Search results for: multi criteria decision making (MCDM)

Authors: K. M. Alsager, N. O. Alshehri

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In this paper, we proposed the notion of single valued neutrosophic hesitant fuzzy rough set, by combining single valued neutrosophic hesitant fuzzy set and rough set. The combination of single valued neutrosophic hesitant fuzzy set and rough set is a powerful tool for dealing with uncertainty, granularity and incompleteness of knowledge in information systems. We presented both definition and some basic properties of the proposed model. Finally, we gave a general approach which is applied to a decision making problem in disease diagnoses, and demonstrated the effectiveness of the approach by a numerical example.

Keywords: single valued neutrosophic fuzzy set, single valued neutrosophic fuzzy hesitant set, rough set, single valued neutrosophic hesitant fuzzy rough set

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Authors: Kwan Hee Han

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External environment of enterprise is rapidly changing majorly by global competition, cost reduction pressures, and new technology. In these situations, production scheduling function plays a critical role to meet customer requirements and to attain the goal of operational efficiency. It deals with short-term decision making in the production process of the whole supply chain. The major task of production scheduling is to seek a balance between customer orders and limited resources. In manufacturing companies, this task is so difficult because it should efficiently utilize resource capacity under the careful consideration of many interacting constraints. At present, many computerized software solutions have been utilized in many enterprises to generate a realistic production schedule to overcome the complexity of schedule generation. However, most production scheduling systems do not provide sufficient information about the validity of the generated schedule except limited statistics. Process mining only recently emerged as a sub-discipline of both data mining and business process management. Process mining techniques enable the useful analysis of a wide variety of processes such as process discovery, conformance checking, and bottleneck analysis. In this study, the performance of generated production schedule is evaluated by mining event log data of production scheduling software system by using the process mining techniques since every software system generates event logs for the further use such as security investigation, auditing and error bugging. An application of process mining approach is proposed for the validation of the goodness of production schedule generated by scheduling software systems in this study. By using process mining techniques, major evaluation criteria such as utilization of workstation, existence of bottleneck workstations, critical process route patterns, and work load balance of each machine over time are measured, and finally, the goodness of production schedule is evaluated. By using the proposed process mining approach for evaluating the performance of generated production schedule, the quality of production schedule of manufacturing enterprises can be improved.

Keywords: data mining, event log, process mining, production scheduling

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Authors: Eleni Karasavvidou

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Social and anthropological research, parallel to Gender Studies, highlighted the relationship between social structures and symbolic forms as an important field of interaction and recording of 'social trends.' Since the study of representations can contribute to the understanding of the social functions and power relations, they encompass. This ‘mirage,’ however, has not only to do with the representations themselves but also with the ways they are received and the film or critical narratives that are established as dominant or alternative. Cinema and the criticism of its cultural products are no exception. Even in the rapidly changing media landscape of the 21st century, movies remain an integral and widespread part of popular culture, making films an extremely powerful means of 'legitimizing' or 'delegitimizing' visions of domination and commonsensical gender stereotypes throughout society. And yet it is film criticism, the 'language per se,' that legitimizes, reinforces, rewards and reproduces (or at least ignores) the stereotypical depictions of female roles that remain common in the realm of film images. This creates the need for this issue to have emerged (also) in academic research questioning gender criteria in film reviews as part of the effort for an inclusive art and society. Qualitative content analysis is used to examine female roles in selected Oscar-nominated films against their reviews from leading websites and newspapers. This method was chosen because of the complex nature of the depictions in the films and the narratives they evoke. The films were divided into basic scenes depicting social functions, such as love and work relationships, positions of power and their function, which were analyzed by content analysis, with borrowings from structuralism (Gennette) and the local/universal images of intercultural philology (Wierlacher). In addition to the measurement of the general ‘representation-time’ by gender, other qualitative characteristics were also analyzed, such as: speaking time, sayings or key actions, overall quality of the character's action in relation to the development of the scenario and social representations in general, as well as quantitatively (insufficient number of female lead roles, fewer key supporting roles, relatively few female directors and people in the production chain and how they might affect screen representations. The quantitative analysis in this study was used to complement the qualitative content analysis. Then the focus shifted to the criteria of film criticism and to the rhetorical narratives that exclude or highlight in relation to gender identities and functions. In the criteria and language of film criticism, stereotypes are often reproduced or allegedly overturned within the framework of apolitical "identity politics," which mainly addresses the surface of a self-referential cultural-consumer product without connecting it more deeply with the material and cultural life. One of the prime examples of this failure is the Bechtel Test, which tracks whether female characters speak in a film regardless of whether women's stories are represented or not in the films analyzed. If perceived unbiased male filmmakers still fail to tell truly feminist stories, the same is the case with the criteria of criticism and the related interventions.

