Search results for: Decision Support systems

Authors: Han-hua Lu, Shun-yi Zhang, Yong Zheng, Ya-shi Wang, Li-juan Min

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From the perspective of system of systems (SoS) and emergent behaviors, this paper describes large scale application software systems, and proposes framework methods to further depict systems- functional and non-functional characteristics. Besides, this paper also specifically discusses some functional frameworks. In the end, the framework-s applications in system disintegrations, system architecture and stable intermediate forms are additionally dealt with in this in building, deployment and maintenance of large scale software applications.

Keywords: application software system, framework methods, system of systems, emergent behaviors

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Authors: Jun Sung Park, Hyo Jung Song

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H.264/AVC offers a considerably higher improvement in coding efficiency compared to other compression standards such as MPEG-2, but computational complexity is increased significantly. In this paper, we propose selective mode decision schemes for fast intra prediction mode selection. The objective is to reduce the computational complexity of the H.264/AVC encoder without significant rate-distortion performance degradation. In our proposed schemes, the intra prediction complexity is reduced by limiting the luma and chroma prediction modes using the directional information of the 16×16 prediction mode. Experimental results are presented to show that the proposed schemes reduce the complexity by up to 78% maintaining the similar PSNR quality with about 1.46% bit rate increase in average.

Keywords: Video encoding, H.264, Intra prediction.

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Authors: John Tarus, Zhendong Niu, Bakhti Khadidja

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In recent years, e-learning recommender systems has attracted great attention as a solution towards addressing the problem of information overload in e-learning environments and providing relevant recommendations to online learners. E-learning recommenders continue to play an increasing educational role in aiding learners to find appropriate learning materials to support the achievement of their learning goals. Although general recommender systems have recorded significant success in solving the problem of information overload in e-commerce domains and providing accurate recommendations, e-learning recommender systems on the other hand still face some issues arising from differences in learner characteristics such as learning style, skill level and study level. Conventional recommendation techniques such as collaborative filtering and content-based deal with only two types of entities namely users and items with their ratings. These conventional recommender systems do not take into account the learner characteristics in their recommendation process. Therefore, conventional recommendation techniques cannot make accurate and personalized recommendations in e-learning environment. In this paper, we propose a recommendation technique combining collaborative filtering and ontology to recommend personalized learning materials to online learners. Ontology is used to incorporate the learner characteristics into the recommendation process alongside the ratings while collaborate filtering predicts ratings and generate recommendations. Furthermore, ontological knowledge is used by the recommender system at the initial stages in the absence of ratings to alleviate the cold-start problem. Evaluation results show that our proposed recommendation technique outperforms collaborative filtering on its own in terms of personalization and recommendation accuracy.

Keywords: Collaborative filtering, e-learning, ontology, recommender system.

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Authors: Pardeep Singh, Sanjay Sharma

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Content-Based Image Retrieval (CBIR) has been one on the most vivid research areas in the field of computer vision over the last 10 years. Many programs and tools have been developed to formulate and execute queries based on the visual or audio content and to help browsing large multimedia repositories. Still, no general breakthrough has been achieved with respect to large varied databases with documents of difering sorts and with varying characteristics. Answers to many questions with respect to speed, semantic descriptors or objective image interpretations are still unanswered. In the medical field, images, and especially digital images, are produced in ever increasing quantities and used for diagnostics and therapy. In several articles, content based access to medical images for supporting clinical decision making has been proposed that would ease the management of clinical data and scenarios for the integration of content-based access methods into Picture Archiving and Communication Systems (PACS) have been created. This paper gives an overview of soft computing techniques. New research directions are being defined that can prove to be useful. Still, there are very few systems that seem to be used in clinical practice. It needs to be stated as well that the goal is not, in general, to replace text based retrieval methods as they exist at the moment.

Keywords: CBIR, GA, Rough sets, CBMIR

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Authors: Sung Wook Yun, Yun Jong Choi, Kyong-min Lee, Poogyeon Park*

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Repetitive systems stand for a kind of systems that perform a simple task on a fixed pattern repetitively, which are widely spread in industrial fields. Hence, many researchers have been interested in those systems, especially in the field of iterative learning control (ILC). In this paper, we propose a finite-horizon tracking control scheme for linear time-varying repetitive systems with uncertain initial conditions. The scheme is derived both analytically and numerically for state-feedback systems and only numerically for output-feedback systems. Then, it is extended to stable systems with input constraints. All numerical schemes are developed in the forms of linear matrix inequalities (LMIs). A distinguished feature of the proposed scheme from the existing iterative learning control is that the scheme guarantees the tracking performance exactly even under uncertain initial conditions. The simulation results demonstrate the good performance of the proposed scheme.

