Search results for: multiple distribution supply chain network

Authors: Tingke Wu, Man Yuan

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“National Territorial Planning (2016-2030)” was issued by the State Council of China in 2017. As an important initiative of putting it into effect, territorial planning at provincial level makes overall arrangement of territorial development, resources and environment protection, comprehensive renovation and security system construction. Hubei province, as the pivot of the “Rise of Central China” national strategy, is now confronted with great opportunities and challenges in territorial development, protection, and renovation. Territorial spatial pattern experiences long time evolution, influenced by multiple internal and external driving forces. It is not clear what are the main causes of its formation and what are effective ways of optimizing it. By analyzing land use data in 2016, this paper reveals present status of territory in Hubei. Combined with economic and social data and construction information, driving forces of territorial spatial pattern are then analyzed. Research demonstrates that the three types of territorial space aggregate distinctively. The four aspects of driving forces include natural background which sets the stage for main functions, population and economic factors which generate agglomeration effect, transportation infrastructure construction which leads to axial expansion and significant provincial strategies which encourage the established path. On this basis, targeted strategies for optimizing territory spatial pattern are then put forward. Hierarchical protection pattern should be established based on development intensity control as respect for nature. By optimizing the layout of population and industry and improving the transportation network, polycentric network-based development pattern could be established. These findings provide basis for Hubei Territorial Planning, and reference for future territorial planning in other provinces.

Keywords: driving forces, Hubei, optimizing strategies, spatial pattern, territory

Procedia PDF Downloads 89

Authors: Amita Barik, Ranjit Prasad Bahadur

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We investigate the role of water molecules in 89 protein-RNA complexes taken from the Protein Data Bank. Those with tRNA and single-stranded RNA are less hydrated than with duplex or ribosomal proteins. Protein-RNA interfaces are hydrated less than protein-DNA interfaces, but more than protein-protein interfaces. Majority of the waters at protein-RNA interfaces makes multiple H-bonds; however, a fraction does not make any. Those making Hbonds have preferences for the polar groups of RNA than its partner protein. The spatial distribution of waters makes interfaces with ribosomal proteins and single-stranded RNA relatively ‘dry’ than interfaces with tRNA and duplex RNA. In contrast to protein-DNA interfaces, mainly due to the presence of the 2’OH, the ribose in protein-RNA interfaces is hydrated more than the phosphate or the bases. The minor groove in protein-RNA interfaces is hydrated more than the major groove, while in protein-DNA interfaces it is reverse. The strands make the highest number of water-mediated H-bonds per unit interface area followed by the helices and the non-regular structures. The preserved waters at protein-RNA interfaces make higher number of H-bonds than the other waters. Preserved waters contribute toward the affinity in protein-RNA recognition and should be carefully treated while engineering protein-RNA interfaces.

Keywords: h-bonds, minor-major grooves, preserved water, protein-RNA interfaces

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Authors: Redvan Ghasemlounia, Elham Ansari, Hikmet Kerem Cigizoglu

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Hydrological modeling in arid and semi-arid regions is very important. Iran has many regions with these climate conditions such as Chaharmahal and Bakhtiari province that needs lots of attention with an appropriate management. Forecasting of hydrological parameters and estimation of hydrological events of catchments, provide important information that used for design, management and operation of water resources such as river systems, and dams, widely. Discharge in rivers is one of these parameters. This study presents the application and comparison of some estimation methods such as Feed-Forward Back Propagation Neural Network (FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) to predict the daily flow discharge of the Soolegan River, located at Chaharmahal and Bakhtiari province, in Iran. In this study, Soolegan, station was considered. This Station is located in Soolegan River at 51° 14՜ Latitude 31° 38՜ longitude at North Karoon basin. The Soolegan station is 2086 meters higher than sea level. The data used in this study are daily discharge and daily precipitation of Soolegan station. Feed Forward Back Propagation Neural Network(FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) models were developed using the same input parameters for Soolegan's daily discharge estimation. The results of estimation models were compared with observed discharge values to evaluate performance of the developed models. Results of all methods were compared and shown in tables and charts.

