Search results for: real estate price prediction

Authors: Chariya Laohavich

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At the current, the trends in the lung disease at a university hospital are the treat and diagnosis by bronchoscopy. Bronchoscopic cryotherapy is a long time procedure 1-4 hours. The cryo probe is sensitive and easy to be damaged and expensive. We have this study management for protection the cryo probe, user satisfaction and qualities work. This study conducted in 4 stages: stage 1 for a survey of problems and assessment of user’s needs; stage 2 for designing and developing the Rama-chest cryo arm for a bronchoscopy process; stage 3 for test-implementing the Rama-chest cryo arm in real situations, studying its problems and obstacles, and evaluating the user satisfaction; and stage 4 for an overall assessment and improvement. The sample used in this study consisted of a total of 15 Ramathipbodi Hospital’s Bronchoscopist and bronchoscopist’s nurse who had used the Rama-chest cryo arm for bronchoscopic cryotherapy from January to June 2016. Objective: To study efficacy and user satisfaction on the Rama-chest cryo arm innovation for bronchoscopic cryotherapy. Data were collected using a Rama-chest cryo arm satisfaction assessment form and analysed based on mean and standard deviation. Result is the Rama-chest cryo arm was an innovation that accommodated during bronchoscopic cryotherapy. The subjects rated this the cryo arm as being most satisfactory (M = 4.86 ± , SD 0.48. Therefore we have developed a cryo arm that uses local material, practical and economic. Our innovation is not only flexible and sustainable development but also lean and seamless. This produced device can be used as effectively as the imported one, and thus can be eventually substituted.

Keywords: efficacy, satisfaction, Rama-chest cryo arm, innovation, bronchoscopic cryotherapy

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Authors: Zeina Bou Diab, Arij Daou

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The neural mechanisms of sequential behaviors are intensively studied, with songbirds a focus for learned vocal production. We are studying the premotor nucleus HVC at a nexus of multiple pathways contributing to song learning and production. The HVC consists of multiple classes of neuronal populations, each has its own cellular, electrophysiological and functional properties. During singing, a large subset of motor cortex analog-projecting HVCRA neurons emit a single 6-10 ms burst of spikes at the same time during each rendition of song, a large subset of basal ganglia-projecting HVCX neurons fire 1 to 4 bursts that are similarly time locked to vocalizations, while HVCINT neurons fire tonically at average high frequency throughout song with prominent modulations whose timing in relation to song remains unresolved. This opens the opportunity to define models relating explicit HVC circuitry to how these neurons work cooperatively to control learning and singing. We developed conductance-based Hodgkin-Huxley models for the three classes of HVC neurons (based on the ion channels previously identified from in vitro recordings) and connected them in several physiologically realistic networks (based on the known synaptic connectivity and specific glutaminergic and gabaergic pharmacology) via different architecture patterning scenarios with the aim to replicate the in vivo firing patterning behaviors. We are able, through these networks, to reproduce the in vivo behavior of each class of HVC neurons, as shown by the experimental recordings. The different network architectures developed highlight different mechanisms that might be contributing to the propagation of sequential neural activity (continuous or punctate) in the HVC and to the distinctive firing patterns that each class exhibits during singing. Examples of such possible mechanisms include: 1) post-inhibitory rebound in HVCX and their population patterns during singing, 2) different subclasses of HVCINT interacting via inhibitory-inhibitory loops, 3) mono-synaptic HVCX to HVCRA excitatory connectivity, and 4) structured many-to-one inhibitory synapses from interneurons to projection neurons, and others. Replication is only a preliminary step that must be followed by model prediction and testing.

Keywords: computational modeling, neural networks, temporal neural sequences, ionic currents, songbird

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Authors: Mustafa M. Donma, Orkide Donma

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Obesity and weight gain are associated with increased risk of developing cardiovascular diseases and the progression of liver fibrosis. Aspartate transaminase–to-platelet count ratio index (AST-to-PLT, APRI) and fibrosis-4 (FIB-4) were primarily considered as the formulas capable of differentiating hepatitis from cirrhosis. Recently, they have found clinical use as measures of liver fibrosis and cardiovascular risk. However, their status in children has not been evaluated in detail yet. The aim of this study is to determine APRI and FIB-4 status in obese (OB) children and compare them with values found in children with normal body mass index (N-BMI). A total of sixty-eight children examined in the outpatient clinics of the Pediatrics Department in Tekirdag Namik Kemal University Medical Faculty were included in the study. Two groups were constituted. In the first group, thirty-five children with N-BMI, whose age- and sex-dependent BMI indices vary between 15 and 85 percentiles, were evaluated. The second group comprised thirty-three OB children whose BMI percentile values were between 95 and 99. Anthropometric measurements and routine biochemical tests were performed. Using these parameters, values for the related indices, BMI, APRI, and FIB-4, were calculated. Appropriate statistical tests were used for the evaluation of the study data. The statistical significance degree was accepted as p<0.05. In the OB group, values found for APRI and FIB-4 were higher than those calculated for the N-BMI group. However, there was no statistically significant difference between the N-BMI and OB groups in terms of APRI and FIB-4. A similar pattern was detected for triglyceride (TRG) values. The correlation coefficient and degree of significance between APRI and FIB-4 were r=0.336 and p=0.065 in the N-BMI group. On the other hand, they were r=0.707 and p=0.001 in the OB group. Associations of these two indices with TRG have shown that this parameter was strongly correlated (p<0.001) both with APRI and FIB-4 in the OB group, whereas no correlation was calculated in children with N-BMI. Triglycerides are associated with an increased risk of fatty liver, which can progress to severe clinical problems such as steatohepatitis, which can lead to liver fibrosis. Triglycerides are also independent risk factors for cardiovascular disease. In conclusion, the lack of correlation between TRG and APRI as well as FIB-4 in children with N-BMI, along with the detection of strong correlations of TRG with these indices in OB children, was the indicator of the possible onset of the tendency towards the development of fatty liver in OB children. This finding also pointed out the potential risk for cardiovascular pathologies in OB children. The nature of the difference between APRI vs FIB-4 correlations in N-BMI and OB groups (no correlation versus high correlation), respectively, may be the indicator of the importance of involving age and alanine transaminase parameters in addition to AST and PLT in the formula designed for FIB-4.