Keywords: Finite time horizon, linear matrix inequality (LMI), repetitive system, uncertain initial condition.

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Authors: Yousra Zakaria Ahmed, Ahmed El Gendy, Salah El Haggar

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In this paper, our methodology to assess sustainability of wastewater treatment technologies in Egypt is presented. The preliminary list of factors to be considered, as well as their ranking listed. The factors include, but are not limited to pollutants removal efficiency and energy consumption under the environmental dimension, construction cost, operation and maintenance costs and required land area cost under the economic dimension and public acceptance, noise and generating job opportunities for local residents. This methodology is intended to be a user-friendly screening tool to support the decision making process when investigating different wastewater treatment technologies in Egypt. Based on the research work results presented in this paper, it can be generally concluded that the categorization of some of the social and environmental aspects of sustainability is subjective and highly dependent on the local conditions and researchers’ background.

Keywords: Sustainability, wastewater treatment, sustainability assessment, Egypt.

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Authors: Remica Aggarwal, Sanjeet Singh

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The decision to recruit manpower in an organization requires clear identification of the criteria (attributes) that distinguish successful from unsuccessful performance. The choice of appropriate attributes or criteria in different levels of hierarchy in an organization is a multi-criteria decision problem and therefore multi-criteria decision making (MCDM) techniques can be used for prioritization of such attributes. Analytic Hierarchy Process (AHP) is one such technique that is widely used for deciding among the complex criteria structure in different levels. In real applications, conventional AHP still cannot reflect the human thinking style as precise data concerning human attributes are quite hard to be extracted. Fuzzy logic offers a systematic base in dealing with situations, which are ambiguous or not well defined. This study aims at defining a methodology to improve the quality of prioritization of an employee-s performance measurement attributes under fuzziness. To do so, a methodology based on the Extent Fuzzy Analytic Hierarchy Process is proposed. Within the model, four main attributes such as Subject knowledge and achievements, Research aptitude, Personal qualities and strengths and Management skills with their subattributes are defined. The two approaches conventional AHP approach and the Extent Fuzzy Analytic Hierarchy Process approach have been compared on the same hierarchy structure and criteria set.

Keywords: AHP, Extent analysis method, Fuzzy AHP, Prioritization.

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Authors: Okay Gunes

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Unsatisfactory experiences due to an information shortage regarding the future pay-offs of actual choices, yield satisficing decision-making. This research will examine, for the first time in the literature, the motivation behind suboptimal decisions due to uncertainty by subjecting Adam Smith’s and Jeremy Bentham’s assumptions about the nature of the actions that lead to satisficing behavior, in order to clarify the theoretical background of a “consumption-based satisfactory time” concept. The contribution of this paper with respect to the existing literature is threefold: firstly, it is showed in this paper that Adam Smith’s uncertainty is related to the problem of the constancy of ideas and not related directly to beliefs. Secondly, possessions, as in Jeremy Bentham’s oeuvre, are assumed to be just as pleasing, as protecting and improving the actual or expected quality of life, so long as they reduce any displeasure due to the undesired outcomes of uncertainty. Finally, each consumption decision incurs its own satisfactory time period, owed to not feeling hungry, being healthy, not having transportation…etc. This reveals that the level of satisfaction is indeed a behavioral phenomenon where its value would depend on the simultaneous satisfaction derived from all activities.

Keywords: Decision-making, idea and belief, satisficing, uncertainty.

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Authors: Adam Czornik, Aleksander Nawrat

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This paper studies the problem of exponential stability of perturbed discrete linear systems with periodic coefficients. Assuming that the unperturbed system is exponentially stable we obtain conditions on the perturbations under which the perturbed system is exponentially stable.

Keywords: Exponential stability, time-varying linear systems, periodic systems.

