Search results for: supply chain optimization

Authors: Ammara Mehmood, Aneela Zameer, Muhammad Asif Zahoor Raja, Muhammad Faisal Fateh

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In this work, the strength of bio-inspired computational intelligence based technique is exploited for parameter estimation for the periodic signals using Continuous Differential Evolution (CDE) by defining an error function in the mean square sense. Multidimensional and nonlinear nature of the problem emerging in sinusoidal signal models along with noise makes it a challenging optimization task, which is dealt with robustness and effectiveness of CDE to ensure convergence and avoid trapping in local minima. In the proposed scheme of Continuous Differential Evolution based Signal Parameter Estimation (CDESPE), unknown adjustable weights of the signal system identification model are optimized utilizing CDE algorithm. The performance of CDESPE model is validated through statistics based various performance indices on a sufficiently large number of runs in terms of estimation error, mean squared error and Thiel’s inequality coefficient. Efficacy of CDESPE is examined by comparison with the actual parameters of the system, Genetic Algorithm based outcomes and from various deterministic approaches at different signal-to-noise ratio (SNR) levels.

Keywords: parameter estimation, bio-inspired computing, continuous differential evolution (CDE), periodic signals

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Authors: Hamsini Pulugurtha, V.S. Lakshmi Jagadmaba Paluri

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Distributed denial of service attack (DDoS) is one altogether the top-rated cyber threats presently. It runs down the victim server resources like a system of measurement and buffer size by obstructing the server to supply resources to legitimate shoppers. Throughout this text, we tend to tend to propose a mathematical model of DDoS attack; we discuss its relevancy to the choices like inter-arrival time or rate of arrival of the assault customers accessing the server. We tend to tend to further analyze the attack model in context to the exhausting system of measurement and buffer size of the victim server. The projected technique uses an associate in nursing unattended learning technique, self-organizing map, to make the clusters of identical choices. Lastly, the abstract applies mathematical correlation and so the standard likelihood distribution on the clusters and analyses their behaviors to look at a DDoS attack. These systems not exclusively interconnect very little devices exchanging personal data, but to boot essential infrastructures news standing of nuclear facilities. Although this interconnection brings many edges and blessings, it to boot creates new vulnerabilities and threats which might be conversant in mount attacks. In such sophisticated interconnected systems, the power to look at attacks as early as accomplishable is of paramount importance.

Keywords: application attack, bandwidth, buffer correlation, DDoS distribution flooding intrusion layer, normal prevention probability size

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Authors: Chukwukelue Uzodinma Umenyilorah

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The history of the crises in Niger-Delta is readily traceable to the post-colonial oil boom of the early 70s. Prior to this time, it was widely believed that the people of Niger-Delta; especially those in the present day Rivers, Delta and Bayelsa States enjoyed a peaceful coexistence pretty much as the rest of Nigerians. In the early 70s however, crude oil was discovered in commercial quantities in these areas and tranquility has become a far cry over the years ever since then. First, a number of multi-national oil explorers moved into the Niger-Delta for business, and then certain conditions resulted in sundry instances of oil spillage, which caused a lot of environmental damage, destroying nearly all of the people’s sources of livelihood. The result was a multiple chain reaction ranging from incessant agitations from the natives to institutionalized dialogue between the oil business owners, the natives and the government, and then to a proposition of compensation packages for the affected communities. The said compensation, which was meant to bring peace seem to have brought even more crises instead. Corruption and greed crept in, money changed hands, suffering increased and so was the agitation from the people. The whole turn of events gradually snowballed into the formation of various militant groups who are now fingered as responsible for the sundry cases of violence in the Niger-Delta. The oil boom can, therefore, be said to be the immediate cause of the Niger-Delta crises, but there are other remote causes as well; including poverty, neglect and illiteracy to mention but a few. This study is therefore aimed at examining the various reasons behind the seemingly unending crises in the Niger-Delta. It will also take a critical look at the roles played by the various parties in the Niger-Delta crises from the 70s to date; as well as the various human and environmental devastations done in the area with a view to making informed suggestions on how to stop further damage and start fixing that, which is already done. Esiaba Irobi’s Cemetery Road and Hangmen Also Die seem to vividly capture the realities of the Niger-Delta situation, and shall, therefore, be reviewed in this study.

Keywords: corruption, Niger-delta, oil boom, post-colonial

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Authors: Mohammadreza Heydariazad

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Productivity growth of wind energy as a clean source needed to achieve improved strategy in production and transmission and management of wind resources in order to increase quality of power and reduce costs. New technologies based on power converters that cause changing turbine speed to suit the wind speed blowing turbine improve extraction efficiency power from wind. This article introduces variable speed wind turbines and optimization of power, and presented methods to use superconducting inductor in the composition of power converter and is proposed the dc measurement for the wind farm and especially is considered techniques available to them. In fact, this article reviews mechanisms and function, changes of wind speed turbine according to speed control strategies of various types of wind turbines and examines power possible transmission and ac from producing location to suitable location for a strong connection integrating wind farm generators, without additional cost or equipment. It also covers main objectives of the dynamic control of wind turbines, and the methods of exploitation and the ways of using it that includes the unique process of these components. Effective algorithm is presented for power control in order to extract maximum active power and maintains power factor at the desired value.

