Search results for: features extraction

Authors: Camilo Souza, Lidia Melo, Fernanda Terra, Francisco Caio, Marcelo Reis

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SIDIA is a research and development (R&D) institute that belongs to Samsung’s global software development process. The SIDIA’s Model Team (MT) is a part of Samsung’s Mobile Division Area, which is responsible for the development of Android releases embedded in Samsung mobile devices. Basically, in this software development process, the kickoff occurs in some strategic countries (e.g., South Korea) where some software requirements are applied and the initial software tests are performed. When the software achieves a more mature level, a new branch is derived, and the development continues in subsidiaries from other strategic countries (e.g., SIDIA-Brazil). However, even in the newly created branches, there are several interactions between developers from different nationalities in order to fix bugs reported during test activities, apply some specific requirements from partners and develop new features as well. Despite the GSD strategy contributes to improving software development, some challenges are also introduced as well. In this paper, we share the initial results about the application of the failure modes and effect analysis (FMEA) concept in the software development process followed by the SIDIA’s model team. The main goal was to identify and mitigate the process potential failures through the application of recommended actions. The initial results show that the application of the FMEA concept allows us to identify the potential failures in our GSD process as well as to propose corrective actions to mitigate them. Finally, FMEA encouraged members of different teams to take actions that contribute to improving our GSD process.

Keywords: global software development, potential failures, FMEA, recommended actions

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Authors: Rasha Hosny, Ahmed Zahran, Mahmoud Ramzi, Fatma Mahmoud Abdelhafiz, Ammona S. Mohamed, Mahmoud Fathy Mubarak

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Ionic liquids' ability to be tuned and stability under challenging environmental conditions are their significant features in enhanced oil recovery. In this study, two amino acid ionic liquids (AAILs) were prepared from quaternized hyperbranched polyamidoamine PAMAM (G0.5 C12) and amino acids (Cysteine and Lysine). The chemical structures of the prepared AAILs were verified by using FTIR and 1H-NMR spectra. These AAILs were tested for solubility, thermal stability, and surface activity in the presence of Egyptian medium crude oils under different PVT parameters after being diluted in several brine solutions of various salt compositions at 10% (w/w) salinity. The measurements reveal that the produced AAILs have good solubility and thermal stability. The effect of different concentrations of AAILs (0.1-5%) and salinity (20000-70000 ppm) on Interfacial tension (IFT) were studied. To test the efficacy of (AAILs) for a CEOR, numerous flooding experiments were carried out in samples of sandstone rock. Rock wettability is important for sandstone rocks, so conduct wettability alteration by contact angle (CA) of (30-55) and IFT of (7-13). The additional oil recovery was largely influenced by ionic liquid concentration, which may be changed by dilution with the formation and injected brines. This research has demonstrated that EOR techniques led to a recovery wt. (22-45%).

Keywords: amino acid ionic liquids, surface activity, critical micelle concentration, interfacial tension, contact angle, chemical enhanced oil recovery, wettability

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Authors: Adrien Pyskir, Manuel Collet, Zoran Dimitrijevic, Claude-Henri Lamarque

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During the last decades, great efforts have been made to reduce acoustic and vibrational disturbances in transportations, as it has become a key feature for comfort. Today, isolation and design have neutralized most of the troublesome vibrations, so that cars are quieter and more comfortable than ever. However, some problems remain unsolved, in particular concerning low-frequency isolation and the frequency-dependent stiffening of materials like rubber. To sum it up, a balance has to be found between a high static stiffness to sustain the vibration source’s mass, and low dynamic stiffness, as wideband as possible. Systems meeting these criteria are yet to be designed. We thus investigated solutions inspired by metamaterials to control efficiently low-frequency wave propagation. Structures exhibiting a negative Poisson ratio, also called auxetic structures, are known to influence the propagation of waves through beaming or damping. However, their stiffness can be quite peculiar as well, as they can present regions of zero stiffness on the stress-strain curve for compression. In addition, auxetic materials can be easily adapted in many ways, inducing great tuning potential. Using finite element software COMSOL Multiphysics, a resonant design has been tested through statics and dynamics simulations. These results are compared to experimental results. In particular, the bandgaps featured by these structures are analyzed as a function of design parameters. Great stiffness properties can be observed, including low-frequency dynamic stiffness loss and broadband transmission loss. Such features are very promising for practical isolation purpose, and we hope to adopt this kind of metamaterial into an effective industrial damper.

Keywords: auxetics, metamaterials, structural dynamics, vibration isolation

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Authors: Taekyong Lee, Joon-Young Kim, Jae-Min Cha

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Piping and instrumentation diagram (P&ID) is an essential design drawing describing the interconnection of process equipment and the instrumentation installed to control the process. P&IDs are modified and managed throughout a whole life cycle of a process plant. For the ease of data transfer, P&IDs are generally handed over from a design company to an engineering company as portable document format (PDF) which is hard to be modified. Therefore, engineering companies have to deploy a great deal of time and human resources only for manually converting P&ID images into a computer aided design (CAD) file format. To reduce the inefficiency of the P&ID conversion, various symbols and texts in P&ID images should be automatically recognized. However, recognizing information in P&ID images is not an easy task. A P&ID image usually contains hundreds of symbol and text objects. Most objects are pretty small compared to the size of a whole image and are densely packed together. Traditional recognition methods based on geometrical features are not capable enough to recognize every elements of a P&ID image. To overcome these difficulties, state-of-the-art deep learning models, RetinaNet and connectionist text proposal network (CTPN) were used to build a system for recognizing symbols and texts in a P&ID image. Using the RetinaNet and the CTPN model carefully modified and tuned for P&ID image dataset, the developed system recognizes texts, equipment symbols, piping symbols and instrumentation symbols from an input P&ID image and save the recognition results as the pre-defined extensible markup language format. In the test using a commercial P&ID image, the P&ID information recognition system correctly recognized 97% of the symbols and 81.4% of the texts.

