Search results for: computerized decision support systems

Authors: Tiago Sampaio, André Vasconcelos, Bruno Fragoso

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The Normalized Systems Theory, which is designed to be applied to software architectures, provides a set of theorems, elements and rules, with the purpose of enabling evolution in Information Systems, as well as ensuring that they are ready for change. In order to make that possible, this work’s solution is to apply the Normalized Systems Theory to the domain of enterprise architectures, using Archimate. This application is achieved through the adaptation of the elements of this theory, making them artifacts of the modeling language. The theorems are applied through the identification of the viewpoints to be used in the architectures, as well as the transformation of the theory’s encapsulation rules into architectural rules. This way, it is possible to create normalized enterprise architectures, thus fulfilling the needs and requirements of the business. This solution was demonstrated using the Portuguese Public Procurement System. The Portuguese government aims to make this system as fair as possible, allowing every organization to have the same business opportunities. The aim is for every economic operator to have access to all public tenders, which are published in any of the 6 existing platforms, independently of where they are registered. In order to make this possible, we applied our solution to the construction of two different architectures, which are able of fulfilling the requirements of the Portuguese government. One of those architectures, TO-BE A, has a Message Broker that performs the communication between the platforms. The other, TO-BE B, represents the scenario in which the platforms communicate with each other directly. Apart from these 2 architectures, we also represent the AS-IS architecture that demonstrates the current behavior of the Public Procurement Systems. Our evaluation is based on a comparison between the AS-IS and the TO-BE architectures, regarding the fulfillment of the rules and theorems of the Normalized Systems Theory and some quality metrics.

Keywords: archimate, architecture, broker, enterprise, evolvable systems, interoperability, normalized architectures, normalized systems, normalized systems theory, platforms

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Authors: Dhouha Laribi Galalou, Najla Allani Bouhoula, Atef Hammouda

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This research delves into the fundamental question of the morphological restitution of built archaeology in order to place it in its paradigmatic context and to seek answers to it. Indeed, the understanding of the object of the study, its analysis, and the methodology of solving the morphological problem posed, are manageable aspects only by means of a thoughtful strategy that draws on well-defined epistemological scaffolding. In this stream, the crisis of natural reasoning in archaeology has generated multiple changes in this field, ranging from the use of new tools to the integration of an archaeological information system where urbanization involves the interplay of several disciplines. The built archaeological topic is also an architectural and morphological object. It is also a set of articulated elementary data, the understanding of which is about to be approached from a logicist point of view. Morphological restitution is no exception to the rule, and the inter-exchange between the different disciplines uses the capacity of each to frame the reflection on the incomplete elements of a given architecture or on its different phases and multiple states of existence. The logicist sequence is furnished by the set of scattered or destroyed elements found, but also by what can be called a rule base which contains the set of rules for the architectural construction of the object. The knowledge base built from the archaeological literature also provides a reference that enters into the game of searching for forms and articulations. The choice of the Roman Forum in North Africa is justified by the great urban and architectural characteristics of this entity. The research on the forum involves both a fairly large knowledge base but also provides the researcher with material to study - from a morphological and architectural point of view - starting from the scale of the city down to the architectural detail. The experimentation of the knowledge deduced on the paradigmatic level, as well as the deduction of an analysis model, is then carried out on the basis of a well-defined context which contextualises the experimentation from the elaboration of the morphological information container attached to the rule base and the knowledge base. The use of logicist analysis and artificial intelligence has allowed us to first question the aspects already known in order to measure the credibility of our system, which remains above all a decision support tool for the morphological restitution of Roman Fora in North Africa. This paper presents a first experimentation of the model elaborated during this research, a model framed by a paradigmatic discussion and thus trying to position the research in relation to the existing paradigmatic and experimental knowledge on the issue.

Keywords: classical reasoning, logicist reasoning, archaeology, architecture, roman forum, morphology, calculation

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Authors: Mahmoud Almasri, Xavier Marjou, Fanny Parzysz