Keywords: wind energy, generator, superconducting inductor, wind turbine power

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Authors: Pedro F. D. Oliveira, Rangel S. Maia, Aline S. Paula

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As the electric energy consumption grows, the necessity of energy transmission lines increases. One of the problems caused by an oscillatory response to dynamical loads (such as wind effects) in transmission lines is the cable fatigue. Thus, the dynamical behavior of transmission cables understanding and its control is extremely important. The socioeconomic damage caused by a failure in these cables can be quite significant, from large economic losses to energy supply interruption in large regions. Dynamic Vibration Absorbers (DVA) are oscillatory elements used to mitigate the vibration of a primary system subjected to harmonic excitation. The positioning of Stockbridge (DVA for overhead transmission lines) plays an important role in mitigating oscillations of transmission lines caused by airflows. Nowadays, the positioning is defined by technical standards or commercial software. The aim of this paper is to conduct an analysis of multiple DVAs performances in cable conductors of overhead transmission lines. The cable is analyzed by a finite element method and the model is calibrated by experimental results. DVAs performance is analyzed by evaluating total cable energy, and a study of multiple DVAs positioning is conducted. The results are compared to the existing regulations showing situations where proper positioning, different from the standard, can lead to better performance of the DVA. Results also show situations where the use of multiple DVAs is appropriate.

Keywords: dynamical vibration absorber, finite element method, overhead transmission lines, structural dynamics

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Authors: Alireza Abbassi Monjezi, Mohammad Hasan Shaheed

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Flood, caused by excessive rainfall, monsoon, cyclone and tsunami is a common disaster in many countries of the world especially sea connected low-lying countries. A stand-alone self-powered water filtration module for decontamination of floodwater has been designed and modeled. A combination forward osmosis – low pressure reverse osmosis (FO-LPRO) system powered by solar photovoltaic-thermal (PVT) energy is investigated which could overcome the main barriers to water supply for remote areas and ensure off-grid filtration. The proposed system is designed to be small scale and portable to provide on-site potable water to communities that are no longer themselves mobile nor can be reached quickly by the aid agencies. FO is an osmotically driven process that uses osmotic pressure gradients to drive water across a controlled pore membrane from a feed solution (low osmotic pressure) to a draw solution (high osmotic pressure). This drops the demand for high hydraulic pressures and therefore the energy demand. There is also a tendency for lower fouling, easier fouling layer removal and higher water recovery. In addition, the efficiency of the PVT unit will be maximized through freshwater cooling which is integrated into the system. A filtration module with the capacity of 5 m3/day is modeled to treat floodwater and provide drinking water. The module can be used as a tool for disaster relief, particularly in the aftermath of flood and tsunami events.

Keywords: flood resilience, membrane desalination, portable water treatment, solar energy

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary condition to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful to study various optical phenomena.

Keywords: deep learning, optical Soliton, neural network, partial differential equation

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Authors: Abdelbasset Tounekti, Kamel Boukhalfa, Tathagata Roy Choudhury, Mohamed Soussi, Santanu Banerjee

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The exceptionally glauconite-rich Miocene strata are superbly exposed throughout the front of the nappes zone of northern Tunisia. Each of the glauconitic fine-grained intervals coincide with the peak rise of third order sea-level cycles during the Burdigalian-Langhiantime. These deposits show coarsening- and thickening-upward glauconitic shale and sandstone, recording a shallowing upward progression across offshore-shoreface settings. Petrographic investigation reveals that the glauconite was originated from the alteration of fecal pellets, and lithoclast including feldspar, volcanic particle, and quartz and infillings with intraparticle pores. Mineralogical analysis of both randomly oriented and air-dried, ethylene-glycolate, and heated glauconite pellets show the low intensity of (002) reflection peaks, indicating high iron substitution for aluminum in octahedral sites. Geochemical characterization of the Miocene glauconite reveals a high K2O and variable Fe2O3 (total) content. A combination of layer lattice and divertissement theories explains the origin of glauconite. The formation of glauconite was facilitated by the abundant supply of Fe through contemporaneous volcanism in Algeria and surrounding areas, which accompanied the African-European plate convergence. Therefore, the occurrence of glauconite in the Miocene succession of Tunisia is influenced by the combination of eustacy and volcanism.