Keywords: APRI, children, FIB-4, obesity, triglycerides

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Authors: Saeed Sayyad Hagh Shomar

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Traffic congestion pricing in urban streets is one of the most suitable options for solving the traffic problems and environment pollutions in the cities of the country. Unlike its acceptable outcomes, there are problems concerning the necessity to pay by the mass. Regarding the fact that public response in order to succeed in this strategy is so influential, studying their response and behavior to get the feedback and improve the strategies is of great importance. In this study, a questionnaire was used to examine the public reactions to the traffic congestion pricing schemes at the center of Tehran metropolis and the factors involved in people’s decision making in accepting or rejecting the congestion pricing schemes were assessed based on the data obtained from the questionnaire as well as the international experiences. Then, by analyzing and comparing the schemes, guidelines to reduce public objections to them are discussed. The results of reviewing and evaluating the public reactions show that all the pros and cons must be considered to guarantee the success of these projects. Consequently, with targeted public education and consciousness-raising advertisements, prior to initiating a scheme and ensuring the mechanism of the implementation after the start of the project, the initial opposition is reduced and, with the gradual emergence of the real and tangible benefits of its implementation, users’ satisfaction will increase.

Keywords: demand management, international experiences, traffic congestion pricing, public acceptance, public reactions, public objection

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Authors: Bilal Arshad, Johan Barthelemy, Elliott Pilton, Pascal Perez

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Getting reliable, informative, and up-to-date information about the location, mobility, and behavioural patterns of animals will enhance our ability to research and preserve biodiversity. The fusion of infra-red sensors and camera traps offers an inexpensive way to collect wildlife data in the form of images. However, extracting useful data from these images, such as the identification and counting of animals remains a manual, time-consuming, and costly process. In this paper, we demonstrate that such information can be automatically retrieved by using state-of-the-art deep learning methods. Another major challenge that ecologists are facing is the recounting of one single animal multiple times due to that animal reappearing in other images taken by the same or other camera traps. Nonetheless, such information can be extremely useful for tracking wildlife and understanding its behaviour. To tackle the multiple count problem, we have designed a meshed network of camera traps, so they can share the captured images along with timestamps, cumulative counts, and dimensions of the animal. The proposed method takes leverage of edge computing to support real-time tracking and monitoring of wildlife. This method has been validated in the field and can be easily extended to other applications focusing on wildlife monitoring and management, where the traditional way of monitoring is expensive and time-consuming.

Keywords: computer vision, ecology, internet of things, invasive species management, wildlife management

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Authors: Mohammad Reza Zamani Kouhpanji

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Characterizing the fatigue and fracture properties of nanostructures is one of the most challenging tasks in nanoscience and nanotechnology due to lack of a MEMS/NEMS device for generating uniform cyclic loadings at high frequencies. Here, the dynamic response of a recently proposed MEMS/NEMS device under different inputs signals is completely investigated. This MEMS/NEMS device is designed and modeled based on the electromagnetic force induced between paired parallel wires carrying electrical currents, known as Ampere’s Force Law (AFL). Since this MEMS/NEMS device only uses two paired wires for actuation part and sensing part, it represents highly sensitive and linear response for nanostructures with any stiffness and shapes (single or arrays of nanowires, nanotubes, nanosheets or nanowalls). In addition to studying the maximum gains at different resonance frequencies of the MEMS/NEMS device, its dynamical responses are investigated for different inputs and nanostructure properties to demonstrate the capability, usability, and reliability of the device for wide range of nanostructures. This MEMS/NEMS device can be readily integrated into SEM/TEM instruments to provide real time study of the fatigue and fracture properties of nanostructures as well as their softening or hardening behaviors, and initiation and/or propagation of nanocracks in them.