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The demand for services provided by Unmanned Aerial Vehicles (UAVs) is increasing pervasively across several sectors including potential public safety, economic, and delivery services. As the number of applications using UAVs grows rapidly, more and more powerful, quality of service, and power efficient computing units are necessary. Recently, cellular technology draws more attention to connectivity that can ensure reliable and flexible communications services for UAVs. In cellular technology, flying with a high speed and altitude is subject to several key challenges, such as frequent handovers (HOs), high interference levels, connectivity coverage holes, etc. Additional HOs may lead to “ping-pong” between the UAVs and the serving cells resulting in a decrease of the quality of service and energy consumption. In order to optimize the number of HOs, we develop in this paper a Q-learning-based algorithm. While existing works focus on adjusting the number of HOs in a static network topology, we take into account the impact of cells deployment for three different simulation scenarios (Rural, Semi-rural and Urban areas). We also consider the impact of the decision distance, where the drone has the choice to make a switching decision on the number of HOs. Our results show that a Q-learning-based algorithm allows to significantly reduce the average number of HOs compared to a baseline case where the drone always selects the cell with the highest received signal. Moreover, we also propose which hyper-parameters have the largest impact on the number of HOs in the three tested environments, i.e. Rural, Semi-rural, or Urban.

Keywords: drones connectivity, reinforcement learning, handovers optimization, decision distance

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Authors: M. R. Babaei, S. M. Hosseini, S. Rahmani, L. Moradi

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Today, the quality of education and training systems and the effectiveness of the education systems of most concern to stakeholders and decision-makers of our country's development in each country. In Iran this is a double issue of concern to numerous reasons; So that governments, over the past decade have hardly even paid the running costs of education. ICT is claiming it has the power to change the structure of a program for training, reduce costs and increase quality, and do education systems and products consistent with the needs of the community and take steps to practice education. Own of the areas that the introduction of information technology has fundamentally changed is the field of education. The aim of this research is process reengineering management in schools simultaneously has been using field studies to collect data in the form of interviews and a questionnaire survey. The statistical community of this research has been the country of Iran and smart schools under the education. Sampling was targeted. The data collection tool was a questionnaire composed of two parts. The questionnaire consists of 36 questions that each question designates one of effective factors on the management of smart schools. Also each question consists of two parts. The first part designates the operating position in the management process, which represents the domain's belonging to the management agent (planning, organizing, leading, controlling). According to the classification of Dabryn and in second part the factors affect the process of managing the smart schools were examined, that Likert scale is used to classify. Questions the validity of the group of experts and prominent university professors in the fields of information technology, management and reengineering of approved and Cronbach's alpha reliability and also with the use of the formula is evaluated and approved. To analyse the data, descriptive and inferential statistics were used to analyse the factors contributing to the rating of (Linkert scale) descriptive statistics (frequency table data, mean, median, mode) was used. To analyse the data using analysis of variance and nonparametric tests and Friedman test, the assumption was evaluated. The research conclusions show that the factors influencing the management process re-engineering smart schools in school performance is affected.

Keywords: re-engineering, management process, smart school, Iran's school

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Authors: Sudha Subramani, Hua Wang

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Domestic Violence (DV) against women is now recognized to be a serious and widespread problem worldwide. There is a growing concern that violence against women has a global public health impact, as well as a violation of human rights. From the existing statistical surveys, it is revealed that there exists a strong relationship between DV and health issues of women like bruising, lacerations, depression, anxiety, flashbacks, sleep disturbances, hyper-arousal, emotional distress, sexually transmitted diseases and so on. This social problem is still considered as behind the closed doors issue and stigmatized topic. Women conceal their sufferings from family and friends, as they experience a lack of trust in others, feelings of shame and embarrassment among the society. Hence, women survivors of DV experience some barriers in seeking the support of specialized services such as health care access, crisis support, and legal guidance. Fortunately, with the popularity of social media like Facebook and Twitter, people share their opinions and emotional feelings to seek the social and emotional support, for sympathetic encouragement, to show compassion and empathy among the public. Considering the DV, social media plays a predominant role in creating the awareness and promoting the support services to the public, as we live in the golden era of social media. The various professional people like the public health researchers, clinicians, psychologists, social workers, national family health organizations, lawyers, and victims or their family and friends share the unprecedentedly valuable information (personal opinions and experiences) in a single platform to improve the social welfare of the community. Though each tweet or post contains a less informational value, the consolidation of millions of messages can generate actionable knowledge and provide valuable insights about the public opinion in general. Hence, this paper reports on an exploratory analysis of the effectiveness of social media for unobtrusive assessment of attitudes and awareness towards DV. In this paper, mixed methods such as qualitative analysis and text mining approaches are used to understand the social media disclosures of DV through the lenses of opinion sharing, anonymity, and support seeking. The results of this study could be helpful to avoid the cost of wide scale surveys, while still maintaining appropriate research conditions is to leverage the abundance of data publicly available on the web. Also, this analysis with data enrichment and consolidation would be useful in assisting advocacy and national family health organizations to provide information about resources and support, raise awareness and counter common stigmatizing attitudes about DV.

