Search results for: large carnivores

Authors: Jocelyn B. Barbosa, Angeli L. Magbaril, Mariel T. Sabanal, John Paul T. Galario, Mikka P. Baldovino

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The use of technology has become ubiquitous in different areas of business today. With the advent of digital imaging and database technology, business owners have been motivated to integrate technology to their business operation ranging from small, medium to large enterprises. Technology has been found to have brought many benefits that can make a business grow. Hog or swine raising, for example, is a very popular enterprise in the Philippines, whose challenges in production monitoring can be addressed through technology integration. Swine production monitoring can become a tedious task as the enterprise goes larger. Specifically, problems like delayed and inconsistent reports are most likely to happen if counting of swine per pen of which building is done manually. In this study, we present iCount, which aims to ensure efficient swine detection and counting that hastens the swine production monitoring task. We develop a system that automatically detects and counts swine based on Sobel filter and ellipse fitting model, given the still photos of the group of swine captured in a pen. We improve the Sobel filter detection result through 8-neigbhorhood rule implementation. Ellipse fitting technique is then employed for proper swine detection. Furthermore, the system can generate periodic production reports and can identify the specific consumables to be served to the swine according to schedules. Experiments reveal that our algorithm provides an efficient way for detecting swine, thereby providing a significant amount of accuracy in production monitoring.

Keywords: automatic swine counting, swine detection, swine production monitoring, ellipse fitting model, sobel filter

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Authors: Kwanele Qonono

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Despite the significance and economic benefits of petrol stations in South Africa, these still pose a huge risk of fire and explosion threatening public safety. This research paper examines the extent to which land-use planning in Stellenbosch, South Africa, considers the fire risk posed by petrol stations and the implications for public safety as well as preparedness for large fires or explosions. To achieve this, the research identified the land-use types around petrol stations in Stellenbosch and determined the extent to which their locations comply with the local, national, and international land-use planning regulations. A mixed research method consisting of the collection and analysis of geospatial data and qualitative data was an applied method, where petrol stations within a six-kilometre radius of Stellenbosch’s town centre were utilised as study sites. The research examined the risk of fires/explosions at these petrol stations. The research investigated Stellenbosch Municipality’s institutional preparedness to respond in the event of a fire/explosion at these petrol stations. The research observed that siting of petrol stations does not comply with local, national, and international good practices, thus exposing the surrounding developments to fires and explosions. Land-use planning practice does not consider hazards created by petrol stations. Despite the potential for major fires at petrol stations, Stellenbosch Municipality’s level of preparedness to respond to petrol station fires appears low due to the prioritisation of more frequent events.

Keywords: petrol stations, technological hazard, drr, land-use planning, risk analysis

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Authors: Ghaleb Bin Huraib

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Atopic dermatitis (AD), also known as atopic eczema, is a chronic inflammatory skin disease characterized by severe itching and recurrent, relapsing eczema-like skin lesions, affecting up to 20% of children and 10% of adults in industrialized countries. AD is a complex multifactorial disease, and its exact etiology and pathogenesis have not been fully elucidated. The aim of this study was to investigate the impact of gene polymorphisms of T helper cell subtype Th1 and Th2 cytokines, interferon-gamma (IFN-γ), interleukin-6 (IL-6) and transforming growth factor (TGF)-β1on AD susceptibility in a Saudi cohort. One hundred four unrelated patients with AD and 195 healthy controls were genotyped for IFN-γ (874A/T), IL-6 (174G/C) and TGF-β1 (509C/T) polymorphisms using ARMS-PCR and PCR-RFLP technique. The frequency of genotypes AA and AT of IFN-γ (874A/T) differed significantly among patients and controls (P 0.001). The genotype AT was increased while genotype AA was decreased in AD patients as compared to controls. AD patients also had a higher frequency of T-containing genotypes (AT+TT) than controls (P = 0.001). The frequencies of alleles T and A were statistically different in patients and controls (P = 0.04). The frequencies of genotype GG and allele G of IL-6 (174G/C) were significantly higher, while genotype GC and allele C were lower in AD patients than in controls. There was no significant difference in the frequencies of alleles and genotypes of TGF-β1 (509C/T) polymorphism between the patient and control groups. These results showed that susceptibility to AD is influenced by the presence or absence of genotypes of IFN-γ (874A/T) and IL-6 (174G/C) polymorphisms. It is concluded T-allele and T-containing genotypes (AT+TT) of IFN-γ (874A/T) and G-allele and GG genotype ofIL-6 (174G/C) polymorphisms are susceptible to AD in Saudis. On the other hand, the TGF-β1 (509C/T) polymorphism may not be associated with AD risk in our population; however, further studies with large sample sizes are required to confirm these results.

Keywords: atopic dermatitis, Polymorphism, Interferon, IL-6

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Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin

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During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.