Keywords: object recognition system, P&ID, symbol recognition, text recognition

Procedia PDF Downloads 134

Authors: Rajesha Kumar Alambi, Mansour Ahmed, Garudachari Bhadrachari, Safiyah Al-Muqahwi, Mansour Al-Rughaib, Jibu P. Thomas

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Membrane-based pressure assisted osmosis (PAO) for seawater desalination has the potential to overcome the challenges of forward osmosis technology. PAO technology is gaining interest among the research community to ensure the sustainability of freshwater with a significant reduction in energy. The requirements of PAO membranes differ from the FO membrane; as it needs a slightly higher porous with sufficient mechanical strength to overcome the applied hydraulic pressure. The porous metal-organic framework (MOF) as a filler for the membrane synthesis has demonstrated a great potential to generate new channels for water transport, high selectivity, and reduced fouling propensity. Accordingly, this study is aimed at fabricating the UiO-66 MOF-based thin film nanocomposite membranes with specific characteristics for water desalination by PAO. A PAO test unit manufactured by Trevi System, USA, was used to determine the performance of the synthesized membranes. Further, the synthesized membranes were characterized in terms of morphological features, hydrophilicity, surface roughness, and mechanical properties. The 0.05 UiO-66 loaded membrane produced highest flux of 38L/m2h and with low reverse salt leakage of 2.1g/m²h for the DI water as feed solution and 2.0 M NaCl as draw solutions at the inlet feed pressure of 0.6 MPa. The new membranes showed a good tolerance toward the applied hydraulic pressure attributed to the fabric support used during the membrane synthesis.

Keywords: metal organic framework, composite membrane, desalination, salt rejection, flux

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Authors: Mahmoud S Gewaily, Atif Hasan, Mohamed Kassab, Ali A. Mansour

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The current study was carried out on the nose of seventeenth healthy adult camels. Specimens were collected from slaughter houses then fixed, dissected and photographed. For ultra structural studies, fresh samples were fixed in different fixatives and prepared for examination by light, scanning and electron microscopes. Grossly, nose of the camel had narrow nostrils, slit like in outline. In the nasal cavity, the nasal vestibule was narrow and has scanty dorsal and lateral cartilaginous support. The Nasal conchae (dorsal, middle and ventral) enclosed the dorsal, middle conchal sinuses and no ventral conchal sinus; instead there was recess and bull a. The ethmoidal conchae (8 in number) were noticeably fewer than in the other domestic animals like ox and horse. The olfactory mucosa was restricted to a small area covering the caudal parts of the ethmoidal conchae. The lining epithelium of the nasal cavity changes gradually from stratified squamous epithelium in the nasal vestibule to pseudo stratified columnar ciliated in the respiratory region and finally, olfactory epithelium covering the caudal parts of the ethmoidal conchae. In the dromedary camel, a special feature was the presence of dense and relatively long hair covering the nostrils and the rostral part of the nasal vestibule. In conclusion, the anatomical features of the nose of the dromedary camel, especially in its rostral parts enable this animal to breathe properly in the sandy dry weather.

Keywords: camel nose, anatomy, dromedary camel, nasal vestibule

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Authors: Massimo Tadi, M. Hadi Mohammad Zadeh, Ozge Ogut

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Although how cities’ forms are structured is studied, more efforts are needed on systemic comprehensions and evaluations of the urban morphology through quantitative metrics that are able to describe the performance of a city in relation to its formal properties. More research is required in this direction in order to better describe the urban form characteristics and their impact on the environmental performance of cities and to increase their sustainability stewardship. With the aim of developing a better understanding of the built environment’s systemic structure, the intention of this paper is to present a holistic methodology for studying the behavior of the built environment and investigate the methods for measuring the effect of urban structure to the environmental performance. This goal will be pursued through an inquiry into the morphological components of the urban systems and the complex relationships between them. Particularly, this paper focuses on proximity, referring to the proximity of different land-uses, is a concept with which Integrated Modification Methodology (IMM) explains how land-use allocation might affect the choice of mobility in neighborhoods, and especially, encourage or discourage non-motived mobility. This paper uses proximity to demonstrate that the structure attributes can quantifiably relate to the performing behavior in the city. The target is to devise a mathematical pattern from the structural elements and correlate it directly with urban performance indicators concerned with environmental sustainability. The paper presents some results of this rigorous investigation of urban proximity and its correlation with performance indicators in four different areas in the city of Milan, each of them characterized by different morphological features.

Keywords: built environment, ecology, sustainable indicators, sustainability, urban morphology

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Authors: W. Hajuthman, R. Warner, S. Rahman, M. Abraham, H. Helliwell, D. Bodiwala

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Context: Prostate cancer is a prevalent cancer in males in Europe and the US, with diagnosis primarily relying on PSA testing, mpMRI, and subsequent biopsies. However, this diagnostic strategy may lead to complications for patients. Research Aim: The aim of this study is to assess compliance with trust guidelines for antibiotic prophylaxis in patients undergoing transperineal template biopsies of the prostate and evaluate the rate of post-procedure complications. Methodology: This study is conducted retrospectively over an 8-month period. Data collection includes patient demographics, compliance with trust guidelines, associated risk factors, and post-procedure complications such as infection, haematuria, and urinary retention. Findings: The audit includes 100 patients with a median age of 66.11. The compliance with pre-procedure antibiotics was 98%, while compliance with antibiotic prophylaxis recommended by trust guidelines was 68%. Among the patients, 3% developed post-procedure sepsis, with 2 requiring admission for intravenous antibiotics. No evident risk factors were identified in these cases. Additionally, post-procedure urinary retention occurred in 3% of patients and post-procedure haematuria in 2%. Theoretical Importance: This study highlights the increasing use of transperineal template biopsies across UK centres and suggests that having a standardized protocol and compliance with guidelines can reduce confusion, ensure appropriate administration of antibiotics, and mitigate post-procedure complications. Data Collection and Analysis Procedures: Data for this study is collected retrospectively, involving the extraction and analysis of relevant information from patient records over the specified 8-month period. Question Addressed: This study addresses the following research questions: (1) What is the compliance rate with trust guidelines for antibiotic prophylaxis in transperineal template biopsies of the prostate? (2) What is the rate of post-procedure complications, such as infection, haematuria, and urinary retention? Conclusion: Transperineal template biopsies are becoming increasingly prevalent in the UK. Implementing a standardized protocol and ensuring compliance with guidelines can reduce confusion, ensure proper administration of antibiotics, and potentially minimize post-procedure complications. Additionally, considering that studies show no difference in outcomes when prophylactic antibiotics are not used, the reminder to follow trust guidelines may prompt a re-evaluation of antibiotic prescribing practices.

