the oil interfaces with low salinity water. Wettability alteration caused by low salinity waterflooding during Enhanced Oil Recovery (EOR) process results from the activities of divalent ions. However, polyelectrolytes are said to lose their viscoelastic property with increasing cation concentrations. In this work, the influence of cation concentrations on the dynamics of viscoelastic liquid-liquid interfaces is numerically investigated. The resultant ion concentrations at the crude oil/brine interfaces were estimated using a surface complexation model. Subsequently, the ion concentration parameter is integrated into a mathematical model to describe its effects on the dynamics of a viscoelastic interfacial thin film. The film growth, stability, and rupture were measured after different time steps for three types of fluids (Newtonian, purely elastic and viscoelastic fluids). The interfacial films respond to exposure time in a similar manner with an increasing growth rate, which resulted in the formation of more droplets with time. Increased surfactant accumulation at the interface results in a higher film growth rate which leads to instability and subsequent formation of more satellite droplets. Purely elastic and viscoelastic properties limit film growth rate and consequent film stability compared to the Newtonian fluid. Therefore, low salinity and reduced concentration of the potential determining ions in injection water will lead to improved interfacial viscoelasticity.

Keywords: liquid-liquid interfaces, surfactant concentrations, potential determining ions, residual oil mobilization

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Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

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Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: communication signal, feature extraction, Holder coefficient, improved cloud model

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Authors: Katerina Krizova, Inigo Molina

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The ongoing climate change affects various natural processes resulting in significant changes in human life. Since there is still a growing human population on the planet with more or less limited resources, agricultural production became an issue and a satisfactory amount of food has to be reassured. To achieve this, agriculture is being studied in a very wide context. The main aim here is to increase primary production on a spatial unit while consuming as low amounts of resources as possible. In Europe, nowadays, the staple issue comes from significantly changing the spatial and temporal distribution of precipitation. Recent growing seasons have been considerably affected by long drought periods that have led to quantitative as well as qualitative yield losses. To cope with such kind of conditions, new techniques and technologies are being implemented in current practices. However, behind assessing the right management, there is always a set of the necessary information about plot properties that need to be acquired. Remotely sensed data had gained attention in recent decades since they provide spatial information about the studied surface based on its spectral behavior. A number of space platforms have been launched carrying various types of sensors. Spectral indices based on calculations with reflectance in visible and NIR bands are nowadays quite commonly used to describe the crop status. However, there is still the staple limit by this kind of data - cloudiness. Relatively frequent revisit of modern satellites cannot be fully utilized since the information is hidden under the clouds. Therefore, microwave remote sensing, which can penetrate the atmosphere, is on its rise today. The scientific literature describes the potential of radar data to estimate staple soil (roughness, moisture) and vegetation (LAI, biomass, height) properties. Although all of these are highly demanded in terms of agricultural monitoring, the crop moisture content is the utmost important parameter in terms of agricultural drought monitoring. The idea behind this study was to exploit the unique combination of SAR (Sentinel-1) and optical (Sentinel-2) data from one provider (ESA) to describe potential crop water stress during dry cropping season of 2019 at six winter wheat plots in the central Czech Republic. For the period of January to August, Sentinel-1 and Sentinel-2 images were obtained and processed. Sentinel-1 imagery carries information about C-band backscatter in two polarisations (VV, VH). Sentinel-2 was used to derive vegetation properties (LAI, FCV, NDWI, and SAVI) as support for Sentinel-1 results. For each term and plot, summary statistics were performed, including precipitation data and soil moisture content obtained through data loggers. Results were presented as summary layouts of VV and VH polarisations and related plots describing other properties. All plots performed along with the principle of the basic SAR backscatter equation. Considering the needs of practical applications, the vegetation moisture content may be assessed using SAR data to predict the drought impact on the final product quality and yields independently of cloud cover over the studied scene.