Keywords: artificial intelligence, COVID-19, depression detection, psychiatric disorder

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Authors: Jerzy Banski

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The basic aim of this study is to discuss and assess different classifications and research approaches to small towns that take their social and economic functions into account, as well as relations with surrounding areas. The subject literature typically includes three types of approaches to the classification of small towns: 1) the structural, 2) the location-related, and 3) the mixed. The structural approach allows for the grouping of towns from the point of view of the social, cultural and economic functions they discharge. The location-related approach draws on the idea of there being a continuum between the center and the periphery. A mixed classification making simultaneous use of the different approaches to research brings the most information to bear in regard to categories of the urban locality. Bearing in mind the approaches to classification, it is possible to propose a synthetic method for classifying small towns that takes account of economic structure, location and the relationship between the towns and their surroundings. In the case of economic structure, the small centers may be divided into two basic groups – those featuring a multi-branch structure and those that are specialized economically. A second element of the classification reflects the locations of urban centers. Two basic types can be identified – the small town within the range of impact of a large agglomeration, or else the town outside such areas, which is to say located peripherally. The third component of the classification arises out of small towns’ relations with their surroundings. In consequence, it is possible to indicate 8 types of small-town: from local centers enjoying good accessibility and a multi-branch economic structure to peripheral supra-local centers characterised by a specialized economic structure.

Keywords: small towns, classification, functional structure, localization

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Authors: Sajia Islam, T. Tahsina, S. Raihana, M. M. Rahman, Q. S. Rahman, T. M. Huda, S. E. Arifeen, M. J. Dibley

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Early neonatal sepsis accounts for more than two-thirds of all deaths in the first year of life. This study assessed the counseling during antenatal, perinatal, post natal periods and its association with possible sepsis in rural Bangladesh. Method: Data were collected from a large community-based trial in Bangladesh where pregnant women were enrolled from 2013-2015 covering 29,497 newborns. Sepsis was defined using neonatal danger signs reported by 'The Young-Infants Clinical Science Study Group. 'Result: Signs of sepsis was found among 15% of the neonates. Neonatal sepsis was higher among those who did not receive advice on TT vaccinations (15.4% vs. 11%, p < 0.05) and danger signs (14.8% vs. 12.8%, p < 0.05) during pregnancy. Advice on delivering in well-lit place was significantly associated with lower incidence of sepsis (12.7% vs. 14.8% p < 0.05). Sepsis was lower among neonates whose mothers were counseled on immediate newborn care for bathing after 3 days of delivery (13.4% vs. 15.2% p=0), breastfeeding within 1hr of birth (13.82 % vs. 15.28% p=0), apply nothing on the cord (11.54 vs. 15.06 p=0), immediate drying of child (12.62% vs. 14.89%, p=0). Neonatal sepsis was lower among children whose mothers received 2-4 advice [OR=0.91(95% CI: 0.85-0.97)] compared to neonates whose mothers received only 1 or none. Overall, children to mothers who received ≥ 5 advice had lowest incidence of sepsis [OR=0.83 (95% CI: 0.71-0.97)] Conclusion: Advice on antenatal, prenatal and post natal is significantly reduced with early newborn sepsis. Further research is required to identify specific type of counseling messages that translate into practices and reduce pathways towards early-newborn morbidities.

Keywords: ante natal care, counseling, neonatal sepsis, post natal care

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Authors: Barbara Erjauz, Juliane Eichhorn

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Background and Purpose: The world´s population is rapidly aging, wherefore the World Health Organization (WHO) is dealing with concepts of Age-Friendly-Communities and criteria to define them. Also in Germany, we can find an aging population and a large amount of seniors is living in rural areas. Those regions are defined by unique social and environmental characteristics, which can enhance or decrease age-friendliness. To identify and work with these characteristics, we are in need of appropriate assessment instruments. To the author’s best knowledge until now, no instrument could be identified as suitable and scientifically proven for the German speaking area. The aim of the study was to identify an assessment instrument to measure the age-friendliness of rural communities and its psychometric testing regarding the content validity. Methods: A literature search was carried out to identify instruments related to concepts of Age-Friendly-Communities. According to the German situation, an instrument was chosen and modified based on a Delphi-study. In this context, the content validity was investigated by calculating the Content Validity Index (CVI). Results: An instrument consisting of 86 items based on WHO indicators and the German situation in rural areas was created. 43 items (50%) had a Content Validity Index for Items (I-CVI) of 1,00, 37 items (43%) had an I-CVI of >0,78 and > 1.00, and 6 items had an I-CVI of >0,78. The value of the Content Validity Index for Scales, averaging calculation method (S-CVI/Ave) for the entire scale was 0,91. Conclusions: The results indicate a good content validity and it can be concluded that the created instrument represents the phenomenon of age-friendliness in rural areas. Nevertheless, further psychometric testing related to reliability, validity and responsiveness is recommended.

Keywords: assessment, age-friendly, rural, psychometric testing

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Authors: Yu-ding Du, Qi-lian Bao, Nassim Bessaad, Lin Liu

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The Global Navigation Satellite System (GNSS) is regarded as an effective approach for the purpose of replacing the large amount used track-side balises in modern train localization systems. This paper describes a method based on the data fusion of a GNSS receiver sensor and an odometer sensor that can significantly improve the positioning accuracy. A digital track map is needed as another sensor to project two-dimensional GNSS position to one-dimensional along-track distance due to the fact that the train’s position can only be constrained on the track. A model trained by BP neural network is used to estimate the trend positioning error which is related to the specific location and proximate processing of the digital track map. Considering that in some conditions the satellite signal failure will lead to the increase of GNSS positioning error, a detection step for GNSS signal is applied. An adaptive weighted fusion algorithm is presented to reduce the standard deviation of train speed measurement. Finally an Extended Kalman Filter (EKF) is used for the fusion of the projected 1-D GNSS positioning data and the 1-D train speed data to get the estimate position. Experimental results suggest that the proposed method performs well, which can reduce positioning error notably.