Keywords: prostate, transperineal template biopsies of prostate, antibiotics, complications, microbiology, guidelines

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Authors: Raka Rahmatulloh, Mohammad Ilham Nugraha, Muhammad Ifan Fathurrahman

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The agricultural sector covers a wide area, one of them is livestock subsector that supply needs of the food source of animal protein. Animal protein is produced by the main livestock production such as meat, milk, eggs, etc. Besides the main production, livestock would produce metabolic residue, so called livestock wastes. Characteristics of livestock wastes can be either solid (feces), liquid (urine), and gas (methane) which turned out to be useful and has economical value when well-processed and well-controlled. Nowadays, this livestock wastes is considered as a source of pollutants, especially water pollution. If the source of pollutants used in an integrated way, it will have a positive impact on organic farming and a healthy environment. Management of livestock wastes can be integrated with the farming sector to the planting and caring that rely on fertilizers. Most Indonesian farmers still use chemical fertilizers, where the use of it in the long term will disturb the ecological balance of the environment. One of the main efforts is to use organic fertilizers instead of chemical fertilizer that conducted by the Faculty of Animal Husbandry, Padjadjaran University. The method is to use the solid waste of livestock and agricultural wastes into liquid organic fertilizer, feed additive, biogas and vermicompost through decomposition. The decomposition takes as long as 14 days including aeration and extraction process using water as a nutrients solvent media which contained in decomposes and disinfection media to release pathogenic microorganisms in decomposes. Liquid organic fertilizer has highly efficient for the farmers to have a ratio of carbon/nitrogen (C/N) 25/1 to 30/1 and neutral pH (6.5-7.5) which is good for plant growth. Feed additive may be given to improve the digestibility of feed so that substances can be easily absorbed by the body for production. Biogas contains methane (CH4), which has a high enough heat to produce electricity. Vermicompost is an overhaul of waste organic material that has excellent structure, porosity, aeration, drainage, and moisture holding capacity. Based on the case study above, an integrated livestock wastes management program strongly supports the Indonesian government in the achievement of sustainable livestock development.

Keywords: integrated, livestock wastes, organic fertilizer, sustainable livestock development

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Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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Authors: Abigail Tan, Heng Liang Tan, Vanessa Ding, James Hui, Eng Hin Lee, Andre Choo

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Introduction: Comparative oncology investigates the similarities in spontaneous carcinogenesis between humans and animals, in order to identify treatments that can benefit these patients. Companion animals (CA), like canines and felines, are of special interest when it comes to studying human cancers due to their exposure to the same environmental factors and develop tumours with similar features. The purpose of this study is to explore the cross-reactivity of monoclonal antibodies (mAbs) across cancers in humans and CA. Material and Methods: A panel of CA mAbs generated in the lab was screened on multiple human cancer cell lines through flow cytometry to identify for positive binders. Shortlisted candidates were then characterised by biochemical and functional assays e.g., antibody-drug conjugate (ADC) and western blot assays, including glycan studies. Results: Candidate mAb KP52 was generated from whole-cell immunisation using feline mammary carcinoma. KP52 showed strong positive binding to human cancer cells, such as breast cancer and ovarian cancer. Furthermore, KP52 demonstrated strong killing ( > 50%) as an ADC with Saporin as the payload. Western blot results revealed the molecular weight of the antigen targets to be approximately 45kD and 50kD under reduced conditions. Glycan studies suggest that the epitope is glycan in nature, specifically an O-linked glycan. Conclusion: Candidate mAb KP52 has a therapeutic potential as an ADC against feline mammary cancer, human ovarian cancer, human mammary cancer, human pancreatic cancer, and human gastric cancer.

Keywords: ADC, comparative oncology, mAb, therapeutic

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Authors: Mostafa Mabrouk, Basma E. Abdel-Ghany, Mona Moaness, Bothaina M. Abdel-Hady, Hanan H. Beherei

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Tissue engineering became a promising field for bone repair and regenerative medicine in which cultured cells, scaffolds and osteogenic inductive signals are used to regenerate tissues. The annual cost of treating bone defects in Egypt has been estimated to be many billions, while enormous costs are spent on imported bone grafts for bone injuries, tumors, and other pathologies associated with defective fracture healing. The current study is aimed at developing a more strategic approach in order to speed-up recovery after bone damage. This will reduce the risk of fatal surgical complications and improve the quality of life of people affected with such fractures. 3D scaffolds loaded with cheap nano-particles that possess an osteogenic effect were prepared by nano-electrospinning. The Microstructure and morphology characterizations of the 3D scaffolds were monitored using scanning electron microscopy (SEM). The physicochemical characterization was investigated using X-ray diffractometry (XRD) and infrared spectroscopy (IR). The Physicomechanical properties of the 3D scaffold were determined by a universal testing machine. The in vitro bioactivity of the 3D scaffold was assessed in simulated body fluid (SBF). The bone-bonding ability of novel 3D scaffolds was also evaluated. The obtained nanofibrous scaffolds demonstrated promising microstructure, physicochemical and physicomechanical features appropriate for enhanced bone regeneration. Therefore, the utilized nanomaterials loaded with the drug are greatly recommended as cheap alternatives to growth factors.