Keywords: glauconite, autogenic, volcanism, geochemistry, chamosite, northern Tunisia, miocene

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Authors: Ajay Kumar Choubey, Geeta Agnihotri, C. Sasikumar, Rashmi Dwivedi

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Deep-drawing operations are performed widely in industrial applications. It is very important for efficiency to achieve parts with no or minimum defects. Deep drawn parts are used in high performance, high strength and high reliability applications where tension, stress, load and human safety are critical considerations. Wrinkling is a kind of defect caused by stresses in the flange part of the blank during metal forming operations. To avoid wrinkling appropriate blank-holder pressure/force or drawbead can be applied. Now-a-day computer simulation plays a vital role in the field of manufacturing process. So computer simulation of manufacturing has much advantage over previous conventional process i.e. mass production, good quality of product, fast working etc. In this study, a two dimensional elasto-plastic Finite Element (F.E.) model for Mild Steel material blank has been developed to study the behavior of the flange wrinkling and deep drawing parameters under different Blank-Holder Pressure (B.H.P.). For this, commercially available Finite Element software ANSYS 14 has been used in this study. Simulation results are critically studied and salient conclusions have been drawn.

Keywords: ANSYS, deep drawing, BHP, finite element simulation, wrinkling

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Authors: Halison da Silva Pereira, Ciro Sobrinho Campolina Martins, Vitor Mainenti Leal Lopes

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Long range performance is a goal for aircraft configuration optimization. Blended Wing Body (BWB) is presented in many works of literature as the most aerodynamically efficient design for a fixed-wing aircraft. Because of its high weight to thrust ratio, BWB is the ideal configuration for many Unmanned Aerial Vehicle (UAV) missions on geomatics applications. In this work, a BWB aerodynamic design for typical light geomatics payload is presented. Aerodynamic non-dimensional coefficients are predicted using low Reynolds number computational techniques (3D Panel Method) and wing parameters like aspect ratio, taper ratio, wing twist and sweep are optimized for high cruise performance and flight quality. The methodology of this work is a summary of tailless aircraft wing design and its application, with appropriate computational schemes, to light UAV subjected to low Reynolds number flows leads to conclusions like the higher performance and flight quality of thicker airfoils in the airframe body and the benefits of using aerodynamic twist rather than just geometric.

Keywords: blended wing body, low Reynolds number, panel method, UAV

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Authors: Jinyan Li, Simon Fong, Raymond Wong, Mohammed Sabah, Fiaidhi Jinan

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Clinical data analysis and forecasting have make great contributions to disease control, prevention and detection. However, such data usually suffer from highly unbalanced samples in class distributions. In this paper, we target at the binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat-inspired algorithm, and combine both of them with the synthetic minority over-sampling technique (SMOTE) for processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reveal that while the performance improvements obtained by the former methods are not scalable to larger data scales, the later one, which we call Adaptive Swarm Balancing Algorithms, leads to significant efficiency and effectiveness improvements on large datasets. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. Leading to more credible performances of the classifier, and shortening the running time compared with the brute-force method.

Keywords: Imbalanced dataset, meta-heuristic algorithm, SMOTE, big data

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Authors: Aderonke Oluseun Akinwumi, Olusola A. Komolaf

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This paper gives information about the wide array of challenges facing both the electric utilities and consumers in the distribution system in developing countries, using Obafemi Awolowo University, Ile-Ife Nigeria as a case study. It also proffers cost-effective solution through remote monitoring, diagnostic and operation of distribution networks without compromising the system reliability. As utilities move from manned and unintelligent networks to completely unmanned smart grids, switching activities at substations and feeders will be managed and controlled remotely by dedicated systems hence this design. The Substation Remote Diagnostic and Operation Solution (sRDOs) would remotely monitor the load on Medium Voltage (MV) and Low Voltage (LV) feeders as well as distribution transformers and allow the utility disconnect non-paying customers with absolutely no extra resource deployment and without interrupting supply to paying customers. The aftermath of the implementation of this design improved the lifetime of key distribution infrastructure by automatically isolating feeders during overload conditions and more importantly erring consumers. This increased the ratio of revenue generated on electricity bills to total network load.

Keywords: electric utility, consumers, remote monitoring, diagnostic, system reliability, manned and unintelligent networks, unmanned smart grids, switching activities, medium voltage, low voltage, distribution transformer

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Authors: Tahira Hyder, Saima Quraeshi, Zohaib Akram

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Salvadora Persica (SP) is known to have anti-inflammatory, antioxidant, anti-coagulant and anti-bacterial properties that may provide therapeutic benefits in the treatment of chronic periodontitis (CP). The current clinical trial was designed to investigate the clinical and anti-microbial effects of SP gel as an adjunct to scaling and root planning (SRP) in subjects with generalized CP. Sixty-six subjects with CP were randomized allocated into two groups: SRP + SP gel (test group) and SRP only (control group). Clinical parameters (periodontal pocket depth, gingival recession, clinical attachment level, bleeding score and plaque score) were recorded at baseline before SRP and at 6 weeks. At baseline and 6 weeks subgingival plaque samples were collected and periodontopathogen Porphyromonas Gingivalis (Pg) quantified using Real-time Polymerase Chain Reaction (RT-PCR). Both therapies reduced the mean periodontal pocket depth (PPD), plaque score (PS) and bleeding score (BOP) and improved the mean clinical attachment level (CAL) between baseline and 6 weeks. In subjects receiving adjunctive SP gel a statistically significant improvement was observed in BOP at follow-up compared to control group (15.01±3.47% and 22.81±6.81% respectively, p=0.001), while there was no statistically significant difference in periodontal pocket depth, gingival recession, clinical attachment level and plaque score between both groups. The test group displayed significantly greater Pg reduction compared to the control group after 6 weeks. The current study establishes that local delivery of SP gel into periodontal pocket in CP stimulated a significant reduction in bacteria Pg level and an improvement in gingival health, as evident from a reduced bleeding score, when used as an adjunct to SRP.