Keywords: multi-sensor data fusion, train positioning, GNSS, odometer, digital track map, map matching, BP neural network, adaptive weighted fusion, Kalman filter

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Authors: N. H. Harun, A. S. Abdul Nasir, M. Y. Mashor, R. Hassan

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Leukaemia is a blood cancer disease that contributes to the increment of mortality rate in Malaysia each year. There are two main categories for leukaemia, which are acute and chronic leukaemia. The production and development of acute leukaemia cells occurs rapidly and uncontrollable. Therefore, if the identification of acute leukaemia cells could be done fast and effectively, proper treatment and medicine could be delivered. Due to the requirement of prompt and accurate diagnosis of leukaemia, the current study has proposed unsupervised pixel segmentation based on clustering algorithm in order to obtain a fully segmented abnormal white blood cell (blast) in acute leukaemia image. In order to obtain the segmented blast, the current study proposed three clustering algorithms which are k-means, fuzzy c-means and moving k-means algorithms have been applied on the saturation component image. Then, median filter and seeded region growing area extraction algorithms have been applied, to smooth the region of segmented blast and to remove the large unwanted regions from the image, respectively. Comparisons among the three clustering algorithms are made in order to measure the performance of each clustering algorithm on segmenting the blast area. Based on the good sensitivity value that has been obtained, the results indicate that moving k-means clustering algorithm has successfully produced the fully segmented blast region in acute leukaemia image. Hence, indicating that the resultant images could be helpful to haematologists for further analysis of acute leukaemia.

Keywords: acute leukaemia images, clustering algorithms, image segmentation, moving k-means

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Authors: Md Omar Faruq Howlader, Tariq Pervez Sattar, Sandra Dudley

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This paper describes the design process of a 200 MHz Ground Penetrating Radar (GPR) and a battery powered concrete vertical concrete surface climbing mobile robot. The key design feature is a miniaturized 200 MHz dipole antenna using additional radiating arms and procedure records a reduction of 40% in length compared to a conventional antenna. The antenna set is mounted in front of the robot using a servo mechanism for folding and unfolding purposes. The robot’s adhesion mechanism to climb the reinforced concrete wall is based on neodymium permanent magnets arranged in a unique combination to concentrate and maximize the magnetic flux to provide sufficient adhesion force for GPR installation. The experiments demonstrated the robot’s capability of climbing reinforced concrete wall carrying the attached prototype GPR system and perform floor-to-wall transition and vice versa. The developed GPR’s performance is validated by its capability of detecting and localizing an aluminium sheet and a reinforcement bar (rebar) of 12 mm diameter buried under a test rig built of wood to mimic the concrete structure environment. The present robotic GPR system proves the concept of feasibility of undertaking inspection procedure on large concrete structures in hazardous environments that may not be accessible to human inspectors.

Keywords: climbing robot, dipole antenna, ground penetrating radar (GPR), mobile robots, robotic GPR

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Authors: Milton Ayoki, Edward Bbaale

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This paper analyses the relationship between innovation and employment at firm level with the objective of understanding the contribution of the different innovation strategies in fostering employment growth in Uganda. We use National Innovation Survey (micro-data of 705 Ugandan firms) for the period 2011-2014 and follow closely Harrison et al. (2014) structured approach, and relate employment growth to process innovations and to the growth of sales separately due to innovative and unchanged products. We find positive effects of product innovation on employment at firm level, while process innovation has no discernable impact on employment. Although there is evidence to suggest displacement of labour in some cases where firms only introduce new process, this effect is compensated by growth in employment from new products, which for most firms are introduced simultaneously with new process. Results suggest that source of innovation as well as size of innovating firms or end users of innovation matter for job growth. Innovation that develops from within the firm itself (user) and involving larger firms has greater impact on employment than that developed from outside or coming from within smaller firms. In addition, innovative firms are one and half times more likely to survive in the innovation driven economy environment than those that do not innovate. These results have important implications for policymakers and stakeholders in innovation ecosystem. Supporting policies need to be correctly tailored since the impacts depend on the innovation strategy (type) and characteristics and sector of the innovative firms (small, large, industry, etc.). Policies to spur investment, particularly in innovative sectors and firms with high growth potential would have long lasting effects on job creation. JEL Classification: D24, J0, J20, L20, O30.

Keywords: employment, process innovation, product innovation, Sub-Saharan Africa

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Authors: Ali A. Ukasha, Majdi F. Elbireki, Mohammad F. Abdullah

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Data security needed in data transmission, storage, and communication to ensure the security. This paper is divided into two parts. This work interests with the color image which is decomposed into red, green and blue channels. The blue and green channels are compressed using 3-levels discrete wavelet transform. The Arnold transform uses to changes the locations of red image channel pixels as image scrambling process. Then all these channels are encrypted separately using the key image that has same original size and are generating using private keys and modulo operations. Performing the X-OR and modulo operations between the encrypted channels images for image pixel values change purpose. The extracted contours from color images recovery can be obtained with accepted level of distortion using single step parallel contour extraction (SSPCE) method. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Color images and completely reconstructed without any distortion. Also shown that the analyzed algorithm has extremely large security against some attacks like salt and pepper and Jpeg compression. Its proof that the color images can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: SSPCE method, image compression and salt and peppers attacks, bitplanes decomposition, Arnold transform, color image, wavelet transform, lossless image encryption

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Authors: Adel. M. Sharaf, Foad H. Gandoman