Keywords: bone regeneration, cheap scaffolds, nanomaterials, active molecules

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Authors: Shetie Gatew

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Current soil maps of Ethiopia do not represent accurately the soils of Nech Sar National Park. In the framework of studies on the ecology of the park, we prepared a soil map based on field observations and a digital terrain model derived from SRTM data with a 30-m resolution. The landscape comprises volcanic cones, lava and basalt outflows, undulating plains, horsts, alluvial plains and river deltas. SOTER-like terrain mapping units were identified. First, the DTM was classified into 128 terrain classes defined by slope gradient (4 classes), relief intensity (4 classes), potential drainage density (2 classes), and hypsometry (4 classes). A soil-landscape relation between the terrain mapping units and WRB soil units was established based on 34 soil profile pits. Based on this relation, the terrain mapping units were either merged or split to represent a comprehensive soil and terrain map. The soil map indicates that Leptosols (30 %), Cambisols (26%), Andosols (21%), Fluvisols (12 %), and Vertisols (9%) are the most widespread Reference Soil Groups of the park. In contrast, the harmonized soil map of Africa derived from the FAO soil map of the world indicates that Luvisols (70%), Vertisols (14%) and Fluvisols (16%) would be the most common Reference Soil Groups. However, these latter mapping units are not consistent with the topography, nor did we find such extensive areas occupied by Luvisols during the field survey. This case study shows that with the now freely available SRTM data, it is possible to improve current soil information layers with relatively limited resources, even in a complex terrain like Nech Sar National Park.

Keywords: andosols, cambisols, digital elevation model, leptosols, soil-landscaps relation

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Authors: Calister Wingang Makebe, Wilson Ambindei Agwanande, Emmanuel Jong Nso, P. Nisha

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Traditional liquid-state fermentation processes of Annona muricata L. juice can result in fluctuating product quality and quantity due to difficulties in control and scale up. This work describes a laboratory-scale batch fermentation process to produce a probiotic Annona muricata L. enzymatically extracted juice, which was modeled using the Doehlert design with independent extraction factors being incubation time, temperature, and enzyme concentration. It aimed at a better understanding of the traditional process as an initial step for future optimization. Annona muricata L. juice was fermented with L. acidophilus (NCDC 291) (LA), L. casei (NCDC 17) (LC), and a blend of LA and LC (LCA) for 72 h at 37 °C. Experimental data were fitted into mathematical models (Monod, Logistic and Luedeking and Piret models) using MATLAB software, to describe biomass growth, sugar utilization, and organic acid production. The optimal fermentation time was obtained based on cell viability, which was 24 h for LC and 36 h for LA and LCA. The model was particularly effective in estimating biomass growth, reducing sugar consumption, and lactic acid production. The values of the determination coefficient, R2, were 0.9946, 0.9913 and 0.9946, while the residual sum of square error, SSE, was 0.2876, 0.1738 and 0.1589 for LC, LA and LCA, respectively. The growth kinetic parameters included the maximum specific growth rate, µm, which was 0.2876 h-1, 0.1738 h-1 and 0.1589 h-1 as well as the substrate saturation, Ks, with 9.0680 g/L, 9.9337 g/L and 9.0709 g/L respectively for LC, LA and LCA. For the stoichiometric parameters, the yield of biomass based on utilized substrate (YXS) was 50.7932, 3.3940 and 61.0202, and the yield of product based on utilized substrate (YPS) was 2.4524, 0.2307 and 0.7415 for LC, LA, and LCA, respectively. In addition, the maintenance energy parameter (ms) was 0.0128, 0.0001 and 0.0004 with respect to LC, LA and LCA. With the kinetic model proposed by Luedeking and Piret for lactic acid production rate, the growth associated, and non-growth associated coefficients were determined as 1.0028 and 0.0109, respectively. The model was demonstrated for batch growth of LA, LC, and LCA in Annona muricata L. juice. The present investigation validates the potential of Annona muricata L. based medium for heightened economical production of a probiotic medium.

Keywords: L. acidophilus, L. casei, fermentation, modelling, kinetics

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Authors: Faiza Babur Khan, Sohail Asghar

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With an emergence of distributed environment, cloud computing is proving to be the most stimulating computing paradigm shift in computer technology, resulting in spectacular expansion in IT industry. Many companies have augmented their technical infrastructure by adopting cloud resource sharing architecture. Cloud computing has opened doors to unlimited opportunities from application to platform availability, expandable storage and provision of computing environment. However, from a security viewpoint, an added risk level is introduced from clouds, weakening the protection mechanisms, and hardening the availability of privacy, data security and on demand service. Issues of trust, confidentiality, and integrity are elevated due to multitenant resource sharing architecture of cloud. Trust or reliability of cloud refers to its capability of providing the needed services precisely and unfailingly. Confidentiality is the ability of the architecture to ensure authorization of the relevant party to access its private data. It also guarantees integrity to protect the data from being fabricated by an unauthorized user. So in order to assure provision of secured cloud, a roadmap or model is obligatory to analyze a security problem, design mitigation strategies, and evaluate solutions. The aim of the paper is twofold; first to enlighten the factors which make cloud security critical along with alleviation strategies and secondly to propose an intrusion detection model that identifies the attackers in a preventive way using machine learning Random Forest classifier with an accuracy of 99.8%. This model uses less number of features. A comparison with other classifiers is also presented.