Keywords: domestic violence, social media, social stigma and support, women health

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Authors: Haeng A. Seo, Changseok Oh, Seung Jun Yoo

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This study attempts to examine the disparities in S&T innovation capacity from 14 developing countries to discuss how to support specific features in national innovation systems. It includes East-Asian, Middle-Asian, Central American and African countries. Here, we particularly focus on five dimensions- resources, activities, network, environment and performance- with 37 indicators. They were derived as structuring components of the relevant diagnostic model, which encompasses the whole process of S&T innovation from the input of resources to the output of economically valuable results. For many developing nations, economic industries remain weaker than actual S&T capabilities, and relevant regulatory authorities may not exist. This paper will be helpful to provide basic evidence and to set directions for better national S&T Innovation capacities and toward national competitiveness.

Keywords: developing countries, measurement, NIS, S&T innovation capacity

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Authors: T. Tulwin, M. Gęca, R. Sochaczewski

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Recent improvements in electric propulsion systems and energy storage systems allow for the electrification of many sectors where it was previously not feasible. This analysis proves the feasibility of electric propulsion in aviation applications reviewing recent energy storage developments. It can be more quiet, energy efficient and more environmentally friendly. Numerical simulations were done to prove that energy efficiency can be improved for rotorcrafts especially in hover conditions. New types of aircraft configurations are reviewed and future trends are presented.

Keywords: aircraft, propulsion , efficiency, storage

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Authors: Rafat Rob, Khaled Alotaibi, Dana Nour, Abdullah Albadrani, Abdulmohsen Mulhim

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Power systems digitization solutions provides a comprehensive smart, cohesive, interconnected network, extensive connectivity between digital assets, physical power plants, and resources to form digital economies. However, digitization has exposed the classical air gapped power plants to the rapid spread of cyber threats and attacks in the process delaying and forcing many organizations to rethink their cyber security policies and standards before they can augment their operation the new advanced digital devices. Cyber Security requirements for power systems (and industry control systems therein) demand a new approach, unique methodology, and design process that is completely different to Cyber Security measures designed for the IT systems. In practice, Cyber Security strategy, as applied to power systems, tends to be closely aligned to those measures applied for IT system purposes. The differentiator for Cyber Security in terms of power systems are the physical assets and applications used, alongside the ever-growing rate of expansion within the industry controls sector (in comparison to the relatively saturated growth observed for corporate IT systems). These factors increase the magnitude of the cyber security risk within such systems. The introduction of smart devices and sensors along the grid initiate vulnerable entry points to the systems. Every installed Smart Meter is a target; the way these devices communicate with each other may instigate a Denial of Service (DoS) and Distributed Denial of Service (DDoS) attack. Attacking one sensor or meter has the potential to propagate itself throughout the power grid reaching the IT network, where it may manifest itself as a malware infiltration.

Keywords: supply chain, cybersecurity, maturity model, risk, smart grid

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Authors: Baljit Singh Khehra, Amar Partap Singh Pharwaha

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Clusters of Microcalcifications (MCCs) are most frequent symptoms of Ductal Carcinoma in Situ (DCIS) recognized by mammography. Least-Square Support Vector Machine (LS-SVM) is a variant of the standard SVM. In the paper, LS-SVM is proposed as a classifier for classifying MCCs as benign or malignant based on relevant extracted features from enhanced mammogram. To establish the credibility of LS-SVM classifier for classifying MCCs, a comparative evaluation of the relative performance of LS-SVM classifier for different kernel functions is made. For comparative evaluation, confusion matrix and ROC analysis are used. Experiments are performed on data extracted from mammogram images of DDSM database. A total of 380 suspicious areas are collected, which contain 235 malignant and 145 benign samples, from mammogram images of DDSM database. A set of 50 features is calculated for each suspicious area. After this, an optimal subset of 23 most suitable features is selected from 50 features by Particle Swarm Optimization (PSO). The results of proposed study are quite promising.

Keywords: clusters of microcalcifications, ductal carcinoma in situ, least-square support vector machine, particle swarm optimization

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Authors: Chen Chih-Cheng, Chen I-Cheng, Lee Yung-Tan, Kuo Yen-Whea, Yu Chin-Hung

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The purpose of this study is to construct a model for best spike player selection in a top volleyball tournament of the world. Data consisted of the records of 2013 World Grand Prix declared by International Volleyball Federation (FIVB). Simple Multiple-Attribute Rating Technique (SMART) was used for optimal decision-making model on the best spike player selection. The research results showed that the best spike player ranking by SMART is different than the ranking by FIVB. The results demonstrated the effectiveness and feasibility of the proposed model.