Keywords: ANN, multi linear regression, Bayesian network, forecasting, discharge, gene expression programming

Procedia PDF Downloads 550

Authors: Pear-Rarin Leelakunakorn, Patompong Satapornpong

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Introduction: Dapsone is an anti-inflammatory and antibiotic drug that was widely used for the treatment of leprosy, acne fulminans, and dermatitis herpetiformis (DH). However, dapsone is the main cause that triggers severe cutaneous adverse reactions (SCARs), with a possibility of 0.4 to 3.6% of patients after initiating treatment. In fact, the mortality rate of dapsone-induced SCARs is approximately 9.9%. In previous studies, HLA-B*13:01 was strongly associated with dapsone-induced SCARs in Han Chinese, Thais, and Koreans. Nevertheless, the distribution of HLA-B*13:01 marker in each population might differ. Moreover, there were found that the association between HLA-C*03:04 and dapsone hypersensitivity syndrome in Han Chinese leprosy patients by OR = 9.00 and p-value = 2.23×10⁻¹⁹. Objective: The aim of this study was to investigate the distribution of HLA-C* 03:04 in Thailand's healthy population. Method: A total of 350 participants were HLA-C genotyping used sequence-specific oligonucleotides (PCR-SSOs). This study was approved by the Ethics Committee of Rangsit University Result : The most frequency of HLA -C alleles in Thais, consist of HLA -C* 01:02 (17.00 %), -C*08:01 (11.00%) , -C*07:02 (10.70%) , -C* 03:04 ( 9.10%) , -C* 03:02 (8.00%) , -C* 07:01 (6.30%), -C* 07:04 (4.60%), -C* 04:01 (4.40%) ,-C* 12:02 ( 4.30% ) ,and -C* 04:03(3.90%). Interestingly, HLA -C* 03:04 allele was similar to the distribution among Thais and other populations such as Eastern Europe (6.09%), Vietnam (7.42% ), East Croatia (2.25%), and Han Chinese (11.70%). Conclusion: Consequently, HLA-C*03:04 might serve as a pharmacogenetic marker for screening prior to initiation therapy with dapsone for prevention of dapsone-induced SCARs in Thai population.

Keywords: HLA-C*03:04, SCARs, thai population, allele frequency

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Authors: Khue Nguyen Dinh, Loi Nguyen Van, Thanh Nguyen Nhu

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In this paper, we propose an adaptive method to resolve ambiguities and a ghost target removal process to extract targets detected by a ground-based pulse-Doppler radar using medium pulse repetition frequency (PRF) waveforms. The ambiguity resolution method is an adaptive implementation of the coincidence algorithm, which is implemented on a two-dimensional (2D) range-velocity matrix to resolve range and velocity ambiguities simultaneously, with a proposed clustering filter to enhance the anti-error ability of the system. Here we consider the scenario of multiple target environments. The ghost target removal process, which is based on the power after Doppler processing, is proposed to mitigate ghosting detections to enhance the performance of ground-based radars using a short PRF schedule in multiple target environments. Simulation results on a ground-based pulsed Doppler radar model will be presented to show the effectiveness of the proposed approach.

Keywords: ambiguity resolution, coincidence algorithm, medium PRF, ghosting removal

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Authors: Navab Karimi, Tohid Alizadeh

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An intelligent vision-based system was designed to measure the quality and purity of raisins. A machine vision setup was utilized to capture the images of bulk raisins in ranges of 5-50% mixed pure-impure berries. The textural features of bulk raisins were extracted using Grey-level Histograms, Co-occurrence Matrix, and Local Binary Pattern (a total of 108 features). Genetic Algorithm and neural network regression were used for selecting and ranking the best features (21 features). As a result, the GLCM features set was found to have the highest accuracy (92.4%) among the other sets. Followingly, multiple feature combinations of the previous stage were fed into the second regression (linear regression) to increase accuracy, wherein a combination of 16 features was found to be the optimum. Finally, a Support Vector Machine (SVM) classifier was used to differentiate the mixtures, producing the best efficiency and accuracy of 96.2% and 97.35%, respectively.

Keywords: sun-dried organic raisin, genetic algorithm, feature extraction, ann regression, linear regression, support vector machine, south azerbaijan.

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Authors: Hirseland Andreas, Kerschbaumer Lukas