Keywords: cloud security, threats, machine learning, random forest, classification

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Authors: Yildiray Korkmaz, Mehmet Aksoy

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In today's operations, countries want to reach their aims in the shortest way due to economical, political and humanitarian aspects. The most effective way of achieving this goal is to be able to penetrate strategic targets. Strategic targets are generally located deep inside of the countries and are defended by modern and efficient surface to air missiles (SAM) platforms which are operated as integrated with Intelligence, Surveillance and Reconnaissance (ISR) systems. On the other hand, these high valued targets are buried deep underground and hardened with strong materials against attacks. Therefore, to penetrate these targets requires very detailed intelligence. This intelligence process should include a wide range that is from weaponry to threat assessment. Accordingly, the framework of the attack package will be determined. This mission package has to execute missions in a high threat environment. The way to minimize the risk which depends on loss of life is to use packages which are formed by UAVs. However, some limitations arising from the characteristics of UAVs restricts the performance of the mission package consisted of UAVs. So, the mission package should be formed with UAVs under the leadership of a fifth generation manned aircraft. Thus, we can minimize the limitations, easily penetrate in the deep inside of the enemy territory with minimum risk, make a decision according to ever-changing conditions and finally destroy the strategic targets. In this article, the strengthens and weakness aspects of UAVs are examined by SWOT analysis. And also, it revealed features of a mission package and presented as an example what kind of a mission package we should form in order to get marginal benefit and penetrate into strategic targets with the development of autonomous mission execution capability in the near future.

Keywords: UAV, autonomy, mission package, strategic attack, mission planning

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Authors: Arup Saha Chaudhuri

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Structural steel is a very ductile material with high strength carrying capacity, thus it is very useful to make earthquake resistant buildings. It is a homogeneous material also. The member section and the structural system can be made very efficient for economical design. As the steel is recyclable and reused, it is a green material. The embodied energy for the efficiently designed steel structure is less than the RC structure. For sustainable green building steel is the best material nowadays. Moreover, pre-engineered and pre-fabricated faster construction methodologies help the development work to complete within the stipulated time. In this paper, the usefulness of Eccentric Bracing Frame (EBF) in steel structure over Moment Resisting Frame (MRF) and Concentric Bracing Frame (CBF) is shown. Stability of the steel structures against horizontal forces especially in seismic condition is efficiently possible by Eccentric bracing systems with economic connection details. The EBF is pin–ended, but the beam-column joints are designed for pin ended or for full connectivity. The EBF has several desirable features for seismic resistance. In comparison with CBF system, EBF system can be designed for appropriate stiffness and drift control. The link beam is supposed to yield in shear or flexure before initiation of yielding or buckling of the bracing member in tension or compression. The behavior of a 2-D steel frame is observed under seismic loading condition in the present paper. Ductility and brittleness of the frames are compared with respect to time period of vibration and dynamic base shear. It is observed that the EBF system is better than MRF system comparing the time period of vibration and base shear participation.

Keywords: steel building, green and sustainable, earthquake resistant, EBF system

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Authors: Hannah Nagel, Hayley Lang, Albert Sole Guitart, Natasha Lean, Rachel Allavena, Cleide Sprohnie-Barrera, Alex Young

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Aggressive neoplasia of the hoof is a rare occurrence in horses and has been only sporadically described in the literature. In the few cases reported intra-hoof wall, aggressive neoplasia has been documented radiographically and has been described with variable imaging characteristics. These include a well-defined osteolytic area, a smoothly outlined semi-circular defect, an extensive draining tract beneath the hoof wall, as well as an additional large area of osteolysis or an extensive central lytic region. A 20-year-old Quarterhorse gelding and a 10-year-old Thoroughbred gelding were both presented for chronic reoccurring lameness in the left forelimb and left hindlimb, respectively. Both of the cases displayed radiographic lesions that have been previously described but also displayed osteoproliferative expansile regions of additional bone formation. Changes associated with hoof neoplasia are often non-specific due to the nature and capacity of bone to react to pathological insult, which is either to proliferate or be absorbed. Both cases depict and describe imaging findings seen on radiography, contrast radiography, computed tomography, and magnetic resonance imaging before reaching a histological diagnosis of malignant melanoma and squamous cell carcinoma. Although aggressive hoof wall neoplasia is rare, there are some imaging features which may raise our index of suspicion for an aggressive hoof wall lesion. This case report documents two horses with similar imaging findings who underwent multiple assessments, surgical interventions, and imaging modalities with a final diagnosis of malignant neoplasia.

Keywords: horse, hoof, imaging, radiography, neoplasia

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Authors: Gianmaria Califano, Júlio Augusto Lucena Maciel, Olfa Zarrouk, Miguel Damasio, Jose Silvestre, Ana Margarida Fortes

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Global warming, with rapid and sudden changes in meteorological conditions, is one of the major constraints to ensuring agricultural and crop resilience in the Mediterranean regions. Several strategies are being adopted to reduce the pressure of drought stress on grapevines at regional and local scales: improvements in the irrigation systems, adoption of interline cover crops, and adaptation of pruning techniques. However, still, more can be achieved if also microbial compartments associated with plants are considered in crop management. It is known that the microbial community change according to several factors such as latitude, plant variety, age, rootstock, soil composition and agricultural management system. Considering the increasing pressure of the biotic and abiotic stresses, it is of utmost necessity to also evaluate the effects of drought on the microbiome associated with the grapevine, which is a commercially important crop worldwide. In this study, we characterize the diversity and the structure of the microbial community under three long-term irrigation levels (100% ETc, 50% ETc and rain-fed) in a drought-tolerant grapevine cultivar present worldwide, Syrah. To avoid the limitations of culture-dependent methods, amplicon sequencing with target primers for bacteria and fungi was applied to the same soil samples. The use of the DNeasy PowerSoil (Qiagen) extraction kit required further optimization with the use of lytic enzymes and heating steps to improve DNA yield and quality systematically across biological treatments. Target regions (16S rRNA and ITS genes) of our samples are being sequenced with Illumina technology. With bioinformatic pipelines, it will be possible to obtain a characterization of the bacterial and fungal diversity, structure and composition. Further, the microbial communities will be assessed for their functional activity, which remains an important metric considering the strong inter-kingdom interactions existing between plants and their associated microbiome. The results of this study will lay the basis for biotechnological applications: in combination with the establishment of a bacterial library, it will be possible to explore the possibility of testing synthetic microbial communities to support plant resistance to water scarcity.