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Nowadays, Photovoltaic-PV Farms/ Parks and large PV-Smart Grid Interface Schemes are emerging and commonly utilized in Renewable Energy distributed generation. However, PV-hybrid-Dc-Ac Schemes using interface power electronic converters usually has negative impact on power quality and stabilization of modern electrical network under load excursions and network fault conditions in smart grid. Consequently, robust FACTS based interface schemes are required to ensure efficient energy utilization and stabilization of bus voltages as well as limiting switching/fault onrush current condition. FACTS devices are also used in smart grid-Battery Interface and Storage Schemes with PV-Battery Storage hybrid systems as an elegant alternative to renewable energy utilization with backup battery storage for electric utility energy and demand side management to provide needed energy and power capacity under heavy load conditions. The paper presents a robust interface PV-Li-Ion Battery Storage Interface Scheme for Distribution/Utilization Low Voltage Interface using FACTS stabilization enhancement and dynamic maximum PV power tracking controllers. Digital simulation and validation of the proposed scheme is done using MATLAB/Simulink software environment for Low Voltage- Distribution/Utilization system feeding a hybrid Linear-Motorized inrush and nonlinear type loads from a DC-AC Interface VSC-6-pulse Inverter Fed from the PV Park/Farm with a back-up Li-Ion Storage Battery.

Keywords: AC FACTS, smart grid, stabilization, PV-battery storage, Switched Filter-Compensation (SFC)

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Authors: Michelle Odudu

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Ghana and Nigeria are known for their high levels of Occupational Fraud in public offices. The governments of both countries have emphasised their commitment to reducing the losses caused to the state by pledging their allegiance to the counter-fraud agencies to help tackle Occupational Fraud. Yet it seems that the prosecution of such cases is ineffective as high-profile fraudsters can operate with immunity and their cases remain unprosecuted. This research project was based on in-depth examinations of 50 occupational fraud cases involving high-profile individuals in both countries. In doing so, it established the characteristics of those who were prosecuted; the extent to which prosecutions were effectively managed; the barriers to effective prosecutions; and the similarities or differences between the occurrences in both countries. The aim of the project is to examine the practice of and barriers to prosecution of large-scale occupational fraud of those in senior public positions in Ghana and Nigeria. The study drew on the experiences of stakeholders such as defence and prosecution barristers, academics, and fraud analysts via semi-structured interviews and questionnaires. 13 interviews were conducted in Ghana and in Nigeria, where respondents were recruited using a snowball approach. Questionnaires were physically distributed: 20 of the staff at EOCO and 10 to NGO staff in Ghana; 6 and 5 came back, respectively. The empirical data collected suggests that there is no lack of will on the agencies’ part to at least commence proceedings. However, various impediments hamper a successful completion of prosecution. Challenges were more evident in Nigeria, where agencies are less effective at retrieving stolen assets and changing social norms. This is further compounded by several cultural and political factors, which create limitations leaving many cases ‘still pending’.

Keywords: comparative, prosecution, punishment, international, whitecollar, fraud

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Authors: Arwa Alzughaibi

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Human Motion detection is a challenging task due to a number of factors including variable appearance, posture and a wide range of illumination conditions and background. So, the first need of such a model is a reliable feature set that can discriminate between a human and a non-human form with a fair amount of confidence even under difficult conditions. By having richer representations, the classification task becomes easier and improved results can be achieved. The Aim of this paper is to investigate the reliable and accurate human motion detection models that are able to detect the human motions accurately under varying illumination levels and backgrounds. Different sets of features are tried and tested including Histogram of Oriented Gradients (HOG), Deformable Parts Model (DPM), Local Decorrelated Channel Feature (LDCF) and Aggregate Channel Feature (ACF). However, we propose an efficient and reliable human motion detection approach by combining Histogram of oriented gradients (HOG) and local phase quantization (LPQ) as the feature set, and implementing search pruning algorithm based on optical flow to reduce the number of false positive. Experimental results show the effectiveness of combining local phase quantization descriptor and the histogram of gradient to perform perfectly well for a large range of illumination conditions and backgrounds than the state-of-the-art human detectors. Areaunder th ROC Curve (AUC) of the proposed method achieved 0.781 for UCF dataset and 0.826 for CDW dataset which indicates that it performs comparably better than HOG, DPM, LDCF and ACF methods.

Keywords: human motion detection, histograms of oriented gradient, local phase quantization, local phase quantization

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Authors: Zahid Mahmood

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Mental health problems in adolescents are said to be increasing tremendously, and a large proportion of adolescents are suffering from serious mental health problems that result in short and long term socio-emotional negative consequences. Contemporary clinical and school psychology is now focused on prevention rather than intervene in the mental health concerns of adolescents. Therefore, a wealth of literature is devoted to identify the risk and protective factors so that adolescents may be prevented and identified earlier. This quest has led to identify many risk factors including the early parent-child relationship. Parenting has a long last impact on the growth and development of an individual. If the parent-child relationship is secure and warm, the child tends to have a positive psychological outcome. On the other hand, if parenting is rejecting and distant, it may lead to more mental health problems. Keeping in view the cross-cultural influence of parenting, the current study was aimed to explore the relationship between parental rearing practices and mental health problems on a group of Pakistani adolescents. A sample of 805 participants (49% boys and 51% girls) were selected through a stratified sample with the age range of 13-18 years. All the participants were given protocol of EMBU-C and School Children Problem Scale (SCPS). Results indicate that age, the gender of the participant and parental rejection were found to be a significant positive predictor of mental health problems in adolescents. It can be concluded that parenting may be a universal phenomenon comprising rejection and acceptance yet the differential impact on mental health varies from culture to culture.