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In the case of Germany, there are about one million long-term unemployed – a figure that did not vary much during the past years. These long-term unemployed did not benefit from the prospering labor market while most short-term unemployed did. Instead, they are continuously dependent on welfare and sometimes precarious short-term employment, experiencing work poverty. Long-term unemployment thus turns into a main obstacle to become employed again, especially if it is accompanied by other impediments such as low-level education (school/vocational), poor health (especially chronical illness), advanced age (older than fifty), immigrant status, motherhood or engagement in care for other relatives. As can be shown by this current research project, in these cases the chance to regain employment decreases to near nil. Almost two-thirds of all welfare recipients have multiple impediments which hinder a successful transition from welfare back to sustainable and sufficient employment. Prospective employers are unlikely to hire long-term unemployed with additional impediments because they evaluate potential employees on their negative signaling (e.g. low-level education) and the implicit assumption of unproductiveness (e.g. poor health, age). Some findings of the panel survey “Labor market and social security” (PASS) carried out by the Institute of Employment Research (the research institute of the German Federal Labor Agency) spread a ray of hope, showing that unlikely does not necessarily mean impossible. The presentation reports on current research on these very scarce “success stories” of unlikely transitions from long-term unemployment to work and how these cases were able to perform this switch against all odds. The study is based on a mixed-method design. Within the panel survey (~15,000 respondents in ~10,000 households), only 66 cases of such unlikely transitions were observed. These cases have been explored by qualitative inquiry – in depth-interviews and qualitative network techniques. There is strong evidence that sustainable transitions are influenced by certain biographical resources like habits of network use, a set of informal skills and particularly a resilient way of dealing with obstacles, combined with contextual factors rather than by job-placement procedures promoted by Job-Centers according to activation rules or by following formal paths of application. On the employer’s side small and medium-sized enterprises are often found to give job opportunities to a wider variety of applicants, often based on a slow but steadily increasing relationship leading to employment. According to these results it is possible to show and discuss some limitations of (German) activation policies targeting the labor market and their impact on welfare dependency and long-term unemployment. Based on these findings, indications for more supportive small-scale measures in the field of labor-market policies are suggested to help long-term unemployed with multiple impediments to overcome their situation (e.g. organizing small-scale-structures and low-threshold services to encounter possible employers on a more informal basis like “meet and greet”).

Keywords: against-all-odds, mixed-methods, Welfare State, long-term unemployment

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Authors: Henry Schwartz, Bogdan Iancu, Magnus Gustafsson, Johan Lilius

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The shipping sector generates significant amounts of carbon emissions on annual basis. The excess amount of carbon dioxide is harmful for both the environment and the society, and partly for that reason, there is acute interest to decrease the volume of anthropogenic carbon dioxide emissions in shipping. The usage of the existing cargo carrying capacity can be maximized, and the share of time used in actual transportation operations could be increased if the whole transportation and logistics chain was optimized with the aid of information sharing done through a centralized marketplace and an information-sharing platform. The outcome of this change would be decreased carbon dioxide emission volumes produced per each metric ton of cargo transported by a vessel. Cargo coordination is a platform under development that matches the need for waterborne transportation services with the ships that operate at a given moment in time. In this research, the transition towards adopting cargo coordination is modelled with system dynamics. The model encompasses the complex supply-demand relationships of ship operators and cargo owners. The built scenarios predict the pace at which different stakeholders start using the digitalized platform and by doing so reduce the amount of annual CO2 emissions generated. To improve the reliability of the results, various sensitivity analyses considering the pace of transition as well as the overall impact on the environment (carbon dioxide emissions per amount of cargo transported) are conducted. The results of the study can be used to support investors and politicians in decision making towards more environmentally sustainable solutions. In addition, the model provides concepts and ideas for a wider discussion considering the paths towards carbon neutral transportation.

Keywords: carbon dioxide emissions, energy efficiency, sustainable transportation, system dynamics

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Authors: Oded Hochman

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We first show that current measures of welfare changes in the whole economy do not apply to an economy with cities. In addition, since such measures are defined over a partial equilibrium, they capture only partially the effect of a welfare change. We then define a unique and additive measure that we term the modified economic surplus (mES) which fully captures the welfare effects caused by a change in the price of a nationally traded good. We show that the price change causes, on the one hand a change of land rents in the economy and, on the other hand, an equal change of mES that can be estimated by measuring areas in the price-quantity national demand and supply plane. We construct for each city a cost function from which we derive a city’s and, after aggregation, an economy-wide demand and supply functions of nationwide prices and of either the unearned incomes (Marshalian functions) or the utility levels (compensated functions).

Keywords: city cost function, welfare measures, modified compensated variation, modified economic surplus, unearned income function, differential land rents, city size

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Authors: Narendra Akhadkar, Philippe Delcambre

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In power protection and control products, assembly process variations due to the individual parts manufactured from single or multi-cavity tooling is a major problem. The dimensional and geometrical variations on the individual parts, in the form of manufacturing tolerances and assembly tolerances, are sources of clearance in the kinematic joints, polarization effect in the joints, and tolerance stack-up. All these variations adversely affect the quality of product, functionality, cost, and time-to-market. Variation simulation analysis may be used in the early product design stage to predict such uncertainties. Usually, variations exist in both manufacturing processes and materials. In the tolerance analysis, the effect of the dimensional and geometrical variations of the individual parts on the functional characteristics (conditions) of the final assembled products are studied. A functional characteristic of the product may be affected by a set of interrelated dimensions (functional parameters) that usually form a geometrical closure in a 3D chain. In power protection and control products, the prerequisite is: when a fault occurs in the electrical network, the product must respond quickly to react and break the circuit to clear the fault. Usually, the response time is in milliseconds. Any failure in clearing the fault may result in severe damage to the equipment or network, and human safety is at stake. In this article, we have investigated two important functional characteristics that are associated with the robust performance of the product. It is demonstrated that the experimental data obtained at the Schneider Electric Laboratory prove the very good prediction capabilities of the variation simulation performed using CETOL (tolerance analysis software) in an industrial context. Especially, this study allows design engineers to better understand the critical parts in the product that needs to be manufactured with good, capable tolerances. On the contrary, some parts are not critical for the functional characteristics (conditions) of the product and may lead to some reduction of the manufacturing cost, ensuring robust performance. The capable tolerancing is one of the most important aspects in product and manufacturing process design. In the case of miniature circuit breaker (MCB), the product's quality and its robustness are mainly impacted by two aspects: (1) allocation of design tolerances between the components of a mechanical assembly and (2) manufacturing tolerances in the intermediate machining steps of component fabrication.