Keywords: representations, context analysis, reviews, sexist stereotypes

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Authors: Chin-Chih Chiou, Tai-Yuan Su, Ti-Yu Chen, Wen-Yu Chiu, Chungyu Chen

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The purpose of this study was to investigate the effect of reaction time (RT) or balance performance as the number of stimulus-response choices increases, the amount of information processing of 0-bit and 1-bit conditions based on Hick’s law, using the dual-task design. Eighteen children (age: 9.38 ± 0.27 years old) were recruited as the participants for this study, and asked to assess RT and balance performance separately and simultaneously as following five conditions: simple RT (0-bit decision), choice RT (1-bit decision), single balance control, balance control with simple RT, and balance control with choice RT. Biodex 950-300 balance system and You-Shang response timer were used to record and analyze the postural stability and information processing speed (RT) respectively for the participants. Repeated measures one-way ANOVA with HSD post-hoc test and 2 (balance) × 2 (amount of information processing) repeated measures two-way ANOVA were used to test the parameters of balance performance and RT (α = .05). The results showed the overall stability index in the 1-bit decision was lower than in 0-bit decision, and the mean deflection in the 1-bit decision was lower than in single balance performance. Simple RTs were faster than choice RTs both in single task condition and dual task condition. It indicated that the chronometric approach of RT could use to infer the attention requirement of the secondary task. However, this study did not find that the balance performance is interfered for children by the increasing of the amount of information processing.

Keywords: capacity theory, reaction time, Hick’s law, balance

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Authors: Seyedmahdi Mousavihashemi

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One of the most important subjects of interest in researches is 'improving' which result in various algorithms. In so many geometrical problems we are faced with target functions which should be optimized. In group practices, all the functions’ cooperation lead to convergence. In the study, the optimization algorithm of dense particles is used. Usage of the algorithm improves the given performance norms. The results reveal that usage of swarm algorithm for reinforced particles in designing state feedback improves the given performance norm and in optimized designing of multi-target state feedback controlling, the network will maintain its bearing structure. The results also show that PSO is usable for optimization of state feedback controllers.

Keywords: multi-objective, enhanced, feedback, optimization, algorithm, particle, design

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Authors: Hossein Kh. Bisheh, Nan Wu

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Advanced composite materials have a great importance in engineering structures due to their high specific modulus and strength and low weight. These materials can be used in design and fabrication of automotive drive shafts to reduce the weight of the structure. Hence, an optimum design of a composite drive shaft satisfying the design criteria, can be an appropriate substitution of metallic drive shafts. The aim of this study is to design and analyze a composite automotive drive shaft with high specific strength and low weight satisfying the design criteria. Tsai-Wu criterion is chosen as the failure criterion. Various designs with different lay-ups and materials are investigated based on the design requirements and finally, an optimum design satisfying the design criteria is chosen based on the weight and cost considerations. The results of this study indicate that if the weight is the main concern, a shaft made of Carbon/Epoxy can be a good option, and if the cost is a more important parameter, a hybrid shaft made of aluminum and Carbon/Epoxy can be considered.

Keywords: Bending natural frequency, Composite drive shaft, Peak torque, Torsional buckling

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Authors: Anika Chebrolu

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Mono-targeted drugs can be of limited efficacy against complex diseases. Recently, multi-target drug design has been approached as a promising tool to fight against these challenging diseases. However, the scope of current computational approaches for multi-target drug design is limited. DeepLig presents a de-novo drug discovery platform that uses reinforcement learning to generate and optimize novel, potent, and multitargeted drug candidates against protein targets. DeepLig’s model consists of two networks in interplay: a generative network and a predictive network. The generative network, a Stack- Augmented Recurrent Neural Network, utilizes a stack memory unit to remember and recognize molecular patterns when generating novel ligands from scratch. The generative network passes each newly created ligand to the predictive network, which then uses multiple Graph Attention Networks simultaneously to forecast the average binding affinity of the generated ligand towards multiple target proteins. With each iteration, given feedback from the predictive network, the generative network learns to optimize itself to create molecules with a higher average binding affinity towards multiple proteins. DeepLig was evaluated based on its ability to generate multi-target ligands against two distinct proteins, multi-target ligands against three distinct proteins, and multi-target ligands against two distinct binding pockets on the same protein. With each test case, DeepLig was able to create a library of valid, synthetically accessible, and novel molecules with optimal and equipotent binding energies. We propose that DeepLig provides an effective approach to design multi-targeted drug therapies that can potentially show higher success rates during in-vitro trials.

Keywords: drug design, multitargeticity, de-novo, reinforcement learning

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Authors: Hanmei Peng, Yiqun Wang, Mao Tan, Zhuocen Dai, Yongxin Su

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Efficient energy management in multi-microgrid distribution systems holds significant importance for enhancing the economic benefits of regional power grids. To better balance conflicts among various stakeholders, a two-stage game-based collaborative optimization approach is proposed in this paper, effectively addressing the realistic scenario involving both competition and collaboration among stakeholders. The first stage, aimed at maximizing individual benefits, involves constructing a non-cooperative tariff game model for the distribution network and surplus microgrid. In the second stage, considering power flow and physical line capacity constraints we establish a cooperative P2P game model for the multi-microgrid distribution system, and the optimization involves employing the Lagrange method of multipliers to handle complex constraints. Simulation results demonstrate that the proposed approach can effectively improve the system economics while harmonizing individual and collective rationality.

Keywords: cooperative game, collaborative optimization, multi-microgrid distribution system, non-cooperative game

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Authors: Xiuqin Ma, Hongwu Qin

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A new efficient normal parameter reduction algorithm of soft set in decision making was proposed. However, up to the present, few documents have focused on real-life applications of this algorithm. Accordingly, we apply a New Efficient Normal Parameter Reduction algorithm into real-life datasets of online shopping, such as Blackberry Mobile Phone Dataset. Experimental results show that this algorithm is not only suitable but feasible for dealing with the online shopping.