Keywords: miswak, scaling and root planing, porphyromonas gingivalis, chronic periodontitis

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Authors: Volker Koch, Sigrid Swobodnik, Bernd M. Zunk

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The success of companies on globalized markets is significantly influenced by the performance of purchasing departments and, of course, the individuals employed as professional purchasers. Nonetheless, this is generally accepted in practice, in literature as well as in empirical research, only insufficient attention was given to the assessment of this relationship between the personality of professional purchasers and their individual performance. This paper aims to describe the relationship against the background of the 'Big Five Inventory'. Based on the five dimensions of a personality (openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism) a research model was designed. The research model divides the individual performance of professional purchasers into two major dimensions: operational and strategic. The operational dimension consists of the items 'cost', 'quality delivery' and 'flexibility'; the strategic dimension comprises the positions 'innovation', 'supplier satisfaction' as wells as 'purchasing and supply management integration in the organization'. To test the research model, a survey study was performed, and an online questionnaire was sent out to purchasing professionals in Austrian companies. The data collected from 78 responses was used to test the research model applying a group comparison. The comparison points out that there is (i) an influence of the purchasers’ personality on the individual performance of professional purchasers and (ii) a link between purchasers’ personality to a high or a low individual performance of professional purchasers. The findings of this study may help human resource managers during staff recruitment processes to identify the 'right performing personality' for an operational and/or a strategic position in purchasing departments.

Keywords: big five inventory, individual performance, personality, purchasing professionals

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Authors: Lourdita Llanto

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This study described and assessed the implementation of artificial insemination (AI) for cattle and carabaos in the Bicol Region, Philippines: Albay, Sorsogon and Camarines Sur. Three hundred respondents were interviewed. Results were analyzed using frequency counts, means, percentages and chi-square test. Semen samples from different stations were analyzed for motility, viability and morphology. T-test was used in semen quality evaluation. Provincial AI coordinators (PAIC) were male, averaging 59 years old, married, had college education, served in government service for 34 years, but as PAIC for 5.7 years. All had other designations. Mean AI operation was 11.33 years with annual support from the local government unit of Php76,666.67. AI technicians were males, married, with college education, and trained on AI. Problems were on mobility; inadequate knowledge of farmers in animal raising and AI; and lack of liquid nitrogen and frozen semen supply. There was 2.95 municipalities and breedable cattle/carabaos of 3,091.25 per AI technician. Mean number of artificially inseminated animals per AI technician for 2011 was 28.57 heads for carabaos and 8.64 heads for cattle. There was very low participation rate among farmers. Carabaos were 6.52 years with parity 1.53. Cattle were 5.61 years, with parity of 1.51. Semen quality significantly (p ≤ 0.05) deteriorated in normal and live sperm with storage and handling at the provincial and field stations. Breed, AI technicians practices and AI operation significantly affected conception rate. Mean conception rate was 57.62%.

Keywords: artificial insemination, carabao, parity, mother tanks, frozen semen

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Authors: Erich Gomes Schaitza, Antônio Francisco Savi, Glaucia Aparecida Prates

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The penetration of renewable energy into the electricity supply in Brazil is high, one of the highest in the World. Centralized hydroelectric generation is the main source of energy, followed by biomass and wind. Surprisingly, mini and micro-generation are negligible, with less than 2,000 connections to the national grid. In 2015, a new regulatory framework was put in place to change this situation. In the agricultural sector, the framework was complemented by the offer of low interest rate loans to in-farm renewable generation. Brazil proposed to more than double its area of planted forests as part of its INDC- Intended Nationally Determined Contributions to the UNFCCC-U.N. Framework Convention on Climate Change (UNFCCC). This is an ambitious target which will be achieved only if forests are attractive to farmers. Therefore, this paper analyses whether planting forests for in-farm energy generation with a with a woodchip gasifier is economically viable for microgeneration under the new framework and at if they could be an economic driver for forest plantation. At first, a static case was analyzed with data from Eucalyptus plantations in five farms. Then, a broader analysis developed with the use of Monte Carlo technique. Planting short rotation forests to generate energy could be a viable alternative and the low interest loans contribute to that. There are some barriers to such systems such as the inexistence of a mature market for small scale equipment and of a reference network of good practices and examples.