Keywords: MEMS/NEMS devices, paired wire actuators and sensors, dynamical response, fatigue and fracture characterization, Ampere’s force law

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Authors: D. S. Gurjar, R. Kaur, K. P. Singh, R. Singh

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A greater volume of wastewater generate from urban areas in India. Due to the adequate availability, less energy requirement and nutrient richness, farmers of urban and peri-urban areas are deliberately using wastewater to grow high value vegetable crops. Wastewater contains pathogens and toxic pollutants, which can enter in the food chain system while using wastewater for irrigating vegetable crops. Hence, wastewater can use for growing commercial flower crops that may avoid food chain contamination. Tuberose (Polianthes tuberosa L.) is one of the most important commercially grown, cultivated over 30, 000 ha area, flower crop in India. Its popularity is mainly due to the sweet fragrance as well as the long keeping quality of the flower spikes. The flower spikes of tuberose has high market price and usually blooms during summer and rainy seasons when there is meager supply of other flowers in the market. It has high irrigation water requirement and fresh water supply is inadequate in tuberose growing areas of India. Therefore, wastewater may fulfill the water and nutrients requirements and may enhance the productivity of tuberose. Keeping in view, the present study was carried out at WTC farm of ICAR-Indian Agricultural Research Institute, New Delhi in 2014-15. Prajwal was the variety of test crop. The seven treatments were taken as T-1. Wastewater irrigation at 0.6 ID/CPE, T-2: Wastewater irrigation at 0.8 ID/CPE, T-3: Wastewater irrigation at 1.0 ID/CPE, T-4: Wastewater irrigation at 1.2 ID/CPE, T-5: Wastewater irrigation at 1.4 ID/CPE, T-6: Conjunctive use of Groundwater and Wastewater irrigation at 1.0 ID/CPE in cyclic mode, T-7: Control (Groundwater irrigation at 1.0 ID/CPE) in randomized block design with three replication. Wastewater and groundwater samples were collected on monthly basis (April 2014 to March 2015) and analyzed for different parameters of irrigation quality (pH, EC, SAR, RSC), pollution hazard (BOD, toxic heavy metals and Faecal coliforms) and nutrients potential (N, P, K, Cu, Fe, Mn, Zn) as per standard methods. After harvest of tuberose crop, soil samples were also collected and analyzed for different parameters of soil quality as per standard methods. The vegetative growth and flower parameters were recorded at flowering stage of tuberose plants. Results indicated that wastewater samples had higher nutrient potential, pollution hazard as compared to groundwater used in experimental crop. Soil quality parameters such as pH EC, available phosphorous & potassium and heavy metals (Cu, Fe, Mn, Zn, Cd. Pb, Ni, Cr, Co, As) were not significantly changed whereas organic carbon and available nitrogen were significant higher in the treatments where wastewater irrigations were given at 1.2 and 1.4 ID/CPE as compared to groundwater irrigations. Significantly higher plant height (68.47 cm), leaves per plant (78.35), spike length (99.93 cm), rachis length (37.40 cm), numbers of florets per spike (56.53), cut spike yield (0.93 lakh/ha) and loose flower yield (8.5 t/ha) were observed in the treatment of Wastewater irrigation at 1.2 ID/CPE. Study concluded that given quality of wastewater improves the productivity of tuberose without an adverse impact on soil quality/health. However, its long term impacts need to be further evaluated.

Keywords: conjunctive use, irrigation, tuberose, wastewater

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Authors: Jens Hagman, Jenny Janhager Stier, Ellen Olausson, Anne Y. Faxer, Ana Magazinius

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Sweden has the second highest electric vehicle (plug-in hybrid and battery electric vehicle) sales per capita in Europe but in relation to sales of internal combustion engine electric vehicles sales are still minuscular (< 4%). Much research effort has been placed on various technical and user focused barriers and enablers for adoption of electric vehicles. Less effort has been placed on investigating the retail (dealership-customer) sales process of vehicles in general and electric vehicles in particular. Arguably, no one ought to be better informed about needs and desires of potential electric vehicle buyers than car salesmen, originating from their daily encounters with customers at the dealership. The aim of this paper is to explore the conditions of selling electric vehicle from a car salesmen’s perspective. This includes identifying barriers and enablers for electric vehicle sales originating from internal (dealership and brand) and external (customer, government) sources. In this interview study five car brands (manufacturers) that sell both electric and internal combustion engine vehicles have been investigated. A total of 15 semi-structured interviews have been conducted (three per brand, in rural and urban settings and at different dealerships). Initial analysis reveals several barriers and enablers, experienced by car salesmen, which influence electric vehicle sales. Examples of as reported by car salesmen identified barriers are: -Electric vehicles earn car salesmen less commission on average compared to internal combustion engine vehicles. -It takes more time to sell and deliver an electric vehicle than an internal combustion engine vehicle. -Current leasing contracts entails relatively low second-hand value estimations for electric vehicles and thus a high leasing fee, which negatively affects the attractiveness of electric vehicles for private consumers in particular. -High purchasing price discourages many consumers from considering electric vehicles. -The education and knowledge level of electric vehicles differs between car salesmen, which could affect their self-confidence in meeting well prepared and question prone electric vehicle buyers. Examples of identified enablers are: -Company car tax regulation promotes sales of electric vehicles; in particular, plug-in hybrid electric vehicles are sold extensively to companies (up to 95 % of sales). -Low operating cost of electric vehicles such as fuel and service is an advantage when understood by consumers. -The drive performance of electric vehicles (quick, silent and fun to drive) is attractive to consumers. -Environmental aspects are considered important for certain consumer groups. -Fast technological improvements, such as increased range are opening up a wider market for electric vehicles. -For one of the brands; attractive private lease campaigns have proved effective to promote sales. This paper gives insights of an important but often overlooked aspect for the diffusion of electric vehicles (and durable products in general); the interaction between car salesmen and customers at the critical acquiring moment. Extracted through interviews with multiple car salesmen. The results illuminate untapped potential for sellers (salesmen, dealerships and brands) to mitigating sales barriers and strengthening sales enablers and thus becoming a more important actor in the electric vehicle diffusion process.