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Authors: Metehan Makinacı

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The objective of this paper, is to apply support vector machine (SVM) approach for the classification of cancerous and normal regions of prostate images. Three kinds of textural features are extracted and used for the analysis: parameters of the Gauss- Markov random field (GMRF), correlation function and relative entropy. Prostate images are acquired by the system consisting of a microscope, video camera and a digitizing board. Cross-validated classification over a database of 46 images is implemented to evaluate the performance. In SVM classification, sensitivity and specificity of 96.2% and 97.0% are achieved for the 32x32 pixel block sized data, respectively, with an overall accuracy of 96.6%. Classification performance is compared with artificial neural network and k-nearest neighbor classifiers. Experimental results demonstrate that the SVM approach gives the best performance.

Keywords: Computer-aided diagnosis, support vector machines, Gauss-Markov random fields, texture classification.

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Authors: Soran Tarkhani

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The phenomenon of significant Arab support for Russia's invasion of Ukraine, despite widespread condemnation from Arab leaders, poses a puzzling scenario. This paper delves into the paradox by employing multiple regression analysis on the online reactions of Arab audiences to the conflict as reported by seven major news networks: CNN Arabic, BBC Arabic, Sky News Arabic, France24 Arabic, DW, Aljazeera, and Al-Arabiya. It hypothesizes that this support stems from prevalent anti-Western sentiment within the Arab world. The empirical findings corroborate the hypothesis, providing insight into the underlying motivations for Arab backing of Russia against Ukraine, despite their historical familiarity with the harsh realities of war.

Keywords: Anti-Western Sentiment, Arab World, Russia-Ukraine Conflict, social media analysis, political sentiment, international relations, regional influence.

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Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, G. Corkery, E. Broderick, J. Walsh

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Farm management and operations will drastically change due to access to real-time data, real-time forecasting and tracking of physical items in combination with Internet of Things (IoT) developments to further automate farm operations. Dairy farms have embraced technological innovations and procured vast amounts of permanent data streams during the past decade; however, the integration of this information to improve the whole farm decision-making process does not exist. It is now imperative to develop a system that can collect, integrate, manage, and analyze on-farm and off-farm data in real-time for practical and relevant environmental and economic actions. The developed systems, based on machine learning and artificial intelligence, need to be connected for useful output, a better understanding of the whole farming issue and environmental impact. Evolutionary Computing (EC) can be very effective in finding the optimal combination of sets of some objects and finally, in strategy determination. The system of the future should be able to manage the dairy farm as well as an experienced dairy farm manager with a team of the best agricultural advisors. All these changes should bring resilience and sustainability to dairy farming as well as improving and maintaining good animal welfare and the quality of dairy products. This review aims to provide an insight into the state-of-the-art of big data applications and EC in relation to smart dairy farming and identify the most important research and development challenges to be addressed in the future. Smart dairy farming influences every area of management and its uptake has become a continuing trend.

Keywords: Big data, evolutionary computing, cloud, precision technologies

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Authors: Siripen Yiamjanya, Kevin Wongleedee

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This research paper aims to identify travel motivation by push and pull factors that affected decision making of international tourists in selecting Thailand as their destination choice. A total of 200 international tourists who traveled to Thailand during January and February, 2014 were used as the sample in this study. A questionnaire was employed as a tool in collecting the data, conducted in Bangkok. The list consisted of 30 attributes representing both psychological factors as “push- based factors” and destination factors as “pull-based factors”. Mean and standard deviation were used in order to find the top ten travel motives that were important determinants in the respondents’ decision making process to select Thailand as their destination choice. The finding revealed the top ten travel motivations influencing international tourists to select Thailand as their destination choice included [i] getting experience in foreign land; [ii] Thai food; [iii] learning new culture; [iv] relaxing in foreign land; [v] wanting to learn new things; [vi] being interested in Thai culture, and traditional markets; [vii] escaping from same daily life; [viii] enjoying activities; [ix] adventure; and [x] good weather. Classification of push- based and pull- based motives suggested that getting experience in foreign land was the most important push motive for international tourists to travel, while Thai food portrayed its highest significance as pull motive. Discussion and suggestions were also made for tourism industry of Thailand.

Keywords: Decision Making, Destination Choice, International Tourist, Pull Factor, Push Factor, Thailand, Travel Motivation.