Keywords: microbiome, metabarcoding, soil, vinegrape, syrah, global warming, crop sustainability

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Authors: Min Jindong, Wang Mingxia

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With the widespread use of artificial intelligence in life, computer vision, especially deep convolutional neural network models, has developed rapidly. With the increase of the complexity of the real visual target detection task and the improvement of the recognition accuracy, the target detection network model is also very large. The huge deep neural network model is not conducive to deployment on edge devices with limited resources, and the timeliness of network model inference is poor. In this paper, knowledge distillation is used to compress the huge and complex deep neural network model, and the knowledge contained in the complex network model is comprehensively transferred to another lightweight network model. Different from traditional knowledge distillation methods, we propose a novel knowledge distillation that incorporates multi-faceted features, called M-KD. In this paper, when training and optimizing the deep neural network model for target detection, the knowledge of the soft target output of the teacher network in knowledge distillation, the relationship between the layers of the teacher network and the feature attention map of the hidden layer of the teacher network are transferred to the student network as all knowledge. in the model. At the same time, we also introduce an intermediate transition layer, that is, an intermediate guidance layer, between the teacher network and the student network to make up for the huge difference between the teacher network and the student network. Finally, this paper adds an exploration module to the traditional knowledge distillation teacher-student network model. The student network model not only inherits the knowledge of the teacher network but also explores some new knowledge and characteristics. Comprehensive experiments in this paper using different distillation parameter configurations across multiple datasets and convolutional neural network models demonstrate that our proposed new network model achieves substantial improvements in speed and accuracy performance.

Keywords: object detection, knowledge distillation, convolutional network, model compression

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Authors: Wong Kean Hin, Kumarason A. L. V. Rasiah

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A building provides shelter and protection for an individual to live, work, sleep, procreate or engage in leisurely activities comfortably. Currently, a very popular term related to building was often stated by many parties, which is sustainability. A sustainable building is environmental friendly, healthy to the occupants, as well as efficient in electricity and water. This particular research is important to any parties that are involved in the construction industry. This research will provide the awareness and acceptability of Malaysian public towards sustainable residential building. It will also provide the developers about which sustainable features that the people usually want so that the developers can build a sustainable housing that suits the needs of people. Then, propose solutions to solve the difficulties of implementing sustainability in Malaysian housing industry. Qualitative and quantitative research methods were used throughout the process of data collection. The quantitative research method was distribution of questionnaires to 100 Malaysian public and 50 individuals that worked in developer companies. Then, the qualitative method was an interview session with experienced personnel in Malaysian construction industry. From the data collected, there is increasingly Malaysian public and developers are aware about the existence of sustainability. Moreover, the public is willing to invest on sustainable residential building with minimum additional cost. However, there is a mismatch in between sustainable elements provided by developers and the public needs. Some recommendations to improve the progression of sustainability had been proposed in this study, which include laws enforcement, cooperation between the both government sector with private sector, and private sector with private sector, and learn from modern countries. These information will be helpful and useful for the future of sustainability development in Malaysia.

Keywords: acceptability, awareness, Malaysian housing industry, sustainable elements, green building index

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Authors: Lufei Mao, Hongwei Chen, Zijiao Chai

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Informal housing is a widespread phenomenon in developing countries. In many newly-emerging cities in China, rapid urbanization leads to an influx of population as well as a shortage of housing. Under this background, container housing, a new form of informal housing, gradually appears on a small scale on urban temporary land in recent years. Container housing, just as its name implies, transforms containers into small houses that allow migrant workers group to live in it. Scholars in other countries have established sound theoretical frameworks for informal housing study, but the research fruits seem rather limited on this small scale housing form. Unlike the cases in developed countries, these houses, which are outside urban planning, bring about various environmental, economic, social and governance issues. Aiming to figure out this new-born housing form, a survey mainly on two container housing settlements in Hangzhou, China was carried out to gather the information of them. Based on this thorough survey, the paper concludes the features and problems of infrastructure, environment and social communication of container housing settlements. The result shows that these containers were lacking of basic facilities and were restricted in a small mess temporary land. Moreover, because of the deficiency in management, the rental rights of these containers might not be guaranteed. Then the paper analyzes the factors affecting the formation and evolution of container housing settlements. It turns out that institutional and policy factors, market factors and social factors were the main three factors that affect the formation. At last, the paper proposes some suggestions for the governance of container housing and the utility pattern of urban temporary land.

Keywords: container housing, informal housing, urban temporary land, urban governance

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Authors: Parisa Mansour

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Cystic fibrosis (CF) is one of the most common autosomal recessive diseases among whites. It mostly affects the lungs, causing infections and inflammation that account for 90% of deaths in CF patients. Because of this high variability in clinical presentation and organ involvement, investigating treatment responses and evaluating lung changes over time is critical to preventing CF progression. High-resolution computed tomography (HRCT) greatly facilitates the assessment of lung disease progression in CF patients. Recently, artificial intelligence was used to analyze chest CT scans of CF patients. In this paper, we propose a convolutional neural network (CNN) approach to classify CF lung patterns in HRCT images. The proposed network consists of two convolutional layers with 3 × 3 kernels and maximally connected in each layer, followed by two dense layers with 1024 and 10 neurons, respectively. The softmax layer prepares a predicted output probability distribution between classes. This layer has three exits corresponding to the categories of normal (healthy), bronchitis and inflammation. To train and evaluate the network, we constructed a patch-based dataset extracted from more than 1100 lung HRCT slices obtained from 45 CF patients. Comparative evaluation showed the effectiveness of the proposed CNN compared to its close peers. Classification accuracy, average sensitivity and specificity of 93.64%, 93.47% and 96.61% were achieved, indicating the potential of CNNs in analyzing lung CF patterns and monitoring lung health. In addition, the visual features extracted by our proposed method can be useful for automatic measurement and finally evaluation of the severity of CF patterns in lung HRCT images.