Keywords: geometrical variation, product robustness, tolerance analysis, variation simulation

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Authors: Meryem Imane Babaghayou, Asma Abdelhafidi, Salem Fouad Chabira, Mohammed Sebaa

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A challenge of plastics industries is the realization of materials that resist the degradation in its application environment, and that to guarantee a longer life time therefore an optimal time of use. Blown extruded films of low-density polyethylene (LDPE) supplied by SABIC SAUDI ARABIA blown and extruded in SOFIPLAST company in Setif ALGERIA , have been subjected to climatic ageing in a sub-Saharan facility at Laghouat (Algeria) with direct exposure to sun. Samples were characterized by X-ray diffraction (XRD) and differential scanning calorimetry (DSC) techniques after prescribed amounts of time up to 8 months. It has been shown via these two techniques the impact of UV irradiation on the morphological development of a plastic material, especially the crystallinity degree which increases with exposure time. The reason of these morphological changes is related to photooxidative reactions leading to cross linking in the beginning and to chain scissions for an advanced stage of ageing this last ones are the first responsible. The crystallinity degree change is essentially controlled by the secondary crystallization of the amorphous chains whose mobility is enhanced by the chain scission processes. The diffusion of these short segments integrates the surface of the lamellae increasing in this way their thicknesses. The results presented highlight the complexity of the involved phenomena.

Keywords: Low Density poly (Ethylene), crystallinity, ageing, XRD, DSC

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Authors: Nassiri Khalid, El Hibaoui Abdelaaziz et Hajar Moha

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In this paper, we introduce and analyse a probabilistic distributed algorithm for a construction of a minimum spanning tree on network. This algorithm is based on the handshake concept. Firstly, each network node is considered as a sub-spanning tree. And at each round of the execution of our algorithm, a sub-spanning trees are merged. The execution continues until all sub-spanning trees are merged into one. We analyze this algorithm by a stochastic process.

Keywords: Spanning tree, Distributed Algorithm, Handshake Algorithm, Matching, Probabilistic Analysis

Procedia PDF Downloads 644

Authors: Vijay Kumar, Jaspreet Singh, Manoj Wadhwa

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Piezo-resistive pressure sensors were one of the first developed micromechanical system (MEMS) devices and still display a significant growth prompted by the advancements in micromachining techniques and material technology. In MEMS based piezo-resistive pressure sensors, temperature can be considered as the main environmental condition which affects the system performance. The study of the thermal behavior of these sensors is essential to define the parameters that cause the output characteristics to drift. In this work, a study on the effects of temperature and doping concentration in a boron implanted piezoresistor for a silicon-based pressure sensor is discussed. We have optimized the temperature coefficient of resistance (TCR) and temperature coefficient of sensitivity (TCS) values to determine the effect of temperature drift on the sensor performance. To be more precise, in order to reduce the temperature drift, a high doping concentration is needed. And it is well known that the Wheatstone bridge in a pressure sensor is supplied with a constant voltage or a constant current input supply. With a constant voltage supply, the thermal drift can be compensated along with an external compensation circuit, whereas the thermal drift in the constant current supply can be directly compensated by the bridge itself. But it would be beneficial to also compensate the temperature coefficient of piezoresistors so as to further reduce the temperature drift. So, with a current supply, the TCS is dependent on both the TCπ and TCR. As TCπ is a negative quantity and TCR is a positive quantity, it is possible to choose an appropriate doping concentration at which both of them cancel each other. An exact cancellation of TCR and TCπ values is not readily attainable; therefore, an adjustable approach is generally used in practical applications. Thus, one goal of this work has been to better understand the origin of temperature drift in pressure sensor devices so that the temperature effects can be minimized or eliminated. This paper describes the optimum doping levels for the piezoresistors where the TCS of the pressure transducers will be zero due to the cancellation of TCR and TCπ values. Also, the fabrication and characterization of the pressure sensor are carried out. The optimized TCR value obtained for the fabricated die is 2300 ± 100ppm/ᵒC, for which the piezoresistors are implanted at a doping concentration of 5E13 ions/cm³ and the TCS value of -2100ppm/ᵒC is achieved. Therefore, the desired TCR and TCS value is achieved, which are approximately equal to each other, so the thermal effects are considerably reduced. Finally, we have calculated the effect of temperature and doping concentration on the output characteristics of the sensor. This study allows us to predict the sensor behavior against temperature and to minimize this effect by optimizing the doping concentration.