Keywords: biomass, distribuited generation, small-scale, Monte Carlo

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Authors: D. S. Naumann, B. J. Evans, O. Hassan

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This paper outlines the development of an automated aerodynamic optimisation algorithm using a novel method of parameterising a computational mesh by employing user–defined control nodes. The shape boundary movement is coupled to the movement of the novel concept of the control nodes via a quasi-1D-linear deformation. Additionally, a second order smoothing step has been integrated to act on the boundary during the mesh movement based on the change in its second derivative. This allows for both linear and non-linear shape transformations dependent on the preference of the user. The domain mesh movement is then coupled to the shape boundary movement via a Delaunay graph mapping. A Modified Cuckoo Search (MCS) algorithm is used for optimisation within the prescribed design space defined by the allowed range of control node displacement. A finite volume compressible NavierStokes solver is used for aerodynamic modelling to predict aerodynamic design fitness. The resulting coupled algorithm is applied to a range of test cases in two dimensions including the design of a subsonic, transonic and supersonic intake and the optimisation approach is compared with more conventional optimisation strategies. Ultimately, the algorithm is tested on a three dimensional wing optimisation case.

Keywords: mesh movement, aerodynamic shape optimization, cuckoo search, shape parameterisation

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Authors: Kaushik Sathupadi, Sandesh Achar

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Human action recognition modeling is a critical task in machine learning. These systems require better techniques for recognizing body parts and selecting optimal features based on vision sensors to identify complex action patterns efficiently. Still, there is a considerable gap and challenges between images and videos, such as brightness, motion variation, and random clutters. This paper proposes a robust approach for classifying human actions over cloud-based image data. First, we apply pre-processing and detection, human and outer shape detection techniques. Next, we extract valuable information in terms of cues. We extract two distinct features: fuzzy local binary patterns and sequence representation. Then, we applied a greedy, randomized adaptive search procedure for data optimization and dimension reduction, and for classification, we used a random forest. We tested our model on two benchmark datasets, AAMAZ and the KTH Multi-view football datasets. Our HMR framework significantly outperforms the other state-of-the-art approaches and achieves a better recognition rate of 91% and 89.6% over the AAMAZ and KTH multi-view football datasets, respectively.

Keywords: computer vision, human motion analysis, random forest, machine learning

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Authors: John Ahluwalia

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As an affluent first-world nation, Canada took swift and comprehensive action during the outbreak of the SARS-CoV-2 (COVID-19) pandemic compared to other countries in the same socio-economic cohort. The United States has stumbled to overcome obstacles most developed nations have faced, which has led to significantly more per capita cases and deaths. The initial outbreaks of COVID-19 occurred in the US and Canada within days of each other and posed similar potentially catastrophic threats to public health, the economy, and governmental stability. On a macro level, events that take place in the US have a direct impact on Canada. For example, both countries tend to enter and exit economic recessions at approximately the same time, they are each other’s largest trading partners, and their currencies are inexorably linked. Variables intrinsic to Canada’s national infrastructure have been instrumental in the country’s efforts to flatten the curve of COVID-19 cases and deaths. Canada’s coordinated multi-level governmental effort has allowed it to create and enforce policies related to COVID-19 at both the national and provincial levels. Canada’s policy of universal health care is another variable. Health care and public health measures are enforced on a provincial level, and it is within each province’s jurisdiction to dictate standards for public safety based on scientific evidence. Rather than introducing confusion and the possibility of competition for resources such as PPE and vaccines, Canada’s multi-level chain of government authority has provided consistent policies supporting national public health and local delivery of medical care. This paper will demonstrate that the coordinated efforts on provincial and federal levels have been the linchpin in Canada’s relative success in containing the deadly spread of the COVID-19 virus.

Keywords: COVID-19, canada, GIS, geospatial analysis

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Authors: Andrew Kirabira

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This study is an investigation into the effectiveness of climate-smart agriculture (CSA) technologies in improving productivity through managing biotic and abiotic stresses in the coffee agroecological zones of Uganda. The motive is to enhance farmer livelihoods. The study was initiated as a result of the decreasing productivity of the crop in Uganda caused by the increasing prevalence of pests, diseases and abiotic stresses. Despite 9 years of farmers’ application of CSA, productivity has stagnated between 700kg -800kg/ha/yr which is only 26% of the 3-5tn/ha/yr that CSA is capable of delivering if properly applied. This has negatively affected the incomes of the 10.6 million people along the crop value chain which has in essence affected the country’s national income. In 2019/20 FY for example, Uganda suffered a deficit of $40m out of singularly the increasing incidence of one pest; BCTB. The amalgamation of such trends cripples the realization of SDG #1 and #13 which are the eradication of poverty and mitigation of climate change, respectively. In probing CSA’s effectiveness in curbing such a trend, this study is guided by the objectives of; determining the existing farmers’ knowledge and perceptions of CSA amongst the coffee farmers in the diverse coffee agro-ecological zones of Uganda; examining the relationship between the use of CSA and prevalence of selected coffee pests, diseases and abiotic stresses; ascertaining the difference in the market organization and pricing between conventionally and CSA produced coffee; and analyzing the prevailing policy environment concerning the use of CSA in coffee production. The data collection research design is descriptive in nature; collecting data from farmers and agricultural extension workers in the districts of Ntungamo, Iganga and Luweero; each of these districts representing a distinct coffee agroecological zone. Policy custodian officers at district, cooperatives and at the crop’s overseeing national authority were also interviewed.