Keywords: parenting, mental health, adolescents, cross cultural

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Authors: S. Rajeswari

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Medicinal Plant extracts and their bioactive compounds have been used for antimicrobial activities and have significant remedial properties. In the recent years, a wide range of investigations have been carried out throughout the world to confirm antimicrobial properties of different medicinally important plants. A number of plants showed efficient antimicrobial activities, which were comparable to that of synthetic standard drugs or antimicrobial agents. The large family Euphorbiaceae contains nearly about 300 genera and 7,500 speciesand one among is Ricinus communis or castor plant which has high traditional and medicinal value for disease free healthy life. Traditionally the plant is used as laxative, purgative, fertilizer and fungicide etc. whereas the plant possess beneficial effects such as anti-oxidant, antihistamine, antinociceptive, antiasthmatic, antiulcer, immunomodulatory anti diabetic, hepatoprotective, anti inflammatory, antimicrobial, and many other medicinal properties. This activity of the plant possess due to the important phytochemical constituents like flavonoids, saponins, glycosides, alkaloids and steroids. The presents study includes the phytochemical properties of Ricinus communis and to prediction of the anti-microbial activity of Ricinus communis using DNA gyrase of Staphylococcus aureus as molecular target. Docking results of varies chemicals compounds of Ricinus communis against DNA gyrase of Staphylococcus aureus by maestro 9.8 of Schrodinger show that the phytochemicals are effective against the target protein DNA gyrase. our studies suggest that the phytochemical from Ricinus communis such has INDICAN (G.Score 4.98) and SUPLOPIN-2(G.Score 5.74) can be used as lead molecule against Staphylococcus infections.

Keywords: euphorbiaceae, antimicrobial activity, Ricinus communis, Staphylococcus aureus

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Authors: Hyun Seop Uhm, Yong Ho Choi, Ji Eun Kim, Young Hoon Lee

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Weapon-target assignment (WTA) is a problem that assigns available launchers to appropriate targets in order to defend assets. Various algorithms for WTA have been developed over past years for both in the static and dynamic environment (denoted by SWTA and DWTA respectively). Due to the problem requirement to be solved in a relevant computational time, WTA has suffered from the solution efficiency. As a result, SWTA and DWTA problems have been solved in the limited situation of the battlefield. In this paper, the general situation under continuous time is considered by Time based Weapon Target Assignment (TWTA) problem. TWTA are studied using the mixed integer programming model, and three heuristic algorithms; decomposed opt-opt, decomposed opt-greedy, and greedy algorithms are suggested. Although the TWTA optimization model works inefficiently when it is characterized by a large size, the decomposed opt-opt algorithm based on the linearization and decomposition method extracted efficient solutions in a reasonable computation time. Because the computation time of the scheduling part is too long to solve by the optimization model, several algorithms based on greedy is proposed. The models show lower performance value than that of the decomposed opt-opt algorithm, but very short time is needed to compute. Hence, this paper proposes an improved method by applying decomposition to TWTA, and more practical and effectual methods can be developed for using TWTA on the battlefield.

Keywords: air and missile defense, weapon target assignment, mixed integer programming, piecewise linearization, decomposition algorithm, military operations research

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Authors: Zhao Cai-qi, Ma Jun

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Twin steel plates-concrete composite shear walls are composed of a pair of steel plate layers and a concrete layer sandwiched between them, which have the characteristics of both reinforced concrete shear walls and steel plate shear walls. Twin steel plates-composite shear walls contain very high ultimate bearing capacity and ductility, which have great potential to be applied in the super high-rise buildings and special structures. In this paper, we analyzed the basic characteristics and stress mechanism of the twin steel plates-composite shear walls. Specifically, we analyzed the effects of the steel plate thickness, wall thickness and concrete strength on the bearing capacity of the twin steel plates-composite shear walls. The analysis results indicate that：（1）the initial shear stiffness and ultimate shear-carrying capacity is not significantly affected by the thickness of concrete wall but by the class of concrete,（2）both factors significantly impact the shear distribution of the shear walls in ultimate shear-carrying capacity. The technique of twin steel plates-composite shear walls has been successfully applied in the construction of a 88-meter Huge Statue of Buddha located in Hunan Province, China. The analysis results and engineering experiences showed that the twin steel plates-composite shear walls have great potential for future research and applications.

Keywords: twin steel plates-concrete composite shear wall, huge statue of Buddha, shear capacity, initial lateral stiffness, overturning moment bearing

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Authors: Seokyoon Moon, Yun-Ho Ahn, Heejoong Kim, Sujin Hong, Yunseok Lee, Youngjune Park