Keywords: piezo-resistive, pressure sensor, doping concentration, TCR, TCS

Procedia PDF Downloads 170

Authors: M. Fertouna Bellakhal, M. Bellakhal, A. Dhib, A. Fathalli, S. Turki, L. Aleya

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Study of dinoflagellate cysts is a precious tool to get information about environment and water quality in many aquatic ecosystems. The distribution of Alexandrium pacificum cysts, in Bizerta lagoon located in North of Tunisia, was made based on sediment samples analysis from 123 equidistant stations delimiting 125 km² surfaces. Sediment characteristics such as percentage of water, organic matter, and particle size were analyzed to determine the factors that influence the distribution of this dinoflagellate. In addition, morphological examination and ribotyping of vegetative forms from microalgal cultures made from cyst germination confirmed the identity of the species attributed to A. pacificum. A correlation between the abundance of A. pacificum cysts and the percentage of water and sediment organic matter was recorded. In addition, the sedimentary fraction < 63μm was found to be potentially favorable for the installation and initiation of the Alexandrium pacificum efflorescence at the Bizerte lagoon. The mapping of cysts in this aquatic ecosystem has also allowed us to define distinct areas with specific abundance with closed relationship with shellfish aquaculture stations located within the lagoon.

Keywords: Alexandrium pacificum, cysts, Dinoflagellate, microalgal culture

Procedia PDF Downloads 137

Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

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To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

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Authors: Mohammed Jibrin Ndejiko

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Modern and current models such as flow cell technology which enhances a non-destructive growth and inspection of the sessile microbial communities revealed a great understanding of biofilms. A continuous flow system was designed to evaluate possibility of biofilm formation by Escherichia coli DH5α on the stainless steel (type 304) under continuous nutrient supply. The result of the colony forming unit (CFU) count shows that bacterial attachment and subsequent biofilm formation on stainless steel coupons with average surface roughness of 1.5 ± 1.8 µm and 2.0 ± 0.09 µm were both significantly higher (p ≤ 0.05) than those of the stainless steel coupon with lower surface roughness of 0.38 ± 1.5 µm. These observations support the hypothesis that surface profile is one of the factors that influence biofilm formation on stainless steel surfaces. The SEM and FESEM micrographs of the stainless steel coupons also revealed the attached Escherichia coli DH5α biofilm and dehydrated extracellular polymeric substance on the stainless steel surfaces. Thus, the fabricated flow system represented a very useful tool to study biofilm formation under continuous nutrient supply.

Keywords: biofilm, flowcell, stainless steel, coupon

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Authors: Ather Saeed, Arif Khan, Jeffrey Gosper

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Sensor devices are prone to errors and sudden node failures, which are difficult to detect in a timely manner when deployed in real-time, hazardous, large-scale harsh environments and in medical emergencies. Therefore, the loss of data can be life-threatening when the sensed phenomenon is not disseminated due to sudden node failure, battery depletion or temporary malfunctioning. We introduce a set of partial differential equations for localizing faults, similar to Green’s and Maxwell’s equations used in Electrostatics and Electromagnetism. We introduce a node organization and clustering scheme for self-stabilizing sensor networks. Green’s theorem is applied to regions where the curve is closed and continuously differentiable to ensure network connectivity. Experimental results show that the proposed GTFD (Green’s Theorem fault-detection and Self-stabilization) protocol not only detects faulty nodes but also accurately generates network stability graphs where urgent intervention is required for dynamically self-stabilizing the network.

Keywords: Green’s Theorem, self-stabilization, fault-localization, RSSI, WSN, clustering

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Authors: Krismonika Khoirunnisa

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This research article aims to describe the variation of the Javanese lexicon "Sleep " and its distribution in the Jombang area, East Java. The objectives of this study were (1) to classify the variation of the "Sleep" lexicon in the Jombang area and (2) to design the fish rips for the variation of the "Sleep" lexicon according to their distribution. This type of research is a qualitative descriptive study using the method of leading proficiency, namely conducting interviews with speakers without directly meeting the speakers (interviews via WhatsApp and email as the media). This research article uses techniques record as support and tools for mapping and classifying data, collecting data in this study conducted at four points, namely the Kaliwungu village (Jombang City), Banjardowo village (District of Jombang), Mayangan Village (Subdistrict Jogoroto), and Karobelah village (Subdistrict Mojoagung) as a target investigators to conduct the interview. This study uses the dialectology theory as a basis for analyzing the data obtained. The results of this study found that the Javanese language variation "Sleep" has many different linguals, meanings, and forms even though they are in the same area (Jombang).