Keywords: climate change, food security, field stresses, Productivity

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Authors: Syed Khurram Mahmud, Athar Naveed, Shoaib Arif

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Beamforming is a signal processing technique extensively utilized in wireless communications and radars for desired signal intensification and interference signal minimization through spatial selectivity. In this paper, we present a method for calculation of optimal weight vectors for smart antenna array, to achieve a directive pattern during transmission and selective reception in interference prone environment. In proposed scheme, Mutual Information (MI) extrema are evaluated through an energy constrained objective function, which is based on a-priori information of interference source and desired array factor. Signal to Interference plus Noise Ratio (SINR) performance is evaluated for both transmission and reception. In our scheme, MI is presented as an index to identify trade-off between information gain, SINR, illumination time and spatial selectivity in an energy constrained optimization problem. The employed method yields lesser computational complexity, which is presented through comparative analysis with conventional methods in vogue. MI based beamforming offers enhancement of signal integrity in degraded environment while reducing computational intricacy and correlating key performance indicators.

Keywords: beamforming, interference, mutual information, wireless communications

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Authors: Erez Yerushalmi, Sani Ziv

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The rising demand for healthcare services, without a corresponding rise in public supply, led to a debate on whether to increase private healthcare provision - especially in hospital services and second-tier healthcare. Proponents for increasing private healthcare highlight gains in efficiency, while opponents its risk to social welfare. None, however, provide a measure of the social value and its impact on the economy in terms of a monetary value. In this paper, we impute a minimum social value of public healthcare that corresponds to indifference between gains in efficiency, with losses to social welfare. Our approach resembles contingent valuation methods that introduce a hypothetical market for non-commodities, but is different from them because we use numerical simulation techniques to exploit certain market failure conditions. In this paper, we develop a general equilibrium model that distinguishes between public-private healthcare services and public-private financing. Furthermore, the social value is modelled as a by product of healthcare services. The model is then calibrated to our unique health focused Social Accounting Matrix of Israel, and simulates the introduction of a hypothetical health-labour market - given that it is heavily regulated in the baseline (i.e., the true situation in Israel today). For baseline parameters, we estimate the minimum social value at around 18% public healthcare financing. The intuition is that the gain in economic welfare from improved efficiency, is offset by the loss in social welfare due to a reduction in available social value. We furthermore simulate a deregulated healthcare scenario that internalizes the imputed value of social value and searches for the optimal weight of public and private healthcare provision.

Keywords: contingent valuation method (CVM), general equilibrium model, hypothetical market, private-public healthcare, social value of public healthcare

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Authors: Swadhin Mondal

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While safe drinking water is an effective defense against the infection of water borne diseases, a large number of populations suffering from these diseases do not have access to safe drinking water due inadequacy of supply. Private entrepreneurs entered this sector and made bottled drinking water available by supplying various kinds of bottled water. In this study we found that the bottled drinking water industry has experienced a spectacular growth over the past two decades and it has a huge growth potential because of rising demand for safe drinking. High profit margin (217 %) is the main attraction to the entrepreneur to invest in this industry. Health awareness, lack of safe drinking water facilities, rising income, urbanization, migration and rising trend in tourism industries are the major influencing factors of demand for bottled drinking water (BDW). This industry also partially fulfills the demand for drinking water. More than 2 percent of household’s demands were met by this industry and many more households (additional 4 percent) coping with BDW during water crisis. Poor households spend around 4 percent of their total monthly household’s consumption expenditure on BDW which may have an adverse impact on household because households could have spent this for purchasing other goods. Like other developed counties, a large section of Indian households are shifting from their traditional sources of water to BDW. However, there are some concerns about the quality of BDW. Many cases, BDW contains chemical toxins at more than permissible level that can be harmful for health. Hence, there is an urgent need for appropriate intervention to regulate price, reduce potential harm and improve the quality of water provided by this industry.