Keywords: simple multiple-attribute rating technique, World Grand Prix, best spike player, International Volleyball Federation

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Authors: Sinsze Koo, Benjin Luo, Matthew Henry

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In order to increase the performance of an automatic transmission, the automatic transmission fluid is required to be warm up to an optimal operating temperature. In a conventional vehicle, cold starts result in friction loss occurring in the gear box and engine. The stop and go nature of city driving dramatically affect the warm-up of engine oil and automatic transmission fluid and delay the time frame needed to reach an optimal operating temperature. This temperature phenomenon impacts both engine and transmission performance but also increases fuel consumption and CO2 emission. The aim of this study is to develop know-how of the thermal behavior in order to identify thermal impacts and functional principles in automatic transmissions. Thermal behavior was studied using models and simulations, developed using GT-Suit, on a one-dimensional thermal and flow transport. A power train of a conventional vehicle was modeled in order to emphasis the thermal phenomena occurring in the various components and how they impact the automatic transmission performance. The simulation demonstrates the thermal model of a transmission fluid cooling system and its component parts in warm-up after a cold start. The result of these analyses will support the future designs of transmission systems and components in an attempt to obtain better fuel efficiency and transmission performance. Therefore, these thermal analyses could possibly identify ways that improve existing thermal management techniques with prioritization on fuel efficiency.

Keywords: thermal management, automatic transmission, hybrid, and systematic approach

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Authors: Jianzhou Ni, Hua Fan

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It has been determined that supervisor support has a major influence on postgraduate students' academic emotions and is considered a method of successfully anticipating postgraduates' good psychological well-being levels. As a result, by assessing the mediating influence upon academic emotions for contemporary postgraduates in China, this study investigated the tight reciprocal relationship between psychological empowerment and positive mental well-being among postgraduates. To that end, a help enables a theoretical analysis of role clarity, academic emotion, and positive psychological health was developed, and its validity and reliability were demonstrated for the first time using the normalized postgrad relationship with supervisor scale, academic emotion scale, and positive mental scale, as well as questionnaire data from Chinese postgraduate students. This study used the cross-lagged (ARCL) panel model data to longitudinally measure 798 valid data from two survey questions polls taken in 2019 (T1) and 2021 (T2) to investigate the link between supervisor support and positive graduate student mental well-being in a bidirectional relationship of influence. The study discovered that mentor assistance could have a considerable beneficial impact on graduate students' academic emotions and, as a result, indirectly help learners attain positive mental health development. This verifies the theoretical premise that academic emotions partially mediate the effect of mentor support on positive mental health development and argues for the coexistence of the two. The outcomes of this study can help researchers gain a better knowledge of the dynamic interplay among three different research variables: supervisor support, academic emotions, and positive mental health, as well as fill gaps in previous research. In this regard, the study indicated that mentor assistance directly stimulates students' academic drive and assists graduate students in developing good academic emotions, which contributes to the development of positive mental health. However, given the restricted measurement time in this study's cross-lagged panel data and the potential effect of moderating effects other than academic mood on graduate students' good mental health, the results of this study need to be more fully understood and validated.

Keywords: supervisor support, academic emotions, positive mental health, interaction effects, longitudinal cross-lagged measurements

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Authors: Ahmet Ozcan, Onder Alparslan, Anil Sezgin, Omer Cetin

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The use of unmanned systems for different purposes has become very popular over the past decade. Expectations from these systems have also shown an incredible increase in this parallel. But meeting the demands of the tasks are often not possible with the usage of a single unmanned vehicle in a mission, so it is necessary to use multiple autonomous vehicles with different abilities together in coordination. Therefore the usage of the same type of vehicles together as a swarm is helped especially to satisfy the time constraints of the missions effectively. In other words, it allows sharing the workload by the various numbers of homogenous platforms together. Besides, it is possible to say there are many kinds of problems that require the usage of the different capabilities of the heterogeneous platforms together cooperatively to achieve successful results. In this case, cooperative working brings additional problems beyond the homogeneous clusters. In the scenario presented as an example problem, it is expected that an autonomous ground vehicle, which is lack of its position information, manage to perform point-to-point navigation without losing its way in a previously unknown labyrinth. Furthermore, the ground vehicle is equipped with very limited sensors such as ultrasonic sensors that can detect obstacles. It is very hard to plan or complete the mission for the ground vehicle by self without lost its way in the unknown labyrinth. Thus, in order to assist the ground vehicle, the autonomous air drone is also used to solve the problem cooperatively. The autonomous drone also has limited sensors like downward looking camera and IMU, and it also lacks computing its global position. In this context, it is aimed to solve the problem effectively without taking additional support or input from the outside, just benefiting capabilities of two autonomous vehicles. To manage the point-to-point navigation in a previously unknown labyrinth, the platforms have to work together coordinated. In this paper, cooperative work of heterogeneous unmanned systems is handled in an applied sample scenario, and it is mentioned that how to work together with an autonomous ground vehicle and the autonomous flying platform together in a harmony to take advantage of different platform-specific capabilities. The difficulties of using heterogeneous multiple autonomous platforms in a mission are put forward, and the successful solutions are defined and implemented against the problems like spatially distributed tasks planning, simultaneous coordinated motion, effective communication, and sensor fusion.