Keywords: soft sets, parameter reduction, normal parameter reduction, online shopping

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Authors: Flordeliza L. Mercado, Teresito G. Aguinaldo, Helen F. Gavino, Victorino T. Taylan

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Most fruits and vegetables are available in large quantities during peak season which are oftentimes marketed at low price and left to rot or fed to farm animals. The lack of efficient storage facilities, and the additional cost and unavailability of small machinery for food processing, results to low price and wastage. Incidentally, processed fresh fruits and vegetables are gaining importance nowadays and health conscious people are also into ‘juicing’. One way to reduce wastage and ensure an all-season availability of crop juices at reasonable costs is to develop equipment for effective extraction of juice. The study was conducted to design, fabricate and evaluate a multi-juice extractor using locally available materials, making it relatively cheaper and affordable for medium-scale enterprises. The study was also conducted to formulate juice blends using extracted juices and calamansi juice at different blending percentage, and evaluate its chemical properties and sensory attributes. Furthermore, the chemical properties of extracted meals were evaluated for future applications. The multi-juice extractor has an overall dimension of 963mm x 300mm x 995mm, a gross weight of 82kg and 5 major components namely; feeding hopper, extracting chamber, juice and meal outlet, transmission assembly, and frame. The machine performance was evaluated based on juice recovery, extraction efficiency, extraction rate, extraction recovery, and extraction loss considering type of crop as apple and carrot with three replications each and was analyzed using T-test. The formulated juice blends were subjected to sensory evaluation and data gathered were analyzed using Analysis of Variance appropriate for Complete Randomized Design. Results showed that the machine’s juice recovery (73.39%), extraction rate (16.40li/hr), and extraction efficiency (88.11%) for apple were significantly higher than for carrot while extraction recovery (99.88%) was higher for apple than for carrot. Extraction loss (0.12%) was lower for apple than for carrot, but was not significantly affected by crop. Based on adding percentage mark-up on extraction cost (Php 2.75/kg), the breakeven weight and payback period for a 35% mark-up is 4,710.69kg and 1.22 years, respectively and for a 50% mark-up, the breakeven weight is 3,492.41kg and the payback period is 0.86 year (10.32 months). Results on the sensory evaluation of juice blends showed that the type of juice significantly influenced all the sensory parameters while the blending percentage including their respective interaction, had no significant effect on all sensory parameters, making the apple-calamansi juice blend more preferred than the carrot-calamansi juice blend in terms of all the sensory parameter. The machine’s performance is higher for apple than for carrot and the cost analysis on the use of the machine revealed that it is financially viable with a payback period of 1.22 years (35% mark-up) and 0.86 year (50% mark-up) for machine cost, generating an income of Php 23,961.60 and Php 34,444.80 per year using 35% and 50% mark-up, respectively. The juice blends were of good qualities based on the values obtained in the chemical analysis and the extracted meal could also be used to produce another product based on the values obtained from proximate analysis.

Keywords: food processing, fruits and vegetables, juice extraction, multi-juice extractor

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Authors: Muhamad Aris Burhanudin, Angga Firmansyas, Bagus Jaya Santosa

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Earthquakes are natural hazard that can trigger the most dangerous hazard, tsunami. 26 December 2004, a giant earthquake occurred in north-west Andalas Island. It made giant tsunami which crushed Sumatra, Bangladesh, India, Sri Lanka, Malaysia and Singapore. More than twenty thousand people dead. The occurrence of earthquake and tsunami can not be avoided. But this hazard can be mitigated by earthquake forecasting. Early preparation is the key factor to reduce its damages and consequences. We aim to investigate quantitatively on pattern of earthquake. Then, we can know the trend. We study about earthquake which has happened in Andalas island, Indonesia one last decade. Andalas is island which has high seismicity, more than a thousand event occur in a year. It is because Andalas island is in tectonic subduction zone of Hindia sea plate and Eurasia plate. A tsunami forecasting is needed to mitigation action. Thus, a Tsunami Forecasting Method is presented in this work. Neutral Network has used widely in many research to estimate earthquake and it is convinced that by using Backpropagation Method, earthquake can be predicted. At first, ANN is trained to predict Tsunami 26 December 2004 by using earthquake data before it. Then after we get trained ANN, we apply to predict the next earthquake. Not all earthquake will trigger Tsunami, there are some characteristics of earthquake that can cause Tsunami. Wrong decision can cause other problem in the society. Then, we need a method to reduce possibility of wrong decision. Fuzzy TOPSIS is a statistical method that is widely used to be decision seconder referring to given parameters. Fuzzy TOPSIS method can make the best decision whether it cause Tsunami or not. This work combines earthquake prediction using neural network method and using Fuzzy TOPSIS to determine the decision that the earthquake triggers Tsunami wave or not. Neural Network model is capable to capture non-linear relationship and Fuzzy TOPSIS is capable to determine the best decision better than other statistical method in tsunami prediction.