Keywords: geographical dialectology, lexicon variations, jombangan dialect, sssavanese language

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Authors: Mahmoud M. Othman, Almoataz Y. Abdelaziz, Yasser G. Hegazy

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This paper presents a load control strategy based on modification of the Big Bang Big Crunch optimization method. The proposed strategy aims to determine the optimal load to be controlled and the corresponding time of control in order to minimize the energy purchased from substation. The presented strategy helps the distribution network operator to rely on the renewable energy sources in supplying the system demand. The renewable energy sources used in the presented study are modeled using the diagonal band Copula method and sequential Monte Carlo method in order to accurately consider the multivariate stochastic dependence between wind power, photovoltaic power and the system demand. The proposed algorithms are implemented in MATLAB environment and tested on the IEEE 37-node feeder. Several case studies are done and the subsequent discussions show the effectiveness of the proposed algorithm.

Keywords: big bang big crunch, distributed generation, load control, optimization, planning

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Authors: Sunmyeng Kim

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IEEE 802.11a/b/g standards provide multiple transmission rates, which can be changed dynamically according to the channel condition.Cooperative communications we reintroduced to improve the overallperformance of wireless LANs with the help of relay nodes with higher transmission rates. The cooperative communications are based on the fact that the transmission is much faster when sending data packets to a destination node through a relay node with higher transmission rate, rather than sending data directly to the destination node at low transmission rate. To apply the cooperative communications in wireless LAN, several MAC protocols have been proposed. Some of them can result in collisions among relay nodes in a dense network. In order to solve this problem, we propose a new protocol. Relay nodes are grouped based on their transmission rates. And then, relay nodes only in the highest group try to get channel access. Performance evaluation is conducted using simulation, and shows that the proposed protocol significantly outperforms the previous protocol in terms of throughput and collision probability.

Keywords: cooperative communications, MAC protocol, relay node, WLAN

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Authors: Jared Oluoch

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Connected vehicles are equipped with wireless sensors that aid in Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication. These vehicles will in the near future provide road safety, improve transport efficiency, and reduce traffic congestion. One of the challenges for connected vehicles is how to ensure that information sent across the network is secure. If security of the network is not guaranteed, several attacks can occur, thereby compromising the robustness, reliability, and efficiency of the network. This paper discusses existing security mechanisms and unique properties of connected vehicles. The methodology employed in this work is exploratory. The paper reviews existing security solutions for connected vehicles. More concretely, it discusses various cryptographic mechanisms available, and suggests areas of improvement. The study proposes a combination of symmetric key encryption and public key cryptography to improve security. The study further proposes message aggregation as a technique to overcome message redundancy. This paper offers a comprehensive overview of connected vehicles technology, its applications, its security mechanisms, open challenges, and potential areas of future research.

Keywords: VANET, connected vehicles, 802.11p, WAVE, DSRC, trust, security, cryptography

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Authors: Aysun Pınarbaşı, Béla Vizvári

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The countries are the units that procure the vaccines during the COVID-19 pandemic. The delivered quantities are huge. The countries must bear the inventory holding cost according to the variation of stock quantities. This cost depends on the speed of the vaccination in the country. This speed is time-dependent. The vaccinated portion of the population can be approximated by the cumulative distribution function of the Cauchy distribution. A model is provided for determining the minimal-cost inventory policy, and its optimality conditions are provided. The model is solved for 20 countries for different numbers of procurements. The results reveal the individual behavior of each country. We provide an inventory policy for the pandemic period for the countries. This paper presents a deterministic model for vaccines with a demand rate variable over time for the countries. It is aimed to provide an analytical model to deal with the minimization of holding cost and develop inventory policies regarding this aim to be used for a variety of perishable products such as vaccines. The saturation process is introduced, and an approximation of the vaccination curve of the countries has been discussed. According to this aspect, a deterministic model for inventory policy has been developed.