Keywords: unmanned systems, heterogeneous autonomous vehicles, coordination, task planning

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Authors: Tori Reddy Dodla, Laura Ann Jones

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The objective of this study was to propose strategies to improve the efficiency of Knowledge Management Systems (KMS). This study highlights best practices from various industries to create an overall summary of Knowledge Management (KM) and efficiency in organizational performance. Results indicated eleven best practices for maximizing the efficiency of organizational KMS that can be divided into four categories: Designing the KMS, Identifying Case Studies, Implementing the KMS, and Promoting adoption and usage. Our findings can be used as a foundation for scholars to conduct further research on KMS efficiency.

Keywords: artificial intelligence, knowledge management efficiency, knowledge management systems, organizational performance

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Authors: Chih-Hsiang Chang, Fang-Jyun Su

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This paper explores whether stock characteristics influence the herding formation among investors in the US equity market. To extend the research scope of the existing literature, this paper further examines the role that stock risk characteristics play in the US equity market, and the way they influence investors’ decision-making. First, empirical results show that whether general stocks or high-risk stocks, there are no herding behaviors among the investors in the US equity market during the whole research period or during four great events. Moreover, stock characteristics have great influence on investors’ trading decisions. Finally, there is a bidirectional lead-lag relationship of the herding formation between high-risk stocks and low-risk stocks, but the influence of high-risk stocks on the low-risk stocks is stronger than that of low-risk stocks on the high-risk stocks.

Keywords: stock characteristics, herding formation, investment decision, US equity market, lead-lag relationship

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Authors: Allison Futter

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Lifetime use of electronic cigarettes (EC) in college students has been estimated at around 50%; recent research shows Mobile Health (mHealth) technology is a promising tool to help address this public health issue, yet the majority of EC cessation mHealth tools found on smartphone app stores lack empirical support of their effectiveness. The Smiling Instead of Smoking (SiS) app is a positive psychology-based smartphone app for nondaily smokers. Due to previous success with brief, self-administered positive psychology exercises for cigarette cessation, this study examined the SiS App’s feasibility and effectiveness for EC cessation. Sixteen undergraduates used the SiS app for 3 weeks: one week before their quit date and 2 weeks after. As hypothesized, participants had significant declines in their craving and maintained pre-cessation levels of positive affect. There were no significant changes in dependency or self-efficacy. In the one-month follow-up survey, 38% of participants reported being abstinent. The app had an almost 4-star rating for its features (e.g., functionality, aesthetics, information, etc.) and participants reported moderate satisfaction with its use. Participants used the app, on average, 10 out of the 21 days of the prescribed app use. This study highlights the promise of mHealth support and positive psychology for EC cessation, adding to the understanding of possible ways to support EC quit attempts.

Keywords: e-cigarette cessation, mHealth, positive psychology, smartphone app

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Authors: Aby Nesan Raj, Sumil K. Raj, Sumesh Jayan

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The objective of the study is to formulate a self-regulation model that shall enhance the usage of Intelligent Transportation Systems by understanding the theory of self-efficacy. The core logic of the self-regulation model shall monitor driver's behavior based on the situations related to the various sources of Self Efficacy like enactive mastery, vicarious experience, verbal persuasion and physiological arousal in addition to the vehicle data. For this study, four different vehicle data, speed, drowsiness, diagnostic data and surround camera views are considered. This data shall be given to the self-regulation model for evaluation. The oddness, which is the output of self-regulation model, shall feed to Intelligent Transportation Systems where appropriate actions are being taken. These actions include warning to the user as well as the input to the related transportation systems. It is also observed that the usage of vehicle as a sensor reduces the wastage of resource utilization or duplication. Altogether, this approach enhances the intelligence of the transportation systems especially in safety, productivity and environmental performance.