Keywords: customer barriers, electric vehicle promotion, sales of electric vehicles, interviews with car salesmen

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Authors: Mohammad Ali Karimi, Hossein Tavallali, Abdolhamid Hatefi-Mehrjardi

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In this study, an electrochemical sensor based on gold nanoparticles (AuNPs) functionalized improved graphene (AuNPs-IGE) was fabricated for selective determination of L-dopa in the presence of ascorbic acid by a novel self-assembly method. The AuNP IGE modified carbon paste electrode (AuNPs-IGE/CPE) utilized for investigation of the electrochemical behavior of L-dopa in phosphate buffer solution. Compared to bare CPE, AuNPs-IGE/CPE shows novel properties towards the electrochemical redox of levodopa (L-dopa) in phosphate buffer solution at pH 4.0. The oxidation potential of L-dopa shows a significant decrease at the AuNPs-IGE/CPE. The oxidation current of L-dopa is higher than that of the unmodified CPE. AuNPs-IG/CPE shows excellent electrocatalytic activity for the oxidation of ascorbic acid (AA). Using differential pulse voltammetry (DPV) method, the oxidation current is well linear with L-dopa concentration in the range of 0.4–50 µmol L-1, with a detection limit of about 1.41 nmol L-1 (S/N = 3). Therefore, it was applied to measure L-dopa from real samples that recoveries are 94.6-106.2%. The proposed electrode can also effectively avoid the interference of ascorbic acid, making the proposed sensor suitable for the accurate determination of L-dopa in both pharmaceutical preparations and human body fluids.

Keywords: gold nanoparticles, improved graphene, L-dopa, self-assembly

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Authors: Afef Badri

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Metaphorical creativity does not constitute a static property of discourse. It is an interactive dynamic process created online. There has been a lack of research concerning online produced metaphorical creativity. This paper intends to account for metaphorical creativity in online talk-in-interaction as a dynamic process that emerges as discourse unfolds. It brings together insights from the emergentist approach to the study of metaphor in verbal interactions and insights from conceptual blending approach as a model for analysing online metaphorical constructions to propose a model for studying metaphorical creativity in interactive talk. The model is based on three focal points. First, metaphorical creativity is a dynamic emergent and open-to-change process that evolves in real time as interlocutors constantly blend and re-blend previous metaphorical contributions. Second, it is not a product of isolated individual minds but a joint achievement that is co-constructed and co-elaborated by interlocutors. The third and most important point is that the emergent process of metaphorical creativity is tightly shaped by contextual variables surrounding talk-in-interaction. It is grounded in the framework of interpretation of interlocutors. It is constrained by preceding contributions in a way that creates textual cohesion of the verbal exchange and it is also a goal-oriented process predefined by the communicative intention of each participant in a way that reveals the ideological coherence/incoherence of the entire conversation.

Keywords: communicative intention, conceptual blending, the emergentist approach, metaphorical creativity

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Authors: M. Taghavi Zavareh, H. Saremi

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Railway transportation is one of the types of transportation systems which, due to the advantages such as the ability to transport a large number of passengers, environmental protection, low energy consumption, and contribution to tourism, has importance. The existence of suitable and accessible stations is one of the requirements that leads to better performance and plays a significant role in the economic, social, political, and cultural development of urban areas. This paper aims to propose a framework for locating railway passenger stations. This research used descriptive-analytical methods and library tools to answer which definitions and theoretical approaches are suitable for the location of railway passenger stations. The results showed that theoretical approaches such as Transit-Oriented Development and Urban Regeneration are of the utmost importance theoretical bases in the field of research. Moreover, we studied three stations in Iran to find out about real trends and criteria in this research. This study also proposed four major criteria including accessibility, development, rail related and economics, and environmental harmony. Ultimately with an emphasis on the proposed criteria, the study concludes that the combination of Transit-Oriented Development and Urban Regeneration is the most suitable framework to locate railway passenger stations.

Keywords: railway passenger station, railway station, site selection, transit-oriented development, urban regeneration

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Authors: Leila Niroomand, Reza Rafigh

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Nowadays, the world is going under a dramatic change from an industry-centered society to an information-centered one. In other words, we are experiencing a transition from real, physical world into a virtual one. Stepping into the information age and running an effective life within the information-centered society demands getting acquainted with characteristics peculiar to such society. Recently, new technologies such as telecommunication and mobile technologies have changed vehemently and accumulation of achievements and information has become so important and brought about changes in occupational structures. The intellectual structure of this day and age depends on deep attention to creative and knowledge-based human resource collaboration instead of merely functioning human resource. Present study scrutinizes the contribution of different dimensions of mobile technologies including perceived use, perceived enjoyment, continuance intention, confirmation and satisfaction to the creativity of personnel. The statistical population included infrastructure communications company employees totaling 2431 persons out of which 331 individuals were chosen as sample based on Morgan and Krejcie table. This research is descriptive and the questionnaire was used for data gathering and it was distributed among those who used telegram application. 228 questionnaires were analyzed by the researcher. Applying SPSS software, Pierson correlation coefficient was analyzed and it was found out that all dimensions of mobile technologies except satisfaction correlate with the creativity of employees.