Keywords: HRCT, CF, cystic fibrosis, chest CT, artificial intelligence

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Authors: C. Xavier Mendieta, J. J McArthur

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Governments are playing an increasingly active role in reducing carbon emissions, and a key strategy has been the introduction of mandatory energy disclosure policies. These policies have resulted in a significant amount of publicly available data, providing researchers with a unique opportunity to develop location-specific energy and carbon emission benchmarks from this data set, which can then be used to develop building archetypes and used to inform urban energy models. This study presents the development of such a benchmark using the public reporting data. The data from Ontario’s Ministry of Energy for Post-Secondary Educational Institutions are being used to develop a series of building archetype dynamic building loads and energy benchmarks to fill a gap in the currently available building database. This paper presents the development of a benchmark for college and university residences within ASHRAE climate zone 6 areas in Ontario using the mandatory disclosure energy and greenhouse gas emissions data. The methodology presented includes data cleaning, statistical analysis, and benchmark development, and lessons learned from this investigation are presented and discussed to inform the development of future energy benchmarks from this larger data set. The key findings from this initial benchmarking study are: (1) the importance of careful data screening and outlier identification to develop a valid dataset; (2) the key features used to develop a model of the data are building age, size, and occupancy schedules and these can be used to estimate energy consumption; and (3) policy changes affecting the primary energy generation significantly affected greenhouse gas emissions, and consideration of these factors was critical to evaluate the validity of the reported data.

Keywords: building archetypes, data analysis, energy benchmarks, GHG emissions

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Authors: Byung Keun Yang, Jae Eun Ku, Young Seon Joo, Je Sung You, Sung Phil Chung, Hahn Shick Lee

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The purpose of this study is to review the evidence comparing the efficacy and safety between L-carnitine and extracorporeal elimination therapy in the management of acute valproic acid L-carnitine vs Extracorporeal Elimination for Acute Valproic acid Intoxication. PubMed, Embase, Cochrane library, Web of Science, KoreaMed, KMbase, and KISS were searched, using the terms carnitine and valproic acid. All studies, regardless of design, reporting efficacy or safety endpoints were included. Reference citations from identified publications were reviewed. Both English and Korean languages were included. Two authors extracted primary data elements including poisoning severity, presenting features, clinical management, and outcomes. Thirty two articles including 33 cases were identified. Poisoning severity was classified as 3 mild, 11 moderate, and 19 severe cases. Nine cases were treated with L-carnitine while 24 cases received extracorporeal therapy without L-carnitine. All patients except one expired patient treated with hemodialysis recovered clinically and no adverse effects were noted. A case report comparing two patients who ingested the same amount of valproic acid showed increased ICU stay (3 vs. 11 days) in case of delayed extracorporeal therapy. Published evidence comparing L-carnitine with extracorporeal therapy is limited. Based on the available evidence, it is reasonable to consider L-carnitine for patients with acute valproic acid overdose. In case of severe poisoning, extracorporeal therapy would also be considered in the early phase of treatment.

Keywords: carnitine, overdose, poisoning, renal dialysis, valproic acid

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Authors: Dachuan Shi, M. Hecht, Y. Ye

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With the trend of digitalization in railway freight transport, a large number of freight wagons in Germany have been equipped with telematics devices, commonly placed on the wagon body. A telematics device contains a GPS module for tracking and a 3-axis accelerometer for shock detection. Besides these basic functions, it is desired to use the integrated accelerometer for condition monitoring without any additional sensors. Wheel flats as a common type of failure on wheel tread cause large impacts on wagons and infrastructure as well as impulsive noise. A large wheel flat may even cause safety issues such as derailments. In this sense, this paper proposes a machine learning approach for wheel flat detection by using car body accelerations. Due to suspension systems, impulsive signals caused by wheel flats are damped significantly and thus could be buried in signal noise and disturbances. Therefore, it is very challenging to detect wheel flats using car body accelerations. The proposed algorithm considers the envelope spectrum of car body accelerations to eliminate the effect of noise and disturbances. Subsequently, a 1-D convolutional neural network (CNN), which is well known as a deep learning method, is constructed to automatically extract features in the envelope-frequency domain and conduct classification. The constructed CNN is trained and tested on field test data, which are measured on the underframe of a tank wagon with a wheel flat of 20 mm length in the operational condition. The test results demonstrate the good performance of the proposed algorithm for real-time fault detection.