Keywords: precision agriculture, remote sensing, Sentinel-1, SAR, water content

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Authors: Piret Pernik

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Based on strategic, operational, and technical analysis of the ongoing armed conflict in Ukraine, this paper will examine the opportunities and risks of using small commercial drones (dual-use unmanned aerial vehicles, UAV) for military purposes. The paper discusses the opportunities and risks in the information domain, encompassing both cyber and electromagnetic interference and attacks. The paper will draw conclusions on a possible strategic impact to the battlefield outcomes in the modern armed conflicts by the widespread use of dual-use UAVs. This article will contribute to filling the gap in the literature by examining based on empirical data cyberattacks and electromagnetic interference. Today, more than one hundred states and non-state actors possess UAVs ranging from low cost commodity models, widely are dual-use, available and affordable to anyone, to high-cost combat UAVs (UCAV) with lethal kinetic strike capabilities, which can be enhanced with Artificial Intelligence (AI) and Machine Learning (ML). Dual-use UAVs have been used by various actors for intelligence, reconnaissance, surveillance, situational awareness, geolocation, and kinetic targeting. Thus they function as force multipliers enabling kinetic and electronic warfare attacks and provide comparative and asymmetric operational and tactical advances. Some go as far as argue that automated (or semi-automated) systems can change the character of warfare, while others observe that the use of small drones has not changed the balance of power or battlefield outcomes. UAVs give considerable opportunities for commanders, for example, because they can be operated without GPS navigation, makes them less vulnerable and dependent on satellite communications. They can and have been used to conduct cyberattacks, electromagnetic interference, and kinetic attacks. However, they are highly vulnerable to those attacks themselves. So far, strategic studies, literature, and expert commentary have overlooked cybersecurity and electronic interference dimension of the use of dual use UAVs. The studies that link technical analysis of opportunities and risks with strategic battlefield outcomes is missing. It is expected that dual use commercial UAV proliferation in armed and hybrid conflicts will continue and accelerate in the future. Therefore, it is important to understand specific opportunities and risks related to the crowdsourced use of dual-use UAVs, which can have kinetic effects. Technical countermeasures to protect UAVs differ depending on a type of UAV (small, midsize, large, stealth combat), and this paper will offer a unique analysis of small UAVs both from the view of opportunities and risks for commanders and other actors in armed conflict.

Keywords: dual-use technology, cyber attacks, electromagnetic warfare, case studies of cyberattacks in armed conflicts

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Authors: Soumya Sajjan

Abstract:

Liver cancer is the most common cancer disease worldwide in men and women, and is one of the few cancers still on the rise. Liver disease is the 4th leading cause of death. According to new NHS (National Health Service) figures, deaths from liver diseases have reached record levels, rising by 25% in less than a decade; heavy drinking, obesity, and hepatitis are believed to be behind the rise. In this study, we focus on Development of Diagnostic Classifier for Ultrasound liver lesion. Ultrasound (US) Sonography is an easy-to-use and widely popular imaging modality because of its ability to visualize many human soft tissues/organs without any harmful effect. This paper will provide an overview of underlying concepts, along with algorithms for processing of liver ultrasound images Naturaly, Ultrasound liver lesion images are having more spackle noise. Developing classifier for ultrasound liver lesion image is a challenging task. We approach fully automatic machine learning system for developing this classifier. First, we segment the liver image by calculating the textural features from co-occurrence matrix and run length method. For classification, Support Vector Machine is used based on the risk bounds of statistical learning theory. The textural features for different features methods are given as input to the SVM individually. Performance analysis train and test datasets carried out separately using SVM Model. Whenever an ultrasonic liver lesion image is given to the SVM classifier system, the features are calculated, classified, as normal and diseased liver lesion. We hope the result will be helpful to the physician to identify the liver cancer in non-invasive method.

Keywords: segmentation, Support Vector Machine, ultrasound liver lesion, co-occurance Matrix

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