Keywords: covid-19, vaccination, inventory policy, bounded total demand, inventory holding cost, cauchy distribution, sigmoid function

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Authors: G. Kiran Kumar, K. Padmaja

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The rise of urban and peri-urban agriculture (UPA) is an important urban phenomenon that needs to be well understood before we pronounce a verdict whether it is beneficial or not. The challenge of supply of safe and nutritious food is faced by urban inhabitants. The definition of urban and peri-urban varies from city to city depending on the local policies framed with a view to bring regulated urban habitations as part of governance. Expansion of cities and the blurring of boundaries between urban and rural areas make it difficult to define peri-urban agriculture. The problem is further exacerbated by the fact that definition adopted in one region may not fit in the other. On the other hand the proportion of urban population is on the rise vis-à-vis rural. The rise of UPA does not promise that the food requirements of cities can be entirely met from this practice, since availability of enormous amounts of spaces on rooftops and vacant plots is impossible for raising crops. However, UPA reduces impact of price volatility, particularly for vegetables, which relatively have a longer shelf life. UPA improves access to fresh, nutritious and safe food for the urban poor. UPA provides employment to food handlers and traders in the supply chain. UPA can pose environmental and health risks from inappropriate agricultural practices; increased competition for land, water and energy; alter the ecological landscape and make it vulnerable to increased pollution. The present work is based on case studies in peri-urban agriculture in Hyderabad, India and relies on secondary data. This paper tries to analyze the need for more intensive production technologies without affecting the environment. An optimal solution in terms of urban-rural linkages has to be devised. There is a need to develop a spatial vision and integrate UPA in urban planning in a harmonious manner. Zoning of peri-urban areas for agriculture, milk and poultry production is an essential step to preserve the traditional nurturing character of these areas. Urban local bodies in conjunction with Departments of Agriculture and Horticulture can provide uplift to existing UPA models, without which the UPA can develop into a haphazard phenomenon and add to the increasing list of urban challenges. Land to be diverted for peri-urban agriculture may render the concept of urban and peri-urban forestry ineffective. This paper suggests that UPA may be practiced for high value vegetables which can be cultivated under protected conditions and are better resilient to climate change. UPA can provide models for climate resilient agriculture in urban areas which can be replicated in rural areas. Production of organic farm produce is another option for promote UPA owing to the proximity to informed consumers and access to markets within close range. Waste lands in peri-urban areas can be allotted to unemployed rural youth with the support of Urban Local Bodies (ULBs) and used for UPA. This can serve the purposes of putting wastelands to food production, enhancing employment opportunities and enhancing access to fresh produce for urban consumers.

Keywords: environment, food security, urban and peri-urban agriculture, zoning

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Authors: Mohammed Albahttiti, Eliana Aguilar

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A push for sustainability in the concrete industry is increasing. Cow manure itself is becoming a problem and having the potential solution to use it in concrete as a cementitious replacement would be an ideal solution. For cow manure ash to become a well-rounded substitute, it would have to meet the right criteria to progress in becoming a more popular idea in the concrete industry. This investigation primarily focuses on how the replacement of cow manure ash affects the air content and air void distribution in concrete. In order to assess these parameters, the Super Air Meter (SAM) was used to test concrete in this research. In addition, multiple additional tests were performed, which included the slump test, temperature, and compression test. The strength results of the manure ash in concrete were promising. The manure showed compression strength results that are similar to that of the other supplementary cementitious materials tested. On the other hand, concrete samples made with cow manure ash showed 2% air content loss and an increasing SAM number proportional to cow manure content starting at 0.38 and increasing to 0.8. In conclusion, while the use of cow manure results in loss of air content, it results in compressive strengths similar to other supplementary cementitious materials.

Keywords: air content, biomass ash, cow manure ash, super air meter, supplementary cementitious materials

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Authors: Rejab Hajlaoui, Tarek Moulahi, Hervé Guyennet

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In a highway scenario, the vehicle speed can exceed 120 kmph. Therefore, any vehicle can enter or leave the network within a very short time. This mobility adversely affects the network connectivity and decreases the life time of all established links. To ensure an effective stability in vehicular ad hoc networks with minimum broadcasting storm, we have developed a weighted algorithm based on the k-medoids clustering algorithm (WKCA). Indeed, the number of clusters and the initial cluster heads will not be selected randomly as usual, but considering the available transmission range and the environment size. Then, to ensure optimal assignment of nodes to clusters in both k-medoids phases, the combined weight of any node will be computed according to additional metrics including direction, relative speed and proximity. Empirical results prove that in addition to the convergence speed that characterizes the k-medoids algorithm, our proposed model performs well both AODV-Clustering and OLSR-Clustering protocols under different densities and velocities in term of end-to-end delay, packet delivery ratio, and throughput.