Keywords: fault detection, wheel flat, convolutional neural network, machine learning

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Authors: Christoph Hacker, Zeynep Karahaliloglu, Gunnar Seide, Emir Baki Denkbas, Thomas Gries

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A wound dressing material is designed to facilitate wound healing and minimize scarring. An ideal wound dressing material should protect the wound from any contaminations of exogeneous microorganism. In addition, the dressing material should provide a moist environment through extraction of body fluid from the wound area. Recently, wound dressing electrospun nanofibrous membranes are produced by electrospinning from a polymer solution or a polymer melt. These materials have a great potential as dressing materials for wound healing because of superior properties such as high surface-to-volume ratio, high porosity with excellent pore interconnectivity. Melt electrospinning is an attractive tissue engineering scaffold manufacturing process which eliminated the health risk posed by organic solvents used in electrospinning process and reduced the production costs. In this study, antibacterial wound dressing materials were prepared from TPU (Elastollan 1185A) by a melt-electrospinning technique. The electrospinning parameters for an efficient melt-electrospinning process of TPU were optimized. The surface of the fibers was modified with poly(ethylene glycol) (PEG) by radio-frequency glow discharge plasma deposition method and with silver nanoparticles (nAg) to improve their wettability and antimicrobial properties. TPU melt-electrospun mats were characterized using SEM, DSC, TGA and XPS. The cell viability and proliferation on modified melt-electrospun TPU mats were evaluated using a mouse fibroblast cell line (L929). Antibacterial effects of theirs against both Staphylococcus aureus strain and Escherichia coli were investigated by disk-diffusion method. TPU was successfully processed into a porous, fibrous network of beadless fibers in the micrometer range (4.896±0.94 µm) with a voltage of 50 kV, a working distance of 6 cm, a temperature of the thermocouple and hot coil of 225–230ºC, and a flow rate of 0.1 mL/h. The antibacterial test indicated that PEG-modified nAg-loaded TPU melt-electrospun structure had excellent antibacterial effects and cell study results demonstrated that nAg-loaded TPU mats had no cytotoxic effect on the fibroblast cells. In this work, the surface of a melt-electrospun TPU mats was modified via PEG monomer and then nAg. Results showed melt-electrospun TPU mats modified with PEG and nAg have a great potential for use as an antibacterial wound dressing material and thus, requires further investigation.

Keywords: melt electrospinning, nanofiber, silver nanoparticles, wound dressing

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Authors: David M. Lucas, Charles W. Jarrett

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In the culture of Thailand, the Yak serve as a mediated icon representing strength, power, and mystical protection not only for the Buddha, but for population of worshipers. Originating from the forests of China, the Yak continue to stand guard at the gates of Buddhist temples. The Yak represents Thai culture in the hearts of Thai people. This paper presents a qualitative study regarding the curious mix of media, culture, and religion that projects the Yak of Thailand as a larger than life message throughout the political, cultural, and religious spheres. The gate guardians, or gods as they are sometimes called, appear throughout the religious temples of Asian cultures. However, the Asian cultures demonstrate differences in artistic renditions (or presentations) of such sentinels. Thailand gate guards (the Yak) stand in front of many Buddhist temples, and these iconic figures display unique features with varied symbolic significance. The temple (or wat), plays a vital role in every community; and, for many people, Thailand’s temples are the country’s most endearing sights. The authors applied folk-nography as a methodology to illustrate the importance of the Thai Yak in serving as meaningful icons that transcend not only time, but the culture, religion, and mass media. The Yak represent mythical, religious, artistic, cultural, and militaristic significance for the Thai people. Data collection included interviews, focus groups, and natural observations. This paper summarizes the perceptions of the Thai people concerning their gate sentries and the relationship, communication, connection, and the enduring respect that Thai people hold for their guardians of the gates.

Keywords: communication, culture, folknography, icon, image, media, protection, religion, yak

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Authors: Alanoud Moraya Aldalan, Abdulaziz Almaleh

Abstract:

A crucial component of maintaining a customer-oriented business as in the telecom industry is understanding the reasons and factors that lead to customer churn. Competition between telecom companies has greatly increased in recent years. It has become more important to understand customers’ needs in this strong market of telecom industries, especially for those who are looking to turn over their service providers. So, predictive churn is now a mandatory requirement for retaining those customers. Machine learning can be utilized to accomplish this. Churn Prediction has become a very important topic in terms of machine learning classification in the telecommunications industry. Understanding the factors of customer churn and how they behave is very important to building an effective churn prediction model. This paper aims to predict churn and identify factors of customers’ churn based on their past service usage history. Aiming at this objective, the study makes use of feature selection, normalization, and feature engineering. Then, this study compared the performance of four different machine learning algorithms on the Orange dataset: Logistic Regression, Random Forest, Decision Tree, and Gradient Boosting. Evaluation of the performance was conducted by using the F1 score and ROC-AUC. Comparing the results of this study with existing models has proven to produce better results. The results showed the Gradients Boosting with feature selection technique outperformed in this study by achieving a 99% F1-score and 99% AUC, and all other experiments achieved good results as well.

Keywords: machine learning, gradient boosting, logistic regression, churn, random forest, decision tree, ROC, AUC, F1-score

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Authors: Giuseppe Timperio, Robert De Souza

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The combination of factors such as temperamental climate change, rampant urbanization of risk exposed areas, political and social instabilities, is posing an alarming base for the further growth of number and magnitude of humanitarian crises worldwide. Given the unique features of humanitarian supply chain such as unpredictability of demand in space, time, and geography, spike in the number of requests for relief items in the first days after the calamity, uncertain state of logistics infrastructures, large volumes of unsolicited low-priority items, a proactive approach towards design of disaster response operations is needed to achieve high agility in mobilization of emergency supplies in the immediate aftermath of the event. This paper is an attempt in that direction, and it provides decision makers with crucial strategic insights for a more effective network design for disaster response. Decision sciences and ICT are integrated to analyse the robustness and resilience of a prepositioned network of emergency strategic stockpiles for a real-life case about Indonesia, one of the most vulnerable countries in Asia-Pacific, with the model being built upon a rich set of quantitative data. At this aim, a network optimization approach was implemented, with several what-if scenarios being accurately developed and tested. Findings of this study are able to support decision makers facing challenges related with disaster relief chains resilience, particularly about optimal configuration of supply chain facilities and optimal flows across the nodes, while considering the network structure from an end-to-end in-country distribution perspective.

Keywords: disaster preparedness, humanitarian logistics, network optimization, resilience

Procedia PDF Downloads 160