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Authors: Dong-Jae Kang, Nam-Woo Kim, Duk-Joo Son, Sung-In Jung

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According to dramatic growth of internet services, an easy and prompt service deployment has been important for internet service providers to successfully maintain time-to-market. Before global service deployment, they have to pay the big cost for service evaluation to make a decision of the proper system location, system scale, service delay and so on. But, intra-Lab evaluation tends to have big gaps in the measured data compared with the realistic situation, because it is very difficult to accurately expect the local service environment, network congestion, service delay, network bandwidth and other factors. Therefore, to resolve or ease the upper problems, we propose multiple cloud based GPES Broker system and use case that helps internet service providers to alleviate the above problems in beta release phase and to make a prompt decision for their service launching. By supporting more realistic and reliable evaluation information, the proposed GPES Broker system saves the service release cost and enables internet service provider to make a prompt decision about their service launching to various remote regions.

Keywords: GPES Broker system, Cloud Service Broker, Multiple Cloud, Global performance evaluation service (GPES), Service provisioning

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Authors: Laleh Yerushalmi, Fariborz Haghighat, Maziar Bani Shahabadi

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The estimation of overall on-site and off-site greenhouse gas (GHG) emissions by wastewater treatment plants revealed that in anaerobic and hybrid treatment systems greater emissions result from off-site processes compared to on-site processes. However, in aerobic treatment systems, onsite processes make a higher contribution to the overall GHG emissions. The total GHG emissions were estimated to be 1.6, 3.3 and 3.8 kg CO2-e/kg BOD in the aerobic, anaerobic and hybrid treatment systems, respectively. In the aerobic treatment system without the recovery and use of the generated biogas, the off-site GHG emissions were 0.65 kg CO2-e/kg BOD, accounting for 40.2% of the overall GHG emissions. This value changed to 2.3 and 2.6 kg CO2-e/kg BOD, and accounted for 69.9% and 68.1% of the overall GHG emissions in the anaerobic and hybrid treatment systems, respectively. The increased off-site GHG emissions in the anaerobic and hybrid treatment systems are mainly due to material usage and energy demand in these systems. The anaerobic digester can contribute up to 100%, 55% and 60% of the overall energy needs of plants in the aerobic, anaerobic and hybrid treatment systems, respectively.

Keywords: On-site and off-site greenhouse gas (GHG)emissions, wastewater treatment plants, biogas recovery

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Authors: Dong Sang Yoo

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The problem of finding control laws for underactuated systems has attracted growing attention since these systems are characterized by the fact that they have fewer actuators than the degrees of freedom to be controlled. The acrobot, which is a planar two-link robotic arm in the vertical plane with an actuator at the elbow but no actuator at the shoulder, is a representative in underactuated systems. In this paper, the dynamic model of the acrobot is implemented using Mathworks’ Simscape. And the sliding mode control is constructed using MATLAB and Simulink.

Keywords: Acrobot, MATLAB and Simulink, sliding mode control, underactuated systems.

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Authors: Mokrane Selma

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The shift towards decision making (DM) based on artificial intelligence (AI) techniques will change the way in which consumer markets and our societies function. Through AI, predictive analytics is being used by businesses to identify these patterns and major trends with the objective to improve the DM and influence future business outcomes. This paper proposes an Artificial Neural Network (ANN) approach to predict the success of telemarketing calls for selling bank long-term deposits. To validate the proposed model, we uses the bank marketing data of 41188 phone calls. The ANN attains 98.93% of accuracy which outperforms other conventional classifiers and confirms that it is credible and valuable approach for telemarketing campaign managers.

Keywords: Bank telemarketing, prediction, decision making, artificial intelligence, artificial neural network.

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Authors: Karin Kandananond

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The nature of consumer products causes the difficulty in forecasting the future demands and the accuracy of the forecasts significantly affects the overall performance of the supply chain system. In this study, two data mining methods, artificial neural network (ANN) and support vector machine (SVM), were utilized to predict the demand of consumer products. The training data used was the actual demand of six different products from a consumer product company in Thailand. The results indicated that SVM had a better forecast quality (in term of MAPE) than ANN in every category of products. Moreover, another important finding was the margin difference of MAPE from these two methods was significantly high when the data was highly correlated.