Keywords: communication, clustering algorithm, k-medoids, sensor, vehicular ad hoc network

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Authors: Agostinho Antunes

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The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of varied species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: adaptation, animals, evolution, genomics

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Authors: K. Noah, F.-S. Lien

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In Computational Fluid Dynamics (CFD), there are a variety of numerical methods, of which some depend on macroscopic model representatives. These models can be solved by finite-volume, finite-element or finite-difference methods on a microscopic description. However, the lattice Boltzmann method (LBM) is considered to be a mesoscopic particle method, with its scale lying between the macroscopic and microscopic scales. The LBM works well for solving incompressible flow problems, but certain limitations arise from solving compressible flows, particularly at high Mach numbers. An improved lattice Boltzmann model for compressible flow problems is presented in this research study. A higher-order Taylor series expansion of the Maxwell equilibrium distribution function is used to overcome limitations in LBM when solving high-Mach-number flows. Large eddy simulation (LES) is implemented in LBM to simulate turbulent jet flows. The results have been validated with available experimental data for turbulent compressible free jet flow at subsonic speeds.

Keywords: compressible lattice Boltzmann method, multiple relaxation times, large eddy simulation, turbulent jet flows

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Authors: Marcio Leal, Marta Villamil

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Computacional recognition of sign languages aims to allow a greater social and digital inclusion of deaf people through interpretation of their language by computer. This article presents a model of recognition of two of global parameters from sign languages; hand configurations and hand movements. Hand motion is captured through an infrared technology and its joints are built into a virtual three-dimensional space. A Multilayer Perceptron Neural Network (MLP) was used to classify hand configurations and Dynamic Time Warping (DWT) recognizes hand motion. Beyond of the method of sign recognition, we provide a dataset of hand configurations and motion capture built with help of fluent professionals in sign languages. Despite this technology can be used to translate any sign from any signs dictionary, Brazilian Sign Language (Libras) was used as case study. Finally, the model presented in this paper achieved a recognition rate of 80.4%.

Keywords: artificial neural network, computer vision, dynamic time warping, infrared, sign language recognition

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Authors: Niloufar Yadgari

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GANs are a potent form of deep learning models that have found success in various fields. They are part of the larger group of generative techniques, which aim to produce authentic data using a probabilistic model that learns distributions from actual samples. In clinical settings, GANs have demonstrated improved abilities in capturing spatially intricate, nonlinear, and possibly subtle disease impacts in contrast to conventional generative techniques. This review critically evaluates the current research on how GANs are being used in imaging studies of different neurological conditions like Alzheimer's disease, brain tumors, aging of the brain, and multiple sclerosis. We offer a clear explanation of different GAN techniques for each use case in neuroimaging and delve into the key hurdles, unanswered queries, and potential advancements in utilizing GANs in this field. Our goal is to connect advanced deep learning techniques with neurology studies, showcasing how GANs can assist in clinical decision-making and enhance our comprehension of the structural and functional aspects of brain disorders.

Keywords: GAN, pathology, generative adversarial network, neuro imaging

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Authors: Guan-Ying Chen, Han-Tsung Liou, Shou-Ren Hu

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To address traffic congestion problems and encourage the use of public transportation systems in the Taipei metropolitan area, the Taipei City Government and the New Taipei City Government implemented a monthly ticket policy on April 16, 2018. This policy offers unlimited rides on the Taipei MRT, Taipei City Bus, New Taipei City Bus, Danhai Light Rail, and Public Bike (YouBike) on a monthly basis. Additionally, both city governments replaced the smart card discount policy with a new frequent flyer discount program (referred to as the loyal customer program) on February 1, 2020, introducing a differential pricing policy. Specifically, the more frequently the Taipei MRT system is used, the greater the discounts users receive. To analyze the impact of the Taipei public transport monthly ticket policy and the frequent user discount program on the passenger volume of the Taipei MRT system and the transferring behaviors of MRT users, this study conducts a trip-chain analysis using transaction data from Taipei MRT smart cards between September 2017 and December 2020. To achieve these objectives, the study employs four indicators: 1) number of passengers, 2) average number of rides, 3) average trip distance, and 4) instances of multiple consecutive rides. The study applies the t-test and Mann-Kendall trend test to investigate whether the proposed indicators have changed over time due to the implementation of the discount policy. Furthermore, the study examines the travel behaviors of passengers who use monthly tickets. The empirical results of the study indicate that the implementation of the Taipei public transport monthly ticket policy has led to an increase in the average number of passengers and a reduction in the average trip distance. Moreover, there has been a significant increase in instances of multiple consecutive rides, attributable to the unlimited rides offered by the monthly tickets. The impact of the frequent user discount program on changes in MRT passengers is not as pronounced as that of the Taipei public transportation monthly ticket policy. This is partly due to the fact that the frequent user discount program is only applicable to the Taipei MRT system, and the passenger volume was greatly affected by the COVID-19 pandemic. The findings of this research can serve as a reference for Taipei MRT Corporation in formulating its fare strategy and can also provide guidance for the Taipei and New Taipei City Governments in evaluating differential pricing policies for public transportation systems.

Keywords: frequent user discount program, mass rapid transit, monthly ticket, smart card

Procedia PDF Downloads 56