Keywords: earthquake, fuzzy TOPSIS, neural network, tsunami

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Authors: Anastasia Tsakiridi

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Geographic information systems (GIS) have been utilized in numerous spatial problems, such as site research, land suitability, and demographic analysis. Besides, GIS has been applied in scientific fields like geography, health, and economics. In business studies, GIS has been used to provide insights and spatial perspectives in demographic trends, spending indicators, and network analysis. To date, the information regarding the available usages of GIS in supply chain management (SCM) and how these analyses can benefit businesses is limited. A systematic literature review (SLR) of the last 5-year peer-reviewed academic literature was conducted, aiming to explore the existing usages of GIS in SCM. The searches were performed in 3 databases (Web of Science, ProQuest, and Business Source Premier) and reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. The analysis resulted in 79 papers. The results indicate that the existing GIS applications used in SCM were in the following domains: a) network/ transportation analysis (in 53 of the papers), b) location – allocation site search/ selection (multiple-criteria decision analysis) (in 45 papers), c) spatial analysis (demographic or physical) (in 34 papers), d) combination of GIS and supply chain/network optimization tools (in 32 papers), and e) visualization/ monitoring or building information modeling applications (in 8 papers). An additional categorization of the literature was conducted by examining the usage of GIS in the supply chain (SC) by the business sectors, as indicated by the volume of the papers. The results showed that GIS is mainly being applied in the SC of the biomass biofuel/wood industry (33 papers). Other industries that are currently utilizing GIS in their SC were the logistics industry (22 papers), the humanitarian/emergency/health care sector (10 papers), the food/agro-industry sector (5 papers), the petroleum/ coal/ shale gas sector (3 papers), the faecal sludge sector (2 papers), the recycle and product footprint industry (2 papers), and the construction sector (2 papers). The results were also presented by the geography of the included studies and the GIS software used to provide critical business insights and suggestions for future research. The results showed that research case studies of GIS in SCM were conducted in 26 countries (mainly in the USA) and that the most prominent GIS software provider was the Environmental Systems Research Institute’s ArcGIS (in 51 of the papers). This study is a systematic literature review of the usage of GIS in SCM. The results showed that the GIS capabilities could offer substantial benefits in SCM decision-making by providing key insights to cost minimization, supplier selection, facility location, SC network configuration, and asset management. However, as presented in the results, only eight industries/sectors are currently using GIS in their SCM activities. These findings may offer essential tools to SC managers who seek to optimize the SC activities and/or minimize logistic costs and to consultants and business owners that want to make strategic SC decisions. Furthermore, the findings may be of interest to researchers aiming to investigate unexplored research areas where GIS may improve SCM.

Keywords: supply chain management, logistics, systematic literature review, GIS

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Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Tae-Hyeon Oh, Dae-Kyu Park

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Sound absorbing material is used as automotive interior material. Sound absorption coefficient should be predicted to design it. But it is difficult to predict sound absorbing coefficient because it is comprised of several material layers. So, its targets are achieved through many experimental tunings. It causes a lot of cost and time. In this paper, we propose the process to estimate the sound absorption coefficient with multi-layer structure. In order to estimate the coefficient, physical properties of each material are used. These properties also use predicted values by Foam-X software using the sound absorption coefficient data measured by impedance tube. Since there are many physical properties and the measurement equipment is expensive, the values predicted by software are used. Through the measurement of the sound absorption coefficient of each material, its physical properties are calculated inversely. The properties of each material are used to calculate the sound absorption coefficient of the multi-layer material. Since the absorption coefficient of multi-layer can be calculated, optimization design is possible through simulation. Then, we will compare and analyze the calculated sound absorption coefficient with the data measured by scaled reverberation chamber and impedance tubes for a prototype. If this method is used when developing automotive interior materials with multi-layer structure, the development effort can be reduced because it can be optimized by simulation. So, cost and time can be saved.

Keywords: sound absorption material, sound impedance tube, sound absorption coefficient, optimization design

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Authors: Sedef Sert, Paola Garrone, Marco Melacini, Alessandro Perego

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This paper is aimed at enhancing our current understanding of motivations behind corporate in-kind donations and to find out whether economic efficiency may be a major driver. Our empirical setting is consisted of surplus food recovery and donation by companies from food supply chain. This choice of empirical setting is motivated by growing attention on the paradox of food insecurity and food waste i.e. a total of 842 million people worldwide were estimated to be suffering from regularly not getting enough food, while approximately 1.3 billion tons per year food is wasted globally. Recently, many authors have started considering surplus food donation to nonprofit organizations as a way to cope with social issue of food insecurity and environmental issue of food waste. In corporate philanthropy literature the motivations behind the corporate donations for social purposes, such as altruistic motivations, enhancements to employee morale, the organization’s image, supplier/customer relationships, local community support, have been examined. However, the relationship with economic efficiency is not studied and in many cases the pure economic efficiency as a decision making factor is neglected. Although in literature there are some studies give us the clue on economic value creation of surplus food donation such as saving landfill fees or getting tax deductions, so far there is no study focusing deeply on this phenomenon. In this paper, we develop a conceptual framework which explores the economic barriers and drivers towards alternative surplus food management options i.e. discounts, secondary markets, feeding animals, composting, energy recovery, disposal. The case study methodology is used to conduct the research. Protocols for semi structured interviews are prepared based on an extensive literature review and adapted after expert opinions. The interviews are conducted mostly with the supply chain and logistics managers of 20 companies in food sector operating in Italy, in particular in Lombardy region. The results shows that in current situation, the food manufacturing companies can experience cost saving by recovering and donating the surplus food with respect to other methods especially considering the disposal option. On the other hand, retail and food service sectors are not economically incentivized to recover and donate surplus food to disfavored population. The paper shows that not only strategic and moral motivations, but also economic motivations play an important role in managerial decision making process in surplus food management. We also believe that our research while rooted in the surplus food management topic delivers some interesting implications to more general research on corporate in-kind donations. It also shows that there is a huge room for policy making favoring the recovery and donation of surplus products.