Keywords: Artificial neural network (ANN), Bullwhip effect, Consumer products, Demand forecasting, Supply chain, Support vector machine (SVM).

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Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

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The automatic extraction of shipping routes is advantageous for intelligent traffic management systems to identify events and support decision-making in maritime surveillance. At present, there is a high demand for the extraction of maritime traffic networks that resemble the real traffic of vessels accurately, which is valuable for further analytical processing tasks for vessels trajectories (e.g., naval routing and voyage planning, anomaly detection, destination prediction, time of arrival estimation). With the help of big data and processing huge amounts of vessels’ trajectory data, it is possible to learn these shipping routes from the navigation history of past behaviour of other, similar ships that were travelling in a given area. In this paper, we propose a spatial clustering model of vessels’ trajectories (SPTCLUST) to extract spatial representations of sailing routes from historical Automatic Identification System (AIS) data. The whole model consists of three main parts: data preprocessing, path finding, and route extraction, which consists of clustering and representative trajectory extraction. The proposed clustering method provides techniques to overcome the problems of: (i) optimal input parameters selection; (ii) the high complexity of processing a huge volume of multidimensional data; (iii) and the spatial representation of complete representative trajectory detection in the context of trajectory clustering algorithms. The experimental evaluation showed the effectiveness of the proposed model by using a real-world AIS dataset from the Port of Halifax. The results contribute to further understanding of shipping route patterns. This could aid surveillance authorities in stable and sustainable vessel traffic management.

Keywords: Vessel trajectory clustering, trajectory mining, Spatial Clustering, marine intelligent navigation, maritime traffic network extraction, sdailing routes extraction.

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Authors: Hong Li, Shou-Ming Zhong, Hou-Biao Li

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In this paper, we mainly study the stability of linear and interval linear fractional systems with time delay. By applying the characteristic equations, a necessary and sufficient stability condition is obtained firstly, and then some sufficient conditions are deserved. In addition, according to the equivalent relationship of fractional order systems with order 0 < α ≤ 1 and with order 1 ≤ β < 2, one may get more relevant theorems. Finally, two examples are provided to demonstrate the effectiveness of our results.

Keywords: Fractional order systems, Time delay, Characteristic equation.

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Authors: Toshihiko Takemura, Makoto Osajima, Masatoshi Kawano

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This paper includes a positive analysis to quantitatively grasp the relationship among vulnerability, information security incidents, and the countermeasures by using data based on a 2007 questionnaire survey for Japanese ISPs (Internet Service Providers). To grasp the relationships, logistic regression analysis is used. The results clarify that there are relationships between information security incidents and the countermeasures. Concretely, there is a positive relationship between information security incidents and the number of information security systems introduced as well as a negative relationship between information security incidents and information security education. It is also pointed out that (especially, local) ISPs do not execute efficient information security countermeasures/ investment concerned with systems, and it is suggested that they should positively execute information security education. In addition, to further heighten the information security level of Japanese telecommunication infrastructure, the necessity and importance of the government to implement policy to support the countermeasures of ISPs is insisted.

Keywords: Information security countermeasures, information security incidents, internet service providers, positive analysis

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Authors: Hanna Ziętara

Abstract:

Gastronomy is one of the oldest forms of commercial activity. It is currently one of the most popular and still dynamically developing branches of business. Socio-economic changes, its widespread occurrence, new techniques or culinary styles affect the almost unlimited possibilities of its development. Importantly, regardless of the form of business adopted, foodservice is strongly related to logistics processes, and areas of foodservice that are closely linked to logistics are of strategic importance. Any inefficiency in logistics processes results in reduced chances for success and achieving competitive advantage by companies belonging to the catering industry. The aim of the paper is to identify the areas of logistic support, occurring in the catering business, and affecting the scope of the logistic processes implemented. The aim of the paper is implemented through a plural homogeneous approach, based on direct observation, text analysis of current documents, and in-depth free targeted interviews.

Keywords: Gastronomy, competitive advantage, logistics, logistics support.