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Gas hydrate is a non-stoichiometric crystalline compound consisting of host water-framework and low molecular weight guest molecules. Small gaseous molecules such as CH₄, CO₂, and N₂ can be captured in the host water framework lattices of the gas hydrate with specific temperature and pressure conditions. The three well-known crystal structures of structure I (sI), structure II (sII), and structure H (sH) are determined by the size and shape of guest molecules. In this study, we measured the phase equilibria of binary (2,2-dimethyl-1-propanol + CO₂, CH₄, N₂) hydrates to explore their fundamental thermodynamic characteristics. We identified the structure of the binary gas hydrate by employing synchrotron high-resolution powder diffraction (HRPD), and the guest distributions in the lattice of gas hydrate were investigated via dispersive Raman and ¹³C solid-state nuclear magnetic resonance (NMR) spectroscopies. The end-to-end distance of 2,2-dimethyl-1-propanol was calculated to be 7.76 Å, which seems difficult to be enclathrated in large cages of sI or sII. However, due to the flexibility of the host water framework, binary hydrates of sI or sII types can be formed with the help of small gas molecule. Also, the synchrotron HRPD patterns revealed that the binary hydrate structure highly depends on the type of help gases; a cubic Fd3m sII hydrate was formed with CH₄ or N₂, and a cubic Pm3n sI hydrate was formed with CO₂. Interestingly, dispersive Raman and ¹³C NMR spectra showed that the unique tuning phenomenon occurred in binary (2,2-dimethyl-1-propanol + CO₂) hydrate. By optimizing the composition of NPA, we can achieve both thermodynamic stability and high CO₂ storage capacity for the practical application to CO₂ capture.

Keywords: clathrate, gas hydrate, neopentyl alcohol, CO₂, tuning phenomenon

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Authors: Dylber Qema

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Driven by recent developments in technology and the growing concern about the sustainability and environmental impact of conventional fuel use, the possibility of producing clean and sustainable energy in significant quantities from renewable energy sources has sparked interest all over the world. Solar energy is one of the sources for the generation of electricity, with no emissions or environmental pollution. The electricity produced by photovoltaics can supply a home or business and can even be sold or exchanged with the grid operator. A very positive effect of using photovoltaic modules is that they do not produce greenhouse gases and do not produce chemical waste, unlike all other forms of energy production. Photovoltaics are becoming one of the largest investments in the field of renewable generating units. Improving the reliability of the electric power system is one of the most important impacts of the installation of photovoltaics (PV). Renewable energy sources are so large that they can meet the energy demands of the whole world, thus enabling sustainable supply as well as reducing local and global atmospheric emissions. Albania is rated by experts as one of the most favorable countries in Europe for the production of electricity from solar panels. But the country currently produces about 1% of its energy from the sun, while the rest of the needs are met by hydropower plants and imports. Albania has very good characteristics in terms of solar radiation (about 1300–1400 kW/m2). Solar energy has great potential and is a permanent source of energy with greater economic efficiency. Photovoltaic energy is also seen as an alternative, as long periods of drought in Albania have produced crises and high costs for securing energy in the foreign market.

Keywords: capacity, ministry of tourism and environment, obstacles, photovoltaic energy, sustainable

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Authors: Zhang Lei, Zhao Qingrong, Wang Chen, Zhang Sufang, Zhang Hanguo

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Larch is the main afforestation and timber tree species in Northeast China, and drought is one of the main factors limiting the growth of Larch and other organisms in Northeast China. In order to further explore the mechanism of Larch drought resistance, PEG was used to simulate drought stress. The full-length sequencing of Larch embryogenic callus under PEG simulated drought stress was carried out by combining Illumina-Hiseq and SMRT-seq. A total of 20.3Gb clean reads and 786492 CCS reads were obtained from the second and third generation sequencing. The de-redundant transcript sequences were predicted by lncRNA, 2083 lncRNAs were obtained, and the target genes were predicted, and a total of 2712 target genes were obtained. The de-redundant transcripts were further screened, and 1654 differentially expressed genes (DEGs )were obtained. Among them, different DEGs respond to drought stress in different ways, such as oxidation-reduction process, starch and sucrose metabolism, plant hormone pathway, carbon metabolism, lignin catabolic/biosynthetic process and so on. This study provides basic full-length sequencing data for the study of Larch drought resistance, and excavates a large number of DEGs in response to drought stress, which helps us to further understand the function of Larch drought resistance genes and provides a reference for in-depth analysis of the molecular mechanism of Larch drought resistance.

Keywords: larch, drought stress, full-length transcriptome sequencing, differentially expressed genes

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Authors: Lingfei Sun

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Based on the significant value of ecology, the strategic planning for ecological civilization construction was mentioned in the 17th and 18th National Congress of the Communist Party of China. How to generate economic value based on the environmental capacity is not only an economic decision but also a political decision to make. Boshan took the full use of “Ecology” and transformed it as an inexhaustible green resource to benefit people, reflecting the sustainable value of new agriculture development mode. The Strawberry Harvest Festival and Blueberry Harvest Festival hosted approximately 96,000 and 54,000 leisure tourists respectively in 2014. For the Kiwi Harvest Festival in August 2014, in average, it attracted about 4600 tourists per day, which generated daily kiwi sales of 50,000 lbs and 3 million RMB (About 476,000 USD) of daily revenue. The purpose of this study is to elaborate the modes of agritourism development, by analyzing the cases in rural area of Boshan, China. Interviews with the local government officers were applied to discover operation mode of agritourism operation. The financial data was used to demonstrate the strength of government policy and improvement of the income of rural people. The result indicated that there are mainly three types of modes: the Intensive Mode, the Model Mode and the Mixed Mode, supported by case study respectively. With the boom of tourism, the development of agritourism in Boshan relies on the agriculture encouraging policy of China and the effort of local government; meanwhile, large scale of cultivation and the product differentiation are the crucial elements for the success of rural agritourism projects.