Keywords: mobile technologies, continuance intention, perceived enjoyment, confirmation, satisfaction, creativity, perceived use

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Authors: Francesca La Rosa , Marina Saresella, Mario Clerici, Michael Heneka

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Neuroinflammation plays a key role in the modulation of the pathogenesis of neurodegenerative disorder such as Alzheimer's Disease (AD). Microglia, the main immune effector of the brain, are able to migrate to sites of Amyloid-beta (Aβ) deposition to eliminate Aβ phagocytosis upon activation by multiple receptors: Toll like receptors and scavenger receptors. The issue of whether microglia are able to eliminate pathological lesions such as neurofibrillary tangles or senile plaques from AD brain still remains the matter of controversy. Recent data suggest that the Nod Like Receptor 3 (NLRP3), multiprotein inflammasome complexes, plays a role in AD, as its activation in the microglia by Aβ triggers. IL-1β is produced as a biologically inactive pro-form and requires caspase-1 for activation and secretion. Caspase-1 activity is controlled by inflammasomes. We investigate about the importance of inflammasomes complex in the Aβ phagocytosis and its degradation. The preliminary results of phagocytosis assay and immunofluorescent experiment on primary Microglia cells to lipopolysaccharide (LPS) an Aβ exposure show that a previous treatment with LPS reduce Aβ phagocytosis. Different results were obtained in Primary Microglia wild type, NLRP3 and ASC Knockout suggesting a real inflammasomes involvement in Alzheimer's pathology. Inflammasomes inactivation reduces the production of inflammatory cytokines prolonging the protective activity of microglia and Aβ clearance, featuring a typical microglia phenotype of the early stage of AD disease.

Keywords: Alzheimer disease, innate immunity, neuroinflammation, NLRP3

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Authors: F. Hamidi, N. Amiri, H. Mishmast Nehi

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The Bilevel Programming (BP) model has been presented for a decision making process that consists of two decision makers in a hierarchical structure. In fact, BP is a model for a static two person game (the leader player in the upper level and the follower player in the lower level) wherein each player tries to optimize his/her personal objective function under dependent constraints; this game is sequential and non-cooperative. The decision making variables are divided between the two players and one’s choice affects the other’s benefit and choices. In other words, BP consists of two nested optimization problems with two objective functions (upper and lower) where the constraint region of the upper level problem is implicitly determined by the lower level problem. In real cases, the coefficients of an optimization problem may not be precise, i.e. they may be interval. In this paper we develop an algorithm for solving interval bilevel linear fractional programming problems. That is to say, bilevel problems in which both objective functions are linear fractional, the coefficients are interval and the common constraint region is a polyhedron. From the original problem, the best and the worst bilevel linear fractional problems have been derived and then, using the extended Charnes and Cooper transformation, each fractional problem can be reduced to a linear problem. Then we can find the best and the worst optimal values of the leader objective function by two algorithms.

Keywords: best and worst optimal solutions, bilevel programming, fractional, interval coefficients

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Authors: Priya Pawar, Rithika Susan Thomas, Emmanuel Blonkowski

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Due to the solar geometry of Singapore, which lay within the geographical classification of equatorial tropics, there is a great deal of thermal energy transfer to the inside of the buildings. With changing face of economic development of cities like Singapore, more and more buildings are designed to be lightweight using transparent construction materials such as glass. Increased demand for energy efficiency and reduced cooling load demands make it important for building designer and operators to adopt new and non-invasive technologies to achieve building energy efficiency targets. A real time performance evaluation study was undertaken at School of Art Design and Media (SADM), Singapore, to determine the efficiency potential of a new generation solar insulation film. The building has a window to wall ratio (WWR) of 100% and is fitted with high performance (low emissivity) double glazed units. The empirical data collected was then used to calibrate a computerized simulation model to understand the annual energy consumption based on existing conditions (baseline performance). It was found that the correlations of various parameters such as solar irradiance, solar heat flux, and outdoor air-temperatures quantification are significantly important to determine the cooling load during a particular period of testing.

Keywords: solar insulation film, building energy efficiency, tropics, cooling load

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Authors: Simone Jane Dennis

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This paper leverages the spatial and temporal investigative strategy utilized by crime scene investigators – blood spatter work– to engage with the real and metaphorical memorialization of blood-soaked places. It uses this key trope with phenomenological sensibility, to trace the physical and temporal movement of blood outbound from the human body to sites beyond. Working backward, as crime scene investigators do, this paper traces the importance of both space and time and their confluence, to developing a comprehensive theory of violence. To do this work, the paper engages a range of geo-violent scales, from murder scenes to genocides, to both engage an extraordinarily replete literature of bloodshed across history and to move beyond analyses of how significance is assigned to the sites in which blood comes to rest to instead consider the importance of space and time to the structure of violence itself. It is in this regard that the kind of investigative work upon which blood spatter analysis depends is crucial: it engages time and space in reverse to understand the microscopic relations between bodies, places, and numerous (biological, clock, and seasonal) temporalities. Considering the circumstances under which blood escaped a body, the details of its destination in place, and the temporal circumstances of corporal departure, is crucial to making new knowledge about the peculiar temporality and spatiality of violence itself.