Keywords: emergency management, intelligent transportation system, self-efficacy, traffic management

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Authors: Zhuofan Cheng, Qiongda Hu, Mohammed El-Hajjar, Basel Halak

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Multiple-input multiple-output (MIMO) systems can allow significantly higher data rates compared to single-antenna-aided systems. They are expected to be a prominent part of the 5G communication standard. However, these decoders suffer from high power consumption. This work presents a design technique in order to improve the energy efficiency of MIMO systems; this facilitates their use in the next generation of battery-operated communication devices such as mobile phones and tablets. The proposed optimization approach consists of the use of low complexity lattice reduction algorithm in combination with an adaptive VLSI implementation. The proposed design has been realized and verified in 65nm technology. The results show that the proposed design is significantly more energy-efficient than conventional K-best MIMO systems.

Keywords: energy, lattice reduction, MIMO, VLSI

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Authors: M. Kowalski, M. Życzkowski, M. Karol

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Current quantum key distribution systems (QKD) offer low bit rate of up to single MHz. Compared to conventional optical fiber links with multiple GHz bitrates, parameters of recent QKD systems are significantly lower. In the article we present the conception of application of the Compressed Sensing method for compression of quantum information. The compression methodology as well as the signal reconstruction method and initial results of improving the throughput of quantum information link are presented.

Keywords: quantum key distribution systems, fiber optic system, compressed sensing

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Authors: Mingwei Yi, Liujie Guo, Zongjun Pan, Xiang Lin, Xiaoming Yi

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With the rapid expansion of road construction mileage in China, the scale of road maintenance needs has concurrently escalated. As the service life of roads extends, the design of pavement repair and maintenance emerges as a crucial component in preserving the excellent performance of the pavement. The remaining service life of asphalt pavement structure is a vital parameter in the lifecycle maintenance design of asphalt pavements. Based on an analysis of pavement structural integrity, this study introduces a characterization and assessment of the remaining life of existing asphalt pavement structures. It proposes indicators such as the transverse crack spacing and the length of longitudinal cracks. The transverse crack spacing decreases with an increase in maintenance intervals and with the extended use of semi-rigid base layer structures, although this trend becomes less pronounced after maintenance intervals exceed 4 years. The length of longitudinal cracks increases with longer maintenance intervals, but this trend weakens after five years. This system can support the enhancement of standardization and scientific design in highway maintenance decision-making processes.

Keywords: structural integrity, highways, pavement evaluation, asphalt concrete pavement

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Authors: Mohamed Amhal, Jose Sayritupac

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Photovoltaic (PV) systems have risen as one of the modern renewable energy sources that are used in wide ranges to produce electricity and deliver it to the electrical grid. In parallel, monitoring systems have been deployed as a key element to track the energy production and to forecast the total production for the next days. The reliability of the PV energy production has become a crucial point in the analysis of PV systems. A deeper understanding of each phenomenon that causes a gain or a loss of energy is needed to better design, operate and maintain the PV systems. This work analyzes the current losses distribution in PV systems starting from the available solar energy, going through the DC side and AC side, to the delivery point. Most of the phenomena linked to energy losses and gains are considered and modeled, based on real time monitoring data and datasheets of the PV system components. An analysis of the order of magnitude of each loss is compared to the current literature and commercial software. To date, the analysis of PV systems performance based on a breakdown structure of energy losses and gains is not covered enough in the literature, except in some software where the concept is very common. The cutting-edge of the current analysis is the implementation of software tools for energy losses estimation in PV systems based on several energy losses definitions and estimation technics. The developed tools have been validated and tested on some PV plants in France, which are operating for years. Among the major findings of the current study: First, PV plants in France show very low rates of soiling and aging. Second, the distribution of other losses is comparable to the literature. Third, all losses reported are correlated to operational and environmental conditions. For future work, an extended analysis on further PV plants in France and abroad will be performed.