Keywords: agriculture, agritourism, economy, rural area development

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Authors: Vivek Ku, A. K. Janmeja, D. Aggarwal, R. Gupta

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Purpose: Pulmonary rehabilitation plays a key role in management of chronic lung diseases. However, pulmonary rehabilitation is an underused modality in the management of interstitial lung disease (ILD). This is because limited information is available in literature and no data is available from India on this issue so far. The study was carried out to evaluate the role of pulmonary rehabilitation on respiratory parameters in ILD patients. Methods: The present study was a prospective randomized non-blind case control study. Total of 40 ILD patients were randomized into 2 groups of 20 patients each viz ‘pulmonary rehabilitation group’ and ‘control group’. Pulmonary rehabilitation group underwent 8 weeks pulmonary rehabilitation (PR) along with medical management as per guidelines and the control group was advised only medical management. Results: Mean age in case group was 59.15 ± 10.39 years and in control group was 62.10 ± 14.54 years. The case and the control groups were matched for age and sex. Mean MRC grading at the end of 8 weeks showed significant improvement in the case group as compared to control group (p= 0.011 vs p = 0.655). Similarly, mean St. George Respiratory Questionnaire (SGRQ) score also showed significant improvement in pulmonary rehabilitation group at the end of the study (p= 0.001 vs p= 0.492). However, FEV1 and FVC had no significant change in the case and control group. Similarly, blood gases also did not show any significant difference in the group. Conclusion: Pulmonary rehabilitation improves breathlessness and thereby improves quality of life in the patients suffering from ILD. However, the pulmonary function values and blood gases are unaffected by pulmonary rehabilitation. Clinical Implications: Further large scale multicentre study is needed to ascertain the association.

Keywords: ILD, pulmonary rehabilitation, quality of life, pulmonary functions

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Authors: Parth Mehta, Vedasri Bai Khavala, Prabhu Rajagopal, Tiju Thomas

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There is an increasing need for alternative clean fuels, and hydrogen (H₂) has long been considered a promising solution with a high calorific value (142MJ/kg). However, the storage of H₂ and expensive processes for its generation have hindered its usage. Sodium borohydride (NaBH₄) can potentially be used as an economically viable means of H₂ storage. Thus far, there have been attempts to optimize the life of NaBH₄ (half-life) in aqueous media by stabilizing it with sodium hydroxide (NaOH) for various pH values. Other reports have shown that H₂ yield and reaction kinetics remained constant for all ratios of H₂O to NaBH₄ > 30:1, without any acidic catalysts. Here we highlight the importance of pH and H₂O: NaBH₄ ratio (80:1, 40:1, 20:1 and 10:1 by weight), for NaBH₄ stabilization (half-life reaction time at room temperature) and corrosion minimization of H₂ reactor components. It is interesting to observe that at any particular pH>10 (e.g., pH = 10, 11 and 12), the H₂O: NaBH₄ ratio does not have the expected linear dependence with stability. On the contrary, high stability was observed at the ratio of 10:1 H₂O: NaBH₄ across all pH>10. When the H₂O: NaBH₄ ratio is increased from 10:1 to 20:1 and beyond (till 80:1), constant stability (% degradation) is observed with respect to time. For practical usage (consumption within 6 hours of making NaBH₄ solution), 15% degradation at pH 11 and NaBH₄: H₂O ratio of 10:1 is recommended. Increasing this ratio demands higher NaOH concentration at the same pH, thus requiring a higher concentration or volume of acid (e.g., HCl) for H₂ generation. The reactions are done with tap water to render the results useful from an industrial standpoint. The observed stability regimes are rationalized based on complexes associated with NaBH₄ when solvated in water, which depend sensitively on both pH and NaBH₄: H₂O ratio.

Keywords: hydrogen, sodium borohydride, stability optimization, H₂O:NaBH₄ ratio

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Authors: E. S. Kozlyakova, A. A. Eliseev, A. V. Moskin, A. Y. Akhrorov, P. S. Berdonosov, V. A. Dolgikh, K. N. Denisova, P. Lemmens, B. Rahaman, S. Das, T. Saha-Dasgupta, A. N. Vasiliev, O. S. Volkova

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Considerable attention has been paid recently to FeTe₂O₅Cl due to reduced dimensionality and frustration in the magnetic subsystem, succession of phase transitions, and multiferroicity. The efforts to grow its selenite sibling resulted in mixed halide compound, Fe(Te₁.₅Se₀.₅)O₅Cl, which was found crystallizing in a new structural type and possessing properties drastically different from those of a parent system. Hereby we report the studies of magnetization M and specific heat Cₚ, combined with Raman spectroscopy and density functional theory calculations in Fe(Te₁.₅Se₀.₅)O₅Cl. Its magnetic subsystem features weakly coupled Fe³⁺ - Fe³⁺ dimers showing the regime of short-range correlations at TM ~ 70 K and long-range order at TN = 22 K. In a magnetically ordered state, sizable spin-orbital interactions lead to a small canting of Fe³⁺ moments. The density functional theory calculations of leading exchange interactions were found in agreement with measurements of thermodynamic properties and Raman spectroscopy. Besides, because of the relatively large magnetic moment of the Fe³⁺ ion, we found that magnetic dipole-dipole interactions contribute significantly to experimentally observed orientation of magnetization easy axis in ac-plane. As a conclusion, we suggest a model of magnetic subsystem in magnetically ordered state of Fe(Te₁.₅Se₀.₅)O₅Cl based on a model of interacting dimers.