Keywords: blood, crime scenes, temporality, violence

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Authors: Niklas Panten, Eberhard Abele

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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control

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Authors: Ella Tyuryumina, Alexey Neznanov

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Finding algorithms to predict the growth of tumors has piqued the interest of researchers ever since the early days of cancer research. A number of studies were carried out as an attempt to obtain reliable data on the natural history of breast cancer growth. Mathematical modeling can play a very important role in the prognosis of tumor process of breast cancer. However, mathematical models describe primary tumor growth and metastases growth separately. Consequently, we propose a mathematical growth model for primary tumor and primary metastases which may help to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoM-IV and corresponding software. We are interested in: 1) modelling the whole natural history of primary tumor and primary metastases; 2) developing adequate and precise CoM-IV which reflects relations between PT and MTS; 3) analyzing the CoM-IV scope of application; 4) implementing the model as a software tool. The CoM-IV is based on exponential tumor growth model and consists of a system of determinate nonlinear and linear equations; corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and primary metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for primary metastases; 3) ‘visible period’ for primary metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-IV model and predictive software: a) detect different growth periods of primary tumor and primary metastases; b) make forecast of the period of primary metastases appearance; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of BC and facilitate optimization of diagnostic tests. The following are calculated by CoM-IV: the number of doublings for ‘nonvisible’ and ‘visible’ growth period of primary metastases; tumor volume doubling time (days) for ‘nonvisible’ and ‘visible’ growth period of primary metastases. The CoM-IV enables, for the first time, to predict the whole natural history of primary tumor and primary metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-IV describes correctly primary tumor and primary distant metastases growth of IV (T1-4N0-3M1) stage with (N1-3) or without regional metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and manifestation of primary metastases.

Keywords: breast cancer, exponential growth model, mathematical modelling, primary metastases, primary tumor, survival

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Authors: C. A. Anser Pasha

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In this paper, a new Vehicular Speed Detection Camera System that is applicable as an alternative to traditional radars with the same accuracy or even better is presented. The real-time measurement and analysis of various traffic parameters such as speed and number of vehicles are increasingly required in traffic control and management. Image processing techniques are now considered as an attractive and flexible method for automatic analysis and data collections in traffic engineering. Various algorithms based on image processing techniques have been applied to detect multiple vehicles and track them. The SDCS processes can be divided into three successive phases; the first phase is Objects detection phase, which uses a hybrid algorithm based on combining an adaptive background subtraction technique with a three-frame differencing algorithm which ratifies the major drawback of using only adaptive background subtraction. The second phase is Objects tracking, which consists of three successive operations - object segmentation, object labeling, and object center extraction. Objects tracking operation takes into consideration the different possible scenarios of the moving object like simple tracking, the object has left the scene, the object has entered the scene, object crossed by another object, and object leaves and another one enters the scene. The third phase is speed calculation phase, which is calculated from the number of frames consumed by the object to pass by the scene.

Keywords: radar, image processing, detection, tracking, segmentation

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Authors: Fina O. Faithpraise, Effiong O. Obisung, Azele E. Peter, Chris R. Chatwin

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This study investigates and identifies consumer attitude as a major influence that results in non-technical losses in the Nigerian electricity supply sector. This discovery is revealed by the combination of quantitative and qualitative research to complete a survey. The dataset employed is a simple random sampling of households using electricity (public power supply), and the number of units chosen is based on statistical power analysis. The units were subdivided into two categories (household with and without electrical meters). The hypothesis formulated was tested and analyzed using a chi-square statistical method. The results obtained shows that the critical value for the household with electrical prepared meter (EPM) was (9.488 < 427.4) and those without electrical prepared meter (EPMn) was (9.488 < 436.1) with a p-value of 0.01%. The analysis demonstrated so far established the real-time position, which shows that the wrong attitude towards handling the electricity supplied (not turning off light bulbs and electrical appliances when not in use within the rooms and outdoors within 12 hours of the day) characterized the non-technical losses in the power sector. Therefore the adoption of efficient lighting attitudes in individual households as recommended by the researcher is greatly encouraged. The results from this study should serve as a model for energy efficiency and use for the improvement of electricity consumption as well as a stable economy.

Keywords: attitudinal change, household, non-technical losses, prepared meter

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Authors: Cara DiGirolamo

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In his 2017 Ph.D. thesis, script doctor David Baboulene presented a theory of fiction in which differences in the knowledge states between participants in a literary experience, including reader, author, and characters, create many story elements, among them suspense, expectations, subtext, theme, metaphor, and allegory. This theory can be adjusted and modeled by incorporating a formal pragmatic approach that understands narrative as a speech act with a conversational function. This approach requires both the Speaker and the Listener to be understood as participants in the discourse. It also uses theories of cooperativity and the QUD to identify the existence of implicit questions. This approach predicts that what an effective literary narrative must do: provide a conversational context early in the story so the reader can engage with the text as a conversational participant. In addition, this model incorporates schema theory. Schema theory is a cognitive model for learning and processing information about the world and transforming it into functional knowledge. Using this approach can extend the QUD model. Instead of describing conversation as a form of information gathering restricted to question-answer sets, the QUD can include knowledge modeling and understanding as a possible outcome of a conversation. With this model, Baboulene’s “Knowledge Gaps” can provide real insight into storytelling as a conversational move, and extend the QUD to be able to simply and effectively apply to a more diverse set of conversational interactions and also to narrative texts.