Keywords: energy gains, energy losses, losses distribution, monitoring, photovoltaic, photovoltaic systems

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Authors: Pirta Palola, Richard Bailey, Lisa Wedding

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Societies and economies worldwide fundamentally depend on natural capital. Alarmingly, natural capital assets are quickly depreciating, posing an existential challenge for humanity. The development of robust natural capital accounting systems is essential for transitioning towards sustainable economic systems and ensuring sound management of capital assets. However, the accurate, equitable and comprehensive estimation of natural capital asset stocks and their accounting values still faces multiple challenges. In particular, the representation of socio-cultural values held by groups or communities has arguably been limited, as to date, the valuation of natural capital assets has primarily been based on monetary valuation methods and assumptions of individual rationality. People relate to and value the natural environment in multiple ways, and no single valuation method can provide a sufficiently comprehensive image of the range of values associated with the environment. Indeed, calls have been made to improve the representation of multiple types of value (instrumental, intrinsic, and relational) and diverse ontological and epistemological perspectives in environmental valuation. This study addresses this need by establishing a novel valuation framework, Environmental Value Functions (EVF), that allows for the integration of multiple types of value in natural capital accounting systems. The EVF framework is based on the estimation and application of value functions, each of which describes the relationship between the value and quantity (or quality) of an ecosystem component of interest. In this framework, values are estimated in terms of change relative to the current level instead of calculating absolute values. Furthermore, EVF was developed to also support non-marginalist conceptualizations of value: it is likely that some environmental values cannot be conceptualized in terms of marginal changes. For example, ecological resilience value may, in some cases, be best understood as a binary: it either exists (1) or is lost (0). In such cases, a logistic value function may be used as the discriminator. Uncertainty in the value function parameterization can be considered through, for example, Monte Carlo sampling analysis. The use of EVF is illustrated with two conceptual examples. For the first time, EVF offers a clear framework and concrete methodology for the representation of multiple types of value in natural capital accounting systems, simultaneously enabling 1) the complementary use and integration of multiple valuation methods (monetary and non-monetary); 2) the synthesis of information from diverse knowledge systems; 3) the recognition of value incommensurability; 4) marginalist and non-marginalist value analysis. Furthermore, with this advancement, the coupling of EVF and ecosystem modeling can offer novel insights to the study of spatial-temporal dynamics in natural capital asset values. For example, value time series can be produced, allowing for the prediction and analysis of volatility, long-term trends, and temporal trade-offs. This approach can provide essential information to help guide the transition to a sustainable economy.

Keywords: economics of biodiversity, environmental valuation, natural capital, value function

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Authors: A. Abbou, V. Makis, N. Salari

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We study the condition-based maintenance (CBM) problem of a system subject to stochastic deterioration. The system is composed of three units (or modules): (i) Module 1 deterioration follows a Markov process with two operational states and one failure state. The operational states are partially observable through periodic condition monitoring. (ii) Module 2 deterioration follows a Gamma process with a known failure threshold. The deterioration level of this module is fully observable through periodic inspections. (iii) Only the operating age information is available of Module 3. The lifetime of this module has a general distribution. A CBM policy prescribes when to initiate a maintenance intervention and which modules to repair during intervention. Our objective is to determine the optimal CBM policy minimizing the long-run expected average cost of operating the system. This is achieved by formulating a Markov decision process (MDP) and developing the value iteration algorithm for solving the MDP. We provide numerical examples illustrating the cost-effectiveness of the optimal CBM policy through a comparison with heuristic policies commonly found in the literature.

Keywords: reliability, maintenance optimization, Markov decision process, heuristics

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Authors: Avelino Marques, Diamantino Freitas

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Some important electroacoustic systems, like loudspeaker systems, exhibit a nonminimum phase behavior that poses considerable effort when applying advanced digital signal processing techniques, such as linear equalization. In this paper, the position and the number of zeros and poles of the inverse filter, FIR type or IIR type, designed using time domain techniques, are studied, compared and related to the nonminimum phase zeros of system to be equalized. Conclusions about the impact of the position of the system non-minimum phase zeros, on the length/order of the inverse filter and on the delay of the equalized system are outlined as a guide to previously decide which type of filter will be more adequate.

Keywords: loudspeaker systems, nonminimum phase system, FIR and IIR filter, delay

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Authors: Shiyun Liu

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Radiant heating systems work fundamentally differently from air systems by taking advantage of both radiant and convective heat transfer to remove space heating load. There are rare studies on differences of heating systems between all-air system and radiant floor system. This paper uses the method of simulation based on state-space to calculate the indoor temperature and wall temperature of each system and shows how the dynamic heat transfer in rooms conditioned by a radiant system is different from an air system. Then this paper analyses the changes of indoor temperature of these two systems, finding out the differences between all-air heating system and radiant floor heating system to help the designer choose a more suitable heating system.