Keywords: drinking water, public health public failure, privatization, development, public policy

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Authors: Getachew Mekaa, Bezatu Mengisteb, Tena Alamirewc

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Ashebeka River is the main source of drinking water supply for Assela City and its surrounding inhabitants. Apart from seasonal water reliability disruption, the cost of treating water downstream of the river has been increasing over time due to increased pollutants and suspended sediments. Therefore, this research aimed to identify geo-location and prioritize suspended sediment sources in the Ashebeka River catchment using sediment fingerprinting. We collected 58 composite soil samples and a river water sample for suspended sediment samples from the outlet, which were then filtered using Whatman filter paper. The samples were quantified for geochemical tracers with multi-element capability, and inductively coupled plasma-optical emission spectrometry (ICP-OES). Tracers with significant p-value and that passed the Kruskal-Wallis (KW) test were analyzed for stepwise discriminant function analysis (DFA). The DFA results revealed tracers with good discrimination were subsequently used for the mixed model analysis. The relative significant sediment source contributions from sub-catchments (km2): 3, 4, 1, and 2 were estimated as 49.31% (8), 26.71% (5), 23.65% (5.6), and 0.33% (28.4) respectively. The findings of this study will help the water utilities to prioritize areas of intervention, and the approach used could be followed for catchment prioritization in water safety plan development. Moreover, the findings of this research shed light on the integration of sediment fingerprinting into water safety plans to ensure the reliability of drinking water supplies.

Keywords: disruption of drinking water reliability, ashebeka river catchment, sediment fingerprinting, sediment source contribution, mixed model

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Authors: Felix Boehnisch, Alexander Lutz

Abstract:

Based on the number of users and the amount of content posted daily, Facebook is considered the largest social network in the world. This content includes images or text posts from companies but also private persons, which are also commented on by other users. However, it can sometimes be difficult for companies to keep track of all the posts and the reactions to them, especially when there are several posts a day that contain hundreds to thousands of comments. To facilitate this, the following paper deals with the possible applications of sentiment analysis to social media comments in order to be able to support the work in social media marketing. In a first step, post comments were divided into positive and negative by a subjective rating, then the same comments were checked for their polarity value by the two german python libraries TextBlobDE and SentiWS and also grouped into positive, negative, or even neutral. As a control, the subjective classifications were compared with the machine-generated ones by a confusion matrix, and relevant quality criteria were determined. The accuracy of both libraries was not really meaningful, with 60% to 66%. However, many words or sentences were not evaluated at all, so there seems to be room for optimization to possibly get more accurate results. In future studies, the use of these specific German libraries can be optimized to gain better insights by either applying them to stricter cleaned data or by adding a sentiment value to emojis, which have been removed from the comments in advance, as they are not contained in the libraries.

Keywords: Facebook, German libraries, polarity, sentiment analysis, social media comments

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Authors: Sena Su, Burak Ozbek, Yesim M. Sahin, Sevil Yucel, Dilek Kazan, Faik N. Oktar, Nazmi Ekren, Oguzhan Gunduz

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In recent years, protein, lipid or polysaccharide-based polymers have been used in order to develop biodegradable materials and their chemical nature determines the physical properties of the resulting films. Among these polymers, proteins from different sources have been extensively employed because of their relative abundance, film forming ability, and nutritional qualities. In this study, the biodegradable composite nanofiber films based on fish sarcoplasmic protein (FSP) were prepared via electrospinning technique. Biodegradable polycaprolactone (PCL) was blended with the FSP to obtain hybrid FSP/PCL nanofiber mats with desirable physical properties. Mixture solutions of FSP and PCL were produced at different concentrations and their density, viscosity, electrical conductivity and surface tension were measured. Mechanical properties of electrospun nanofibers were evaluated. Morphology of composite nanofibers was observed using scanning electron microscopy (SEM). Moreover, Fourier transform infrared spectrometer (FTIR) studies were used for analysis chemical composition of composite nanofibers. This study revealed that the FSP based nanofibers have the potential to be used for different applications such as biodegradable packaging, drug delivery, and wound dressing, etc.

Keywords: edible film, electrospinning, fish sarcoplasmic protein, nanofiber

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Authors: Muhammad Suhail Ibrahim, Ahmad Mujtaba

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Background: The accuracy of the most frequently used tests for diagnosing Helicobacter pylori is always under consideration in clinical settings. A reliable diagnosis is crucial to confirm the success of therapy. Objective: The aim of this research was to study the isolation frequency of H. pylori from patients compatible with gastritis or gastric ulcer and to compare some feasible non-invasive and invasive methods for the diagnosis of infection. Materials and Methods: Ninety-six gastric biopsy and blood samples were obtained with various gastroduodenal symptoms after obtaining informed consent. The biopsies were analyzed and compared using the culture, microscopic examination, histopathology, Rapid urease RUT), serology, biochemical, antibiotic susceptibility test and molecular method. Results: A number of 40 (41.67%) were considered H. pylori positive in both histopathology and RUT. On the other hand, 46 patients were positive against anti IgA and IgG by ELISA. Eighteen biopsies were positive according to the culture test. This was further confirmed by endoscopic examination, urease, catalase and oxidase tests. A high percentage of resistance to polymyxin B, amoxicillin, and kanamycin was observed (100, 88.89, and 77.78%, respectively). A gene (Cag A) was also detected by using molecular technique which appeared positive in 16 patients. The sensitivity/specificity (%) of diagnostic method was 95/77 for histology, 100/83.5 for rapid urease, 85.7/90 for gram staining, 100/66.6 for IgG serology, 100/79.5 for IgA serology, 100/75.0 for PCR, 100/79.04 for combination of RUT and IgG serology and 100/92.4 for combination of RUT, gram staining and IgG serology. Conclusion: In view of the result obtained, PCR appeared to be the most reliable test. However, higher sensitivity and specificity were also recorded for other tests. So, for more accurate results, it is advisable not to rely solely on a single method for detection.