Keywords: literature, speech acts, QUD, literary theory

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Authors: Suganya Chandrababu, Dhundy Bastola

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Like in the gut, the subgingival microbiota plays a crucial role in oral hygiene, health, and cariogenic diseases. Human activities like diet, antibiotics, and periodontal treatments alter the bacterial communities, metabolism, and functions in the oral cavity, leading to a dysbiotic state and changes in the plaques of orthodontic patients. Fixed periodontal appliances hinder oral hygiene and cause changes in the dental plaques influencing the subgingival microbiota. However, the microbial species’ diversity and complexity pose a great challenge in understanding the taxa’s community distribution patterns and their role in oral health. In this research, we analyze the subgingival microbial samples from individuals with fixed dental appliances (metal/clear) using an in silico approach. We employ exploratory hypothesis-driven multivariate and regression analysis to shed light on the microbial community and its functional fluctuations due to dental appliances used and identify risks associated with complex disease phenotypes. Our findings confirm the changes in oral microbiota composition due to the presence and type of fixed orthodontal devices. We identified seven main periodontic pathogens, including Bacteroidetes, Actinobacteria, Proteobacteria, Fusobacteria, and Firmicutes, whose abundances were significantly altered due to the presence and type of fixed appliances used. In the case of metal braces, the abundances of Bacteroidetes, Proteobacteria, Fusobacteria, Candidatus saccharibacteria, and Spirochaetes significantly increased, while the abundance of Firmicutes and Actinobacteria decreased. However, in individuals With clear braces, the abundance of Bacteroidetes and Candidatus saccharibacteria increased. The highest abundance value (P-value=0.004 < 0.05) was observed with Bacteroidetes in individuals with the metal appliance, which is associated with gingivitis, periodontitis, endodontic infections, and odontogenic abscesses. Overall, the bacterial abundances decrease with clear type and increase with metal type of braces. Regression analysis further validated the multivariate analysis of variance (MANOVA) results, supporting the hypothesis that the presence and type of the fixed oral appliances significantly alter the bacterial abundance and composition.

Keywords: oral microbiota, statistical analysis, fixed or-thodontal appliances, bacterial abundance, multivariate analysis, regression analysis

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Authors: Barenten Suciu, Ryoichi Kinoshita

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In this paper, an experimental and theoretical study on the bogie pseudo-hunting motion of a reduced-scale model railway vehicle, running on double-curved rails, is presented. Since the actual bogie hunting motion, occurring for real railway vehicles running on straight rails at high travelling speeds, cannot be obtained in laboratory conditions, due to the speed and wavelength limitations, a pseudo- hunting motion was induced by employing double-curved rails. Firstly, the test rig and the experimental procedure are described. Then, a geometrical model of the double-curved rails is presented. Based on such model, the variation of the carriage rotation angle relative to the bogies and the working conditions of the yaw damper are clarified. Vibration spectra recorded during vehicle travelling, on straight and double-curved rails, are presented and interpreted based on a simple vibration model of the railway vehicle. Ride comfort of the vehicle is evaluated according to the ISO 2631 standard, and also by using some particular frequency weightings, which account for the discomfort perceived during the reading and writing activities. Results obtained in this work are useful for the adequate design of the yaw dampers, which are used to attenuate the lateral vibration of the train car bodies.

Keywords: double-curved rail, octave analysis, vibration model, ride comfort, railway vehicle

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Authors: Kolja Them, Priyal Chikhaliwala, Sudeshna Chandra

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Purpose: The purpose of this work is to examine possibilities for noninvasive imaging and identification of tumor markers for cancer diagnosis. The proposed method uses antibody conjugated iron oxide nanoparticles and multicolor Magnetic Particle Imaging (mMPI). The method has the potential for radiation exposure free real-time estimation of local tumor marker concentrations in vivo. In this study, the method is applied to human Alpha-1-Fetoprotein. Materials and Methods: As tracer material AFP antibody-conjugated Dendrimer-Fe3O4 nanoparticles were used. The nanoparticle bioconjugates were then incubated with bovine serum albumin (BSA) to block any possible nonspecific binding sites. Parts of the resulting solution were then incubated with AFP antigen. MPI measurements were done using the preclinical MPI scanner (Bruker Biospin MRI GmbH) and the multicolor method was used for image reconstruction. Results: In multicolor MPI images the nanoparticles incubated only with BSA were clearly distinguished from nanoparticles incubated with BSA and AFP antigens. Conclusion: Tomographic imaging of human tumor marker Alpha-1-Fetoprotein is possible using AFP antibody conjugated iron oxide nanoparticles in presence of BSA. This opens interesting perspectives for cancer diagnosis.

Keywords: noninvasive imaging, tumor antigens, antibody conjugated iron oxide nanoparticles, multicolor magnetic particle imaging, cancer diagnosis

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Authors: Renata Adriana Labanca, Gabriela Rezende Costa, Nilton de Oliveira Couto e Silva, José Marcos Gontijo Mandarino, Rodrigo Santos Leite, Nilson César Castanheira Guimarães, Roberto Gonçalves Junqueira

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The objective of this study was to evaluate the differences in composition between six brands of conventional soybean and six genetically modified cultivars (GM), all of them from Minas Gerais State, Brazil. We focused on the isoflavones profile and mineral content questioning the substantial equivalence between conventional and GM organisms. The statement of compliance label for conventional grains was verified for the presence of genetic modified genes by real time polymerase chain reaction (PCR). We did not detect the presence of the 35S promoter in commercial samples, indicating the absence of transgene insertion. For mineral analysis, we used the method of inductively coupled plasma-optical emission spectrometry (ICP-OES). Isoflavones quantification was performed by high performance liquid chromatography (HPLC). The results showed no statistical difference between the conventional and transgenic soybean groups concerning isoflavone content and mineral composition. The concentration of potassium, the main mineral component of soy, was the highest in conventional soybeans compared to that in GM soy, while GM samples presented the highest concentrations of iron.