Keywords: radiant floor, all-air system, thermal comfort, simulation, heating system

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Authors: Gaurav Kumar Sinha

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The oil and gas industry is a critical component of the global economy, relying heavily on industrial control systems (ICS) to manage and monitor operations. However, these systems are increasingly becoming targets for cyber-attacks, posing significant risks to operational continuity, safety, and environmental integrity. This paper explores comprehensive cybersecurity strategies for protecting oil and gas industrial control systems. It delves into the unique vulnerabilities of ICS in this sector, including outdated legacy systems, integration with IT networks, and the increased connectivity brought by the Industrial Internet of Things (IIoT). We propose a multi-layered defense approach that includes the implementation of robust network security protocols, regular system updates and patch management, advanced threat detection and response mechanisms, and stringent access control measures. We illustrate the effectiveness of these strategies in mitigating cyber risks and ensuring the resilient and secure operation of oil and gas industrial control systems. The findings underscore the necessity for a proactive and adaptive cybersecurity framework to safeguard critical infrastructure in the face of evolving cyber threats.

Keywords: cybersecurity, industrial control systems, oil and gas, cyber-attacks, network security, IoT, threat detection, system updates, patch management, access control, cybersecurity awareness, critical infrastructure, resilience, cyber threats, legacy systems, IT integration, multi-layered defense, operational continuity, safety, environmental integrity

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Authors: Walid Moudani

Abstract:

The Crew Reserve Assignment Problem (CRAP) considers the assignment of the crew members to a set of reserve activities covering all the scheduled flights in order to ensure a continuous plan so that operations costs are minimized while its solution must meet hard constraints resulting from the safety regulations of Civil Aviation as well as from the airlines internal agreements. The problem considered in this study is of highest interest for airlines and may have important consequences on the service quality and on the economic return of the operations. In this communication, a new mathematical formulation for the CRAP is proposed which takes into account the regulations and the internal agreements. While current solutions make use of Artificial Intelligence techniques run on main frame computers, a low cost approach is proposed to provide on-line efficient solutions to face perturbed operating conditions. The proposed solution method uses a dynamic programming approach for the duties scheduling problem and when applied to the case of a medium airline while providing efficient solutions, shows good potential acceptability by the operations staff. This optimization scheme can then be considered as the core of an on-line Decision Support System for crew reserve assignment operations management.

Keywords: airlines operations management, combinatorial optimization, dynamic programming, crew scheduling

Procedia PDF Downloads 351

Authors: Mohammad Nadeem, Haider Banka, R. Venugopal

Abstract:

Granulation or agglomeration is a size enlargement process to transform the fine particulates into larger aggregates since the fine size of available materials and minerals poses difficulty in their utilization. Though a long list of methods is available in the literature for the modeling of granulation process to facilitate the in-depth understanding and interpretation of the system, there is still scope of improvements using novel tools and techniques. Intelligent techniques, such as artificial neural network, fuzzy logic, self-organizing map, support vector machine and others, have emerged as compelling alternatives for dealing with imprecision and complex non-linearity of the systems. The present study tries to review the applications of intelligent techniques in the modeling of size enlargement process for fine materials.

Keywords: fine material, granulation, intelligent technique, modelling

Procedia PDF Downloads 369

Authors: Dzmitry M. Kabanau, Vladimir V. Kabanov, Yahor V. Lebiadok, Denis V. Shabrov, Pavel V. Shpak, Gevork T. Mikaelyan, Alexandr P. Bunichev

Abstract:

This article is deal with the experimental investigations of the laser diode matrixes (LDM) based on the AlGaAs/GaAs heterostructures (lasing wavelength 790-880 nm) to find optimal LDM parameters for active vision systems. In particular, the dependence of LDM radiation pulse power on the pulse duration and LDA active layer heating as well as the LDM radiation divergence are discussed.

Keywords: active vision systems, laser diode matrixes, thermal properties, radiation divergence

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Authors: Nevruz Zogu, Shpetim Rezniqi

Abstract:

In the framework of transformational economic development social pluralism and the free, market health systems operating in the countries of our region are naturally involved in a process of profound change and reform. Health systems actually represent complex ensembles centers and public and private institutions (domestic and foreign), who administer substantial amounts of human, technological, material, financial, information and scientific facts • The goal of health systems is much more than medical care. It includes the promotion, protection, treatment and rehabilitation of health of the population. • Meeting the needs of increasingly diverse broader health services efficient, secure the quality and affordability of their increasing cost of unstoppable, requires the necessary reform of health systems and implementing policies and new management methods, to ensure effectiveness and health benefits as higher population.

Keywords: health, management, economy, finance

Procedia PDF Downloads 416