Keywords: helicobacter pylori, isolation, detection, culture, urease, polymerase chain reaction, antibiotic susceptibility test, dyspeptic patients

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Authors: Souhir Abid

Abstract:

The growing interest in vegetal biomass as an alternative for fossil resources has stimulated the development of numerous classes of monomers. Polymers from renewable resources have attracted an increasing amount of attention over the last two decades, predominantly due to two major reasons (i) firstly environmental concerns, and (ii) secondly the use of monomers from renewable feedstock is a steadily growing field of interest in order to reduce the amount of petroleum consumed in the chemical industry and to open new high-value-added markets to agriculture. Furanic polymers have been considered as alternative environmentally friendly polymers. In our earlier work, modifying furanic polyesters by incorporation of amide functions along their backbone, lead to a particular class of polymer ‘poly(ester-amide)s’, was investigated to combine the excellent mechanical properties of polyamides and the biodegradability of polyesters. As a continuation of our studies on this family of polymer, a series of furanic poly(ester-amide)s bearing sulfonate groups in the main chain were synthesized from 5,5’-Isopropylidene-bis(ethyl 2-furoate), dimethyl 5-sodiosulfoisophthalate, ethylene glycol and hexamethylene diamine by melt polycondensation using zinc acetate as a catalyst. In view of the complexity of the NMR spectrum analysis of the resulting sulfonated poly(ester-amide)s, we found that it is useful to prepare initially the corresponding homopolymers: sulfonated polyesters and polyamides. Structural data of these polymers will be used as a basic element in 1H NMR characterization. The hydrolytic degradation in acidic aqueous conditions (pH = 4,35 ) at 37 °C over the period of four weeks show that the mechanism of the hydrolysis of poly(ester amide)s was elucidated in relation with the microstructure. The strong intermolecular hydrogen bonding interactions between amide functions and water molecules increases the hydrophilicity of the macromolecular chains and consequently their hydrolytic degradation.

Keywords: furan, hydrolytic degradation, polycondensation, poly(ester amide)

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Authors: Mehrzad Soltani, Pegah Rezaei

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In the endeavor to construct cities that are not only thriving but also environmentally responsible, effective urban planning and architectural design assume paramount significance. The focal point of this pursuit is the harnessing of urban renewable energy. By embracing sustainable practices such as the integration of solar panels into the urban landscape and the establishment of smart grids, cities are poised to confront head-on the dual challenge of surging energy demands and pressing environmental concerns. Urban renewable energy solutions offer a multifaceted approach to these issues. Firstly, they usher in a clean and sustainable source of energy, reducing the cities' ecological footprint while ensuring a continuous power supply. This transition to eco-friendly energy is also intrinsically linked to enhanced spatial utilization, thereby streamlining the efficiency of urban areas. Moreover, it spurs the adoption of sustainable transportation alternatives, diminishing the reliance on fossil fuels and mitigating air pollution. However, the significance of integrating renewable energy solutions transcends the realm of urban sustainability. It embodies a holistic approach towards creating cities that harmoniously coexist with the natural environment while catering to the needs and aspirations of their inhabitants. In essence, prioritizing sustainability in urban planning and architectural design has evolved from a choice to a necessity, one that not only safeguards the cities' well-being but also fosters a better quality of life for their residents. Thus, it is imperative that we acknowledge the transformative potential of these innovations as we pave the way towards the cities of the future.

Keywords: sustainability, smart grids, solar panel, urban planning, environmental concerns

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Authors: Olivia Borgue, Massimo Panarotto, Ola Isaksson

Abstract:

This article presents a neural networks-based strategy for reducing the need for support structures when designing for additive manufacturing (AM). Additive manufacturing is a relatively new and immature industrial technology, and the information to make confident decisions when designing for AM is limited. This lack of information impacts especially the early stages of engineering design, for instance, it is difficult to actively consider the support structures needed for manufacturing a part. This difficulty is related to the challenge of designing a product geometry accounting for customer requirements, manufacturing constraints and minimization of support structure. The approach presented in this article proposes an automatized geometry modification technique for reducing the use of the support structures while designing for AM. This strategy starts with a neural network-based strategy for shape recognition to achieve product classification, using an STL file of the product as input. Based on the classification, an automatic part geometry modification based on MATLAB© is implemented. At the end of the process, the strategy presents different geometry modification alternatives depending on the type of product to be designed. The geometry alternatives are then evaluated adopting a QFD-like decision support tool.

Keywords: additive manufacturing, engineering design, geometry modification optimization, neural networks

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