Keywords: corporate philanthropy, donation, recovery, surplus food

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Authors: Shavindrie Cooray

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It is vital that students are supported in having balanced conversations about topics that might be controversial. This process is crucial to the development of critical thinking skills. This can be difficult to attain in e-learning environments, with some research finding students report a perceived loss in the quality of knowledge exchange and performance. This research investigated if Systems Theory could be applied to structure the discussion, improve information sharing, and reduce conflicts when students are working in online environments. This research involved 160 participants across four categories of student groups at a college in the Northeastern US. Each group was provided with a shared problem, and each group was expected to make a proposal for a solution. Two groups worked face-to-face; the first face to face group engaged with the problem and each other with no intervention from a facilitator; a second face to face group worked on the problem using Systems tools to facilitate problem structuring, group discussion, and decision-making. There were two types of virtual teams. The first virtual group also used Systems tools to facilitate problem structuring and group discussion. However, all interactions were conducted in a synchronous virtual environment. The second type of virtual team also met in real time but worked with no intervention. Findings from the study demonstrated that the teams (both virtual and face-to-face) using Systems tools shared more information with each other than the other teams; additionally, these teams reported an increased level of disagreement amongst their members, but also expressed more confidence and satisfaction with the experience and resulting decision compared to the other groups.

Keywords: e-learning, virtual teams, systems approach, conflicts

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Authors: Jong Woo Kim, Go Bong Choi, Sang Hwan Son, Dae Shik Kim, Jung Chul Suh, Jong Min Lee

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The Markov Decision Process (MDP) based methodology is implemented in order to establish the optimal schedule which minimizes the cost. Formulation of MDP problem is presented using the information about the current state of pipe, improvement cost, failure cost and pipe deterioration model. The objective function and detailed algorithm of dynamic programming (DP) are modified due to the difficulty of implementing the conventional DP approaches. The optimal schedule derived from suggested model is compared to several policies via Monte Carlo simulation. Validity of the solution and improvement in computational time are proved.

Keywords: Markov decision processes, dynamic programming, Monte Carlo simulation, periodic replacement, Weibull distribution

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Authors: C. M. Balaceanu, G. Suciu, C. S. Bosoc, O. Orza, C. Fernandez, Z. Viniczay

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The Internet of Things (IoT) represents the best option for smart vineyard applications, even if it is necessary to integrate the technologies required for the development. This article is based on the research and the results obtained in the DISAVIT project. For Smart Agriculture, the project aims to provide a trustworthy, intelligent, integrated vineyard management solution that is based on the IoT. To have interoperability through the use of a multiprotocol technology (being the future connected wireless IoT) it is necessary to adopt an agnostic approach, providing a reliable environment to address cyber security, IoT-based threats and traceability through blockchain-based design, but also creating a concept for long-term implementations (modular, scalable). The ones described above represent the main innovative technical aspects of this project. The DISAVIT project studies and promotes the incorporation of better management tools based on objective data-based decisions, which are necessary for agriculture adapted and more resistant to climate change. It also exploits the opportunities generated by the digital services market for smart agriculture management stakeholders. The project's final result aims to improve decision-making, performance, and viticulturally infrastructure and increase real-time data accuracy and interoperability. Innovative aspects such as end-to-end solutions, adaptability, scalability, security and traceability, place our product in a favorable situation over competitors. None of the solutions in the market meet every one of these requirements by a unique product being innovative.

Keywords: blockchain, IoT, smart agriculture, vineyard

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Authors: Juan Sepúlveda

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Energy is a fundamental component in sustainability, the access and use of this resource is related with economic growth, social improvements, and environmental impacts. In this sense, energy efficiency has been studied as a factor that enhances the positive impacts of energy in communities; however, the implementation of efficiency requires strong policy and strategies that usually rely on individual measures focused in independent dimensions. In this paper, the problem of energy efficiency as a multi-objective problem is studied, using scientometric analysis to discover trends and patterns that allow to identify the main variables and study approximations related with a further development of models to integrate energy efficiency and MCA into policy making for small communities.