Keywords: dipole-dipole interactions, low dimensional magnetism, selenite, spin canting

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Authors: Eğinç Simay Ertürk, Ferhan Gezi̇ci̇

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The decline of large cities and the rise of second-tier cities have been observed as a global trend with significant implications for economic development and urban planning. In this context, the concepts of agglomeration shadow and borrowed size have gained importance as network externalities that affect the growth and development of surrounding areas. Istanbul, Izmir, and Ankara are Turkey's most significant metropolitan cities and play a significant role in the country's economy. The surrounding cities rely on these metropolitan cities for economic growth and development. However, the concentration of resources and investment in a single location can lead to agglomeration shadows in the surrounding areas. On the other hand, network connectivity between metropolitan and second-tier cities can result in borrowed function and performance, enabling smaller cities to access resources, investment, and knowledge they would not otherwise have access. The study hypothesizes that the network connectivity between second-tier and metropolitan cities in Turkey enables second-tier cities to increase their urban performance by borrowing size through these networks. Regression analysis will be used to identify specific network connectivity parameters most strongly associated with urban performance. Network connectivity will be measured with parameters such as transportation nodes and telecommunications infrastructure, and urban performance will be measured with an index, including parameters such as employment, education, and industry entrepreneurship, with data at the province levels. The contribution of the study lies in its research on how networking can benefit second-tier cities in Turkey.

Keywords: network connectivity, borrowed size, agglomeration shadow, secondary cities

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Authors: Yakui Bai, Chen Sun, Ke Wang

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An experimental investigation of environmental effect on fatigue behavior in SA508 Gr.3 Cl.2 Steam Generator Forging CAP1400 nuclear power plant has been carried out. In order to simulate actual loading condition, a range of strain amplitude was applied in different low cycle fatigue (LCF) tests. The current American Society of Mechanical Engineers (ASME) design fatigue code does not take full account of the interactions of environmental, loading, and material's factors. A range of strain amplitude was applied in different low cycle fatigue (LCF) tests at a strain rate of 0.01%s⁻¹. A design fatigue model was constructed by taking environmentally assisted fatigue effects into account, and the corresponding design curves were given for the convenience of engineering applications. The corrosion fatigue experiment was performed in a strain control mode in 320℃ borated and lithiated water environment to evaluate the effects of a mixed environment on fatigue life. Stress corrosion cracking (SCC) in steam generator large forging in primary water of pressurized water reactor was also observed. In addition, it is found that the CF life of SA508 Gr.3 Cl.2 decreases with increasing temperature in the water environment. The relationship between the reciprocal of temperature and the logarithm of fatigue life was found to be linear. Through experiments and subsequent analysis, the mechanisms of reduced low cycle fatigue life have been investigated for steam generator forging.

Keywords: failure behavior, low alloy steel, steam generator forging, stress corrosion cracking

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Authors: John Gibbs, Benjamin Flanders, Dylan Pozorski, Weixuan Liu

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Weight Painting–adjusting the influence a skeletal joint has on a given vertex in a character mesh–is an arduous and time con- suming part of the 3D animation pipeline. This process generally requires a trained technical animator and many hours of work to complete. Our skiNNer plug-in, which works within Autodesk’s Maya 3D animation software, uses Machine Learning and data pro- cessing techniques to create a deep neural network model that can accomplish the weight painting task in seconds rather than hours for bipedal quasi-humanoid character meshes. In order to create a properly trained network, a number of challenges were overcome, including curating an appropriately large data library, managing an arbitrary 3D mesh size, handling arbitrary skeletal architectures, accounting for extreme numeric values (most data points are near 0 or 1 for weight maps), and constructing an appropriate neural network model that can properly capture the high frequency alter- ation between high weight values (near 1.0) and low weight values (near 0.0). The arrived at neural network model is a cross between a traditional CNN, deep residual network, and fully dense network. The resultant network captures the unusually hard-edged features of a weight map matrix, and produces excellent results on many bipedal models.

Keywords: 3d animation, animation, character, rigging, skinning, weight painting, machine learning, artificial intelligence, neural network, deep neural network

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Authors: Masood Varshosaz, Kamyar Hasanpour

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In recent years, we have seen growing interest in recognizing humans in drone images for post-disaster search and rescue operations. Deep learning algorithms have shown great promise in this area, but they often require large amounts of labeled data to train the models. To keep the data acquisition cost low, augmentation techniques can be used to create additional data from existing images. There are many techniques of such that can help generate variations of an original image to improve the performance of deep learning algorithms. While data augmentation is potentially assumed to improve the accuracy and robustness of the models, it is important to ensure that the performance gains are not outweighed by the additional computational cost or complexity of implementing the techniques. To this end, it is important to evaluate the impact of data augmentation on the performance of the deep learning models. In this paper, we evaluated the most currently available 2D data augmentation techniques on a standard convolutional network which was trained for recognizing humans in drone images. The techniques include rotation, scaling, random cropping, flipping, shifting, and their combination. The results showed that the augmented models perform 1-3% better compared to a base network. However, as the augmented images only contain the human parts already visible in the original images, a new data augmentation approach is needed to include the invisible parts of the human body. Thus, we suggest a new method that employs simulated 3D human models to generate new data for training the network.

Keywords: human recognition, deep learning, drones, disaster mitigation

Procedia PDF Downloads 76