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Authors: Noor S. Nasri, Eric C. A. Tatt, Usman D. Hamza, Jibril Mohammed, Husna M. Zain

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Catalytic combustion of methane is imperative due to stability of methane at low temperature. Methane (CH4), therefore, remains unconverted in vehicle exhausts thereby causing greenhouse gas GHG emission problem. In this study, heterogeneous catalysts of palladium with bio-char (2 wt% Pd/Bc) and Al2O3 (2wt% Pd/ Al2O3) supports were prepared by incipient wetness impregnation and then subsequently tested for catalytic combustion of CH4. Support-porous heterogeneous catalytic combustion (HCC) material were selected based on factors such as surface area, porosity, thermal stability, thermal conductivity, reactivity with reactants or products, chemical stability, catalytic activity, and catalyst life. Sustainable and renewable support-material of bio-mass char derived from palm shell waste material was compared with those from the conventional support-porous materials. Kinetic rate of reaction was determined for combustion of methane on Palladium (Pd) based catalyst with Al2O3 support and bio-char (Bc). Material characterization was done using TGA, SEM, and BET surface area. The performance test was accomplished using tubular quartz reactor with gas mixture ratio of 3% methane and 97% air. The methane porous-HCC conversion was carried out using online gas analyzer connected to the reactor that performed porous-HCC. BET surface area for prepared 2 wt% Pd/Bc is smaller than prepared 2wt% Pd/ Al2O3 due to its low porosity between particles. The order of catalyst activity based on kinetic rate on reaction of catalysts in low temperature was 2wt% Pd/Bc>calcined 2wt% Pd/ Al2O3> 2wt% Pd/ Al2O3>calcined 2wt% Pd/Bc. Hence agro waste material can successfully be utilized as an inexpensive catalyst support material for enhanced CH4 catalytic combustion.

Keywords: Catalytic-combustion, Environmental, Support-bio-char material, Sustainable, Renewable material.

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Authors: Felix Brito

Abstract:

With the growth of online learning, several higher education institutions have attempted to incorporate technology in their curriculum. Successful technology implementation projects really on technology infrastructure and on the acceptance of education professionals towards innovation. This research study is aimed at illustrating the relevance of the human component in technology implementation projects in higher education by describing the Learning Management System implementation project executed by instructional designers working for a higher education institution in the southeast region of the United States. An analysis of the Transformative Leadership Theory, the Technology Acceptance Model, and the Diffusion of Innovation Process provide the support for a solid understanding of this issue and address recommendations for future technology implementation projects in higher education institutions.

Keywords: Learning management systems, transformative leadership theory, technology acceptance model, diffusion of innovation process, leadership, instructional design, online learning.

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Authors: Mohammad Reza Ayatollahzadeh Shirazi, Pooya Jaferian, Golnaz Elahi, Hamid Baghi, Babak Sadeghian

Abstract:

The world is moving rapidly toward the deployment of information and communication systems. Nowadays, computing systems with their fast growth are found everywhere and one of the main challenges for these systems is increasing attacks and security threats against them. Thus, capturing, analyzing and verifying security requirements becomes a very important activity in development process of computing systems, specially in developing systems such as banking, military and e-business systems. For developing every system, a process model which includes a process, methods and tools is chosen. The Rational Unified Process (RUP) is one of the most popular and complete process models which is used by developers in recent years. This process model should be extended to be used in developing secure software systems. In this paper, the Requirement Discipline of RUP is extended to improve RUP for developing secure software systems. These proposed extensions are adding and integrating a number of Activities, Roles, and Artifacts to RUP in order to capture, document and model threats and security requirements of system. These extensions introduce a group of clear and stepwise activities to developers. By following these activities, developers assure that security requirements are captured and modeled. These models are used in design, implementation and test activitie

Keywords:

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Authors: Boukelkoul Lahcen

Abstract:

The cumulative costs for O&M may represent as much as 65%-90% of the turbine's investment cost. Nowadays the cost effectiveness concept becomes a decision-making and technology evaluation metric. The cost of energy metric accounts for the effect replacement cost and unscheduled maintenance cost parameters. One key of the proposed approach is the idea of maintaining the WTs which can be captured via use of a finite state Markov chain. Such a model can be embedded within a probabilistic operation and maintenance simulation reflecting the action to be done. In this paper, an approach of estimating the cost of O&M is presented. The finite state Markov model is used for decision problems with number of determined periods (life cycle) to predict the cost according to various options of maintenance.

Keywords: Cost, finite state, Markov model, operation, maintenance.