Keywords: energy efficiency, MCA, scientometric, trends

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Authors: Nivedita Paul

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Marriages in India are part and parcel of kinship and cultural practices. Marriage practices differ in India because of cross-regional diversities in social relations which itself has evolved as a result of causal relationship between space and culture. As the place is important for the formation of culture and other social structures, therefore there is regional differentiation in cultural practices and marital customs. Based on the cultural practices some scholars have divided India into North and South kinship regions where women in the North get married early and have lesser autonomy compared to women in the South where marriages are mostly consanguineous. But, the emergence of new modes and alternative strategies such as matrimonial advertisements becoming popular, as well as the increase in women’s literacy and work force participation, matchmaking process in India has changed to some extent. The present study uses data from Indian Human Development Survey II (2011-12) which is a nationally representative multitopic survey that covers 41,554 households. Currently married women of age group 15-49 in their first marriage; whose year of marriage is from the 1970s to 2000s have been taken for the study. Based on spouse selection experiences, the sample of women has been divided into three marriage categories-self, semi and family arranged. Women in self-arranged or love marriage is the sole decision maker in choosing the partner, in semi-arranged marriage or arranged marriage with consent both parents and women together take the decision, whereas in family arranged or arranged marriage without consent only parents take the decision. The main aim of the study is to show the spatial and regional variations in spouse selection decision making. The basis for regionalization has been taken from Irawati Karve’s pioneering work on kinship studies in India called Kinship Organization in India. India is divided into four kinship regions-North, Central, South and East. Since this work was formulated in 1953, some of the states have experienced changes due to modernization; hence these have been regrouped. After mapping spouse selection patterns using GIS software, it is found that the northern region has mostly family arranged marriages (around 64.6%), the central zone shows a mixed pattern since family arranged marriages are less than north but more than south and semi-arranged marriages are more than north but less than south. The southern zone has the dominance of semi-arranged marriages (around 55%) whereas the eastern zone has more of semi-arranged marriage (around 53%) but there is also a high percentage of self-arranged marriage (around 42%). Thus, arranged marriage is the dominant form of marriage in all four regions, but with a difference in the degree of the involvement of the female and her parents and relatives.

Keywords: spouse selection, consent, kinship, regional pattern

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Authors: Sunandapriya Bhikkhu, Shimo Sraman

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The main objective of this research is to analytically study the concept of Lyotard’s different that rejects the monopoly criteria and single rule with the incommensurable, which can explain about conceptual problems of beauty in the philosophy of contemporary art. In Lyotard’s idea that basic value judgment of human should be a value like a phrase that is a small unit and an individual such as the aesthetic value that to explain the art world. From the concept of the anti-war artist that rejects the concept of the traditional aesthetic which cannot be able to explain the changing in contemporary society but emphasizes the meaning of individual beauty that is at the beginning of contemporary art today. In the analysis of the problem, the researcher supports the concept of Lyotard’s different that emphasizes the artistic expression which opens the space of perception and beyond the limitations of language process. Art is like phrase or small units that can convey a sense of humanity through the aesthetic value of the individual, not social criteria or universal. The concept of Lyotard’s different awakens and challenge us to the rejection of the single rule that is not open the social space to minorities by not accepting the monopoly criteria.

Keywords: difference, Jean-Francois Lyotard, postmodern, beauty, contemporary art

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Authors: Leila Tabrizi, Farnaz Dezhaboun

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In order to study the effect of plant nutrient source and different drying methods on physical and phytochemical characteristics of pot marigold (Calendula officinalis L., Asteraceae) flowers, a factorial experiment was conducted based on completely randomized design with three replications in Research Laboratory of University of Tehran in 2010. Different nutrient sources (vermicompost, municipal waste compost, cattle manure, mushroom compost and control) which were applied in a field experiment for flower production and different drying methods including microwave (300, 600 and 900 W), oven (60, 70 and 80oC) and natural-shade drying in room temperature, were tested. Criteria such as drying kinetic, antioxidant activity, total flavonoid content, total phenolic compounds and total carotenoid of flowers were evaluated. Results indicated that organic inputs as nutrient source for flowers had no significant effects on quality criteria of pot marigold except of total flavonoid content, while drying methods significantly affected phytochemical criteria. Application of microwave 300, 600 and 900 W resulted in the highest amount of total flavonoid content, total phenolic compounds and antioxidant activity, respectively, while oven drying caused the lowest amount of phytochemical criteria. Also, interaction effect of nutrient source and drying method significantly affected antioxidant activity in which the highest amount of antioxidant activity was obtained in combination of vermicompost and microwave 900 W. In addition, application of vermicompost combined with oven drying at 60oC caused the lowest amount of antioxidant activity. Based on results of drying trend, microwave drying showed a faster drying rate than those oven and natural-shade drying in which by increasing microwave power and oven temperature, time of flower drying decreased whereas slope of moisture content reduction curve showed accelerated trend.

Keywords: drying kinetic, medicinal plant, organic fertilizer, phytochemical criteria

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Authors: Sirapop Nuannimnoi, Hojjat Baghban, Ching-Yao Huang

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Over the past decade, with the fast development of blockchain technology since the birth of Bitcoin, there has been a massive increase in the usage of Cryptocurrencies. Cryptocurrencies are not seen as an investment opportunity due to the market’s erratic behavior and high price volatility. With the recent success of deep reinforcement learning (DRL), portfolio management can be modeled and automated. In this paper, we propose a novel DRL-based multi-agent system to automatically make proper trading decisions on multiple cryptocurrencies and gain profits in the highly volatile cryptocurrency market. We also extend this multi-agent system with horizontal federated transfer learning for better adapting to the inclusion of new cryptocurrencies in our portfolio; therefore, we can, through the concept of diversification, maximize our profits and minimize the trading risks. Experimental results through multiple simulation scenarios reveal that this proposed algorithmic trading system can offer three promising key advantages over other systems, including maximized profits, minimized risks, and adaptability.