Keywords: glycine max, genetically modified organism, bioactive compounds, ICP-OES, HPLC

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Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

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Authors: Krasimir Ivanov, Dimitar Dimitrov, Tatyana Tabakova, Stefka Kirkova, Anna Stoilova, Violina Angelova

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It has been suggested that nicotine, CO and tar in mainstream smoke are the most important substances and have been judged as the most harmful compounds, responsible for the health hazards of smoking. As nicotine is extremely important for smoking qualities of cigarettes and the tar yield in the tobacco smoke is significantly reduced due to the use of filters with various content and design, the main efforts of cigarettes researchers and manufacturers are related to the search of opportunities for CO content reduction. Highly active ceria supported gold catalyst was prepared by the deposition-precipitation method, and the possibilities for CO oxidation in the synthetic gaseous mixture were evaluated using continuous flow equipment with fixed bed glass reactor at atmospheric pressure. The efficiently of the catalyst in CO oxidation in the real cigarette smoke was examined by a single port, puf-by-puff smoking machine. Quality assessment of smoking using cigarette holder containing catalyst was carried out. It was established that the catalytic activity toward CO oxidation in cigarette smoke rapidly decreases from 70% for the first cigarette to nearly zero for the twentieth cigarette. The present study shows that there are two critical factors which do not permit the successful use of catalysts to reduce the CO content in the mainstream cigarette smoke: (i) significant influence of the processes of adsorption and oxidation on the main characteristics of tobacco products and (ii) rapid deactivation of the catalyst due to the covering of the catalyst’s grains with condensate.

Keywords: cigarette smoke, CO oxidation, gold catalyst, mainstream

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Authors: Matthew Ndubuisi Abonyi, Christopher Chiedozie Obi, Joseph Tagbo Nwabanne

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This review focuses on the application of Metal-Organic Frameworks (MOF)-based catalysts in the degradation of organic pollutants in wastewater. The degradation of organic pollutants in wastewater remains a critical environmental challenge, necessitating innovative solutions for effective treatment. MOFs have garnered significant attention as promising catalysts for this purpose, owing to their exceptional surface area, tunable porosity, and diverse chemical functionalities. It explores various catalytic mechanisms, including photocatalysis, Fenton-like reactions, and other advanced oxidation processes facilitated by MOFs. The review also explores the design strategies that enhance the catalytic performance of MOFs, such as structural modifications, composite formation, and post-synthetic modifications. Furthermore, real-world case studies are presented, highlighting the practical applications and environmental impact of MOF-based catalysts in wastewater treatment. Challenges associated with the scalability and stability of these materials are discussed, along with future directions for research and development. This review highlights the significant potential of MOF-based catalysts in addressing the pressing issue of water pollution and advocates for continued innovation to optimize their application in wastewater treatment.

Keywords: metal-organic frameworks (MOFs), catalysis, wastewater treatment, organic pollutant degradation, photocatalysis

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Authors: Nikolai Brosch, Alwine Mohnen

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Academics and business leaders increasingly call for a (re)definition of a corporate purpose beyond profit-maximization to contribute to the welfare of society. This study investigates the effect of communicating such a pro-social corporate purpose on three employee-level outcomes that constitute major cost components for most organizations: workers reservation wage, work quality, and work misbehavior. To provide causal evidence, two natural field experiments were conducted with almost 2,000 workers recruited from different online labor marketplaces. Workers were randomly assigned to treatments manipulating whether or not they received information about the employer’s corporate purpose and subsequently performed a short, real-effort task for payment. The main findings in both experiments show that receiving information about an employer’s pro-social corporate purpose causes workers to accept lower wages (9% lower in the first experiment and 28% lower in the second experiment) for the same job. Workers that personally assess high importance to organizations having a pro-social purpose are most responsive. At the same time, sacrificing wage for a corporate purpose comes at no cost of quality and even decreases the likelihood of engaging in work misbehavior. In a broader context, the results provide some evidence that the (re)definition of corporate purpose in commercial organizations is not ultimately at odds with creating profits.

Keywords: corporate purpose, natural field experiment, reservation wage, work misbehavior, work quality

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Authors: Imen Boudali, Marwa Ragmoun

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The Vehicle Routing Problem with Hard Time Windows (VRPHTW) is a basic distribution management problem that models many real-world problems. The objective of the problem is to deliver a set of customers with known demands on minimum-cost vehicle routes while satisfying vehicle capacity and hard time windows for customers. In this paper, we propose to deal with our optimization problem by using a new hybrid stochastic algorithm based on two metaheuristics: Chemical Reaction Optimization (CRO) and Greedy Randomized Adaptive Search Procedure (GRASP). The first method is inspired by the natural process of chemical reactions enabling the transformation of unstable substances with excessive energy to stable ones. During this process, the molecules interact with each other through a series of elementary reactions to reach minimum energy for their existence. This property is embedded in CRO to solve the VRPHTW. In order to enhance the population diversity throughout the search process, we integrated the GRASP in our method. Simulation results on the base of Solomon’s benchmark instances show the very satisfactory performances of the proposed approach.

Keywords: Benchmark Problems, Combinatorial Optimization, Vehicle Routing Problem with Hard Time Windows, Meta-heuristics, Hybridization, GRASP, CRO

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