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Authors: Kwame B. O. Amoah

Abstract:

This paper focuses on retrofitting an old existing office building to a net-zero energy building (NZEB). An existing small office building in Melbourne, Florida, was chosen as a case study to integrate state-of-the-art design strategies and energy-efficient building systems to improve building performance and reduce energy consumption. The study aimed to explore possible ways to maximize energy savings and renewable energy generation sources to cover the building's remaining energy needs necessary to achieve net-zero energy goals. A series of retrofit options were reviewed and adopted with some significant additional decision considerations. Detailed processes and considerations leading to zero energy are well documented in this study, with lessons learned adequately outlined. Based on building energy simulations, multiple design considerations were investigated, such as emerging state-of-the-art technologies, material selection, improvements to the building envelope, optimization of the HVAC, lighting systems, and occupancy loads analysis, as well as the application of renewable energy sources. The comparative analysis of simulation results was used to determine how specific techniques led to energy saving and cost reductions. The research results indicate that this small office building can meet net-zero energy use after appropriate design manipulations and renewable energy sources.

Keywords: Energy consumption, building energy analysis, energy retrofits, energy-efficiency.

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Authors: Aurelija Burinskienė, Dalė Dzemydienė, Arūnas Miliauskas

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This research aims at developing the approach for more effective freight delivery and transportation process management. The road congestions and the identification of causes are important, as well as the context information recognition and management. The measure of many parameters during the transportation period and proper control of driver work became the problem. The number of vehicles per time unit passing at a given time and point for drivers can be evaluated in some situations. The collection of data is mainly used to establish new trips. The flow of the data is more complex in urban areas. Herein, the movement of freight is reported in detail, including the information on street level. When traffic density is extremely high in congestion cases, and the traffic speed is incredibly low, data transmission reaches the peak. Different data sets are generated, which depend on the type of freight delivery network. There are three types of networks: long-distance delivery networks, last-mile delivery networks and mode-based delivery networks; the last one includes different modes, in particular, railways and other networks. When freight delivery is switched from one type of the above-stated network to another, more data could be included for reporting purposes and vice versa. In this case, a significant amount of these data is used for control operations, and the problem requires an integrated methodological approach. The paper presents an approach for providing e-services for drivers by including the assessment of the multi-component infrastructure needed for delivery of freights following the network type. The construction of such a methodology is required to evaluate data flow conditions and overloads, and to minimize the time gaps in data reporting. The results obtained show the possibilities of the proposing methodological approach to support the management and decision-making processes with functionality of incorporating networking specifics, by helping to minimize the overloads in data reporting.

Keywords: Transportation networks, freight delivery, data flow, monitoring, e-services.

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Authors: Xiuyong Ding, Lan Shu, Xiu Liu

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This paper is concerned with the existence of a linear copositive Lyapunov function(LCLF) for a special class of switched positive linear systems(SPLSs) composed of continuousand discrete-time subsystems. Firstly, by using system matrices, we construct a special kind of matrices in appropriate manner. Secondly, our results reveal that the Hurwitz stability of these matrices is equivalent to the existence of a common LCLF for arbitrary finite sets composed of continuous- and discrete-time positive linear timeinvariant( LTI) systems. Finally, a simple example is provided to illustrate the implication of our results.

Keywords: Linear co-positive Lyapunov functions, positive systems, switched systems.

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Authors: Aussadavut Dumrongsiri

Abstract:

Web-based technologies have created numerous opportunities for electronic word-of-mouth (eWOM) communication. There are many factors that affect customer adoption and decisionmaking process. However, only a few researches focus on some factors such as the membership time of forum and propensity to trust. Using a discrete-time event simulation to simulate a diffusion model along with a consumer decision model, the study shows the effect of each factor on adoption of opinions on on-line discussion forum. The purpose of this study is to examine the effect of factor affecting information adoption and decision making process. The model is constructed to test quantitative aspects of each factor. The simulation study shows the membership time and the propensity to trust has an effect on information adoption and purchasing decision. The result of simulation shows that the longer the membership time in the communities and the higher propensity to trust could lead to the higher demand rates because consumers find it easier and faster to trust the person in the community and then adopt the eWOM. Other implications for both researchers and practitioners are provided.

Keywords: word of mouth, simulation, consumer behavior, ebusiness, marketing, diffusion process.

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