Keywords: cryptocurrency portfolio management, algorithmic trading, federated learning, multi-agent reinforcement learning

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Authors: Suresh Hettiarachchi, Conrad Wasko, Ashish Sharma

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The ever changing and expanding urban landscape increases the stress on urban systems to support and maintain safe and functional living spaces. Flooding presents one of the more serious threats to this safety, putting a larger number of people in harm’s way in congested urban settings. Climate change is adding to this stress by creating a dichotomy in the urban flood response. On the one hand, climate change is causing storms to intensify, resulting in more destructive, rarer floods, while on the other hand, longer dry periods are decreasing the severity of more frequent, less intense floods. This variability is creating a need to be more agile and innovative in how we design for and manage urban flooding. Here, we argue that to cope with this challenge climate change brings, we need to move towards urban flood management through resilience rather than flood prevention. We also argue that dealing with the larger variation in flood response to climate change means that we need to look at flooding from all aspects rather than the single-dimensional focus of flood depths and extents. In essence, we need to rethink how we manage flooding in the urban space. This change in our thought process and approach to flood management requires a practical way to assess and quantify resilience that is built into the urban landscape so that informed decision-making can support the required changes in planning and infrastructure design. Towards that end, we propose a Simple Urban Flood Resilience Index (SUFRI) based on a robust definition of resilience as a tool to assess flood resilience. The application of a simple resilience index such as the SUFRI can provide a practical tool that considers urban flood management in a multi-dimensional way and can present solutions that were not previously considered. When such an index is grounded on a clear and relevant definition of resilience, it can be a reliable and defensible way to assess and assist the process of adapting to the increasing challenges in urban flood management with climate change.

Keywords: urban flood resilience, climate change, flood management, flood modelling

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how Bayesian inferential reasoning will contributes in obtaining a well-satisfied prediction for Distributed Constraint Optimization Problems (DCOPs) with uncertainties. We also demonstrate how DCOPs could be merged to multi-agent knowledge understand and prediction (i.e. Situation Awareness). The DCOPs functions were merged with Bayesian Belief Network (BBN) in the form of situation, awareness, and utility nodes. We describe how the uncertainties can be represented to the BBN and make an effective prediction using the expectation-maximization algorithm or conjugate gradient descent algorithm. The idea of variable prediction using Bayesian inference may reduce the number of variables in agents’ sampling domain and also allow missing variables estimations. Experiment results proved that the BBN perform compelling predictions with samples containing uncertainties than the perfect samples. That is, Bayesian inference can help in handling uncertainties and dynamism of DCOPs, which is the current issue in the DCOPs community. We show how Bayesian inference could be formalized with Distributed Situation Awareness (DSA) using uncertain and missing agents’ data. The whole framework was tested on multi-UAV mission for forest fire searching. Future work focuses on augmenting existing architecture to deal with dynamic DCOPs algorithms and multi-agent information merging.

Keywords: DCOP, multi-agent reasoning, Bayesian reasoning, swarm intelligence

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Authors: Loai Abdallah, Malik Yousef

Abstract:

A domain space for the data should reflect the actual similarity between objects. Since objects belonging to the same cluster usually share some common traits even though their geometric distance might be relatively large. In general, the Euclidean distance of data points that represented by large number of features is not capturing the actual relation between those points. In this study, we propose a new method to construct a different space that is based on clustering to form a new distance metric. The new distance space is based on ensemble clustering (EC). The EC distance space is defined by tracking the membership of the points over multiple runs of clustering algorithm metric. Over this distance, we train the decision trees classifier (DT-EC). The results obtained by applying DT-EC on 10 datasets confirm our hypotheses that embedding the EC space as a distance metric would improve the performance.

Keywords: ensemble clustering, decision trees, classification, K nearest neighbors

Procedia PDF Downloads 171

Authors: Ali Bhayani

Abstract:

College is a high involvement decision making where students are expected to evaluate several college offerings before selecting a college or a course to study. However, even in high involvement product like college, students get influenced by opinion leaders and suffer from social contagion. This narrative style study, involving 98 first year students, was able to demonstrate that social contagion differs with regards to gender, ethnicity and personality. Recommendations from students with academically strong background would impact on the college choice of the undergraduate students and limit information search. Study was able to identify the incidence of anchoring heuristics amongst the students. Managerial implications with regards to design of marketing campaign follows at the end of the study.

Keywords: social contagion, opinion leaders, higher education, consumer behavior

Procedia PDF Downloads 348

Authors: Kuplevatsky V., Kuplevatskay, Cherkashin M., Berezina N.

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After 6 months, a violation of the differentiation of the structure of the gland due to edema in 100%. 20% retained signs of a tumor according to DWI/ADC data. By 12 months, the reduction in the size of the gland is 100%. In all cases, no diffusion restriction was observed. The study after 18 months showed no significant changes in all (100%) patients. In the study, 24 months after treatment, the size of the gland was stable in all cases (+/- up to 5%). Diffuse decrease in T2VI signals from peripheral zones, without signs of diffusion restriction in 100%. After 30 months, signs of recovery of adenomatous changes in the transient zone were revealed in 85%. After 36 and 42 months, the restoration of organ differentiation was observed in 93% of patients. In 4 patients, by the 48th month, signs of biochemical relapse were clinically noted. According to the MRI data, signs of a local relapse were revealed. After 48 months, there were signs of restoration of organ differentiation, which allowed the use of PI-RADS criteria. The study after 54 months showed no changes compared to the control. 60 months after treatment, 97% of patients showed a restoration of differentiation of the gland structure, which allows evaluating the organ according to PI-RADS criteria Conclusions: The beginning of restoration of the structure of the prostate gland began 24 months after proton radiation therapy, the PI-RADS criteria can be fully applied after 48 months of treatment. Control studies every 6 months without clinical signs of relapse are not advisable. Local control of the prostate tumor after proton radiation therapy was achieved in 95% of patients during the entire follow-up period ( 60 months).

Keywords: proton therapy, prostate cancer, MRI imaging, PI-RADS

Procedia PDF Downloads 91

Authors: YU Kaijun, Liang Dong, Zhang Yarong, Jin Zhenzhou, Yang Zhaobao

Abstract:

For the impact monitoring of distributed structures, the traditional positioning methods are based on the time difference, which includes the four-point arc positioning method and the triangulation positioning method. But in the actual operation, these two methods have errors. In this paper, the Multi-Agent Blackboard Coordination Principle is used to combine the two methods. Fusion steps: (1) The four-point arc locating agent calculates the initial point and records it to the Blackboard Module.(2) The triangulation agent gets its initial parameters by accessing the initial point.(3) The triangulation agent constantly accesses the blackboard module to update its initial parameters, and it also logs its calculated point into the blackboard.(4) When the subsequent calculation point and the initial calculation point are within the allowable error, the whole coordination fusion process is finished. This paper presents a Multi-Agent collaboration method whose agent framework is JADE. The JADE platform consists of several agent containers, with the agent running in each container. Because of the perfect management and debugging tools of the JADE, it is very convenient to deal with complex data in a large structure. Finally, based on the data in Jade, the results show that the impact location method based on Multi-Agent coordination fusion can reduce the error of the two methods.

Keywords: impact monitoring, structural health monitoring(SHM), multi-agent system(MAS), black-board coordination, JADE

Procedia PDF Downloads 163

Authors: Elzbieta Sikorska-Simmons

Abstract:

Dementia is a progressive terminal disease. Despite this recognition, research shows that most family caregivers do not know it, and it is unclear how this knowledge affects the quality of patient care. The aim of this qualitative study of 20 family caregivers for patients with advanced dementia is to examine how the caregiver's knowledge about dementia affects the quality of patient care in the context of healthcare decision-making, advanced care planning, and access to adequate support systems. Knowledge about dementia implies family caregivers' understanding of dementia trajectories, common symptoms/complications, and alternative treatment options (e.g., comfort feeding versus tube feeding). Data were collected in semi-structured interviews with 20 family caregivers. The interviews were conducted in person by the author and designed to elicit rich descriptions of family caregivers' experiences with healthcare decision-making and the management of common symptoms/complications of end-stage dementia as patient healthcare proxies. The study findings suggest that caregivers who recognize that dementia is a terminal disease are less likely to opt for life-extending treatments during the advanced stages. They are also more likely to seek palliative/hospice care, and consequently, they are better able to avoid unnecessary hospitalizations or medical procedures. For example, those who know that dementia is a terminal disease tend to opt for "comfort feeding" rather than "tube feeding" in managing the swallowing difficulties that accompany advanced dementia. In the context of advance care planning, family caregivers who know that dementia is a terminal disease tend to have more meaningful advance directives (e.g., Power of Attorney and Do Not Resuscitate orders). They are better prepared to anticipate common problems and pursue treatments that foster the best quality of patient life and care. Greater knowledge about advanced dementia helps them make more informed decisions that focus on enhancing the quality of patient life rather than just survival. In addition, those who know that dementia is a terminal disease are more likely to establish adequate support systems to help them cope with the complex demands of caregiving. For example, they are more likely to seek dementia-oriented primary care programs that offer house visits or respite services. Based on the study findings, knowledge about dementia as a terminal disease is critical in the optimal management of patient care needs and the establishment of adequate support systems. More research is needed to better understand what caregivers need to know to better prepare them for the complex demands of dementia caregiving.

Keywords: dementia education, family caregiver, management of dementia, quality of care

Procedia PDF Downloads 81

Authors: Stephen Pembi, Samuel K. Msheliza, Helen A. Andow

Abstract:

Organizational culture is very important in the organization because it enhances organizational performance and serves as a sense of making and control mechanism that guides and shapes the attitude and behaviour of employees. However, organizational culture issues are frequently disregarded in lieu of activities that may or may not have a good impact on performance. This study examines the relationship between organizational culture and organizational performance of Adama Beverages Ltd, Adamawa State. The study employed an explanatory survey research design with a questionnaire as a source of data collection. One hundred and thirty-five copies of the questionnaire were administered using the convenience method of sampling, out of which one hundred and twenty were retrieved and well answered. The data collected were subjected to the Pearson product-moment correlation technique to test the hypotheses of the study using SPSS. The overall results signify that organizational culture has a significant positive relationship with organizational performance. The multiple regression results show that mission, adaptability, and involvement have a significant positive influence on organizational performance, while consistency has a significant negative influence on organizational performance. Therefore, this study concluded that organizational culture is a strong determinant of organizational performance in Adama Beverages Ltd, Adamawa State. The study recommends that the level of employee input into decision-making, flexibility in responding to changes in the business environment, consistency with values and traditions, and organizational performance should all be maintained by Adama Beverages Ltd.

Keywords: adaptability, consistency, involvement, mission, organizational performance

Procedia PDF Downloads 71