Search results for: thoughtful decision support system

Authors: Marina Diković

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By giving personal opinions, suggestions and criticism through e-democracy, young people can reinforce the adoption of decisions which they have an impact on. The purpose of this research was to examine the opinion of university students about the possibility of their decision-making by using information and communication technology (ICT). The questionnaire examined young people's values and behaviour associated with e-democracy and the related decision-making. Students are most active online when it comes to finding information connected with their academic responsibilities, but less frequently take part in democratic processes in society, both at the national and local level. E-democracy as a tool can be learned in programmes of Human Rights Education and Citizenship Education. 

Keywords: active citizens, e-democracy, information and communication technology (ICT), university students

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Authors: Atousa Khodadadyan, Gabe Mythen, Hirbod Assa, Beverley Bishop

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Risk assessment and the knowledge provided through this process is a crucial part of any decision-making process in the management of risks and uncertainties. Failure in assessment of risks can cause inadequacy in the entire process of risk management, which in turn can lead to failure in achieving organisational objectives as well as having significant damaging consequences on populations affected by the potential risks being assessed. The choice of tools and techniques in risk assessment can influence the degree and scope of decision-making and subsequently the risk response strategy. There are various available qualitative and quantitative tools and techniques that are deployed within the broad process of risk assessment. The sheer diversity of tools and techniques available to practitioners makes it difficult for organisations to consistently employ the most appropriate methods. This tools and techniques adaptation is rendered more difficult in public risk regulation organisations due to the sensitive and complex nature of their activities. This is particularly the case in areas relating to the environment, food, and human health and safety, when organisational goals are tied up with societal, political and individuals’ goals at national and international levels. Hence, recognising, analysing and evaluating different decision support tools and techniques employed in assessing risks in public risk management organisations was considered. This research is part of a mixed method study which aimed to examine the perception of risk assessment and the extent to which organisations practise risk assessment’ tools and techniques. The study adopted a semi-structured questionnaire with qualitative and quantitative data analysis to include a range of public risk regulation organisations from the UK, Germany, France, Belgium and the Netherlands. The results indicated the public risk management organisations mainly use diverse tools and techniques in the risk assessment process. The primary hazard analysis; brainstorming; hazard analysis and critical control points were described as the most practiced risk identification techniques. Within qualitative and quantitative risk analysis, the participants named the expert judgement, risk probability and impact assessment, sensitivity analysis and data gathering and representation as the most practised techniques.

Keywords: decision-making, public risk management organisations, risk assessment, tools and techniques

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Authors: Tayyaba Azim, Bibi Amina

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The increase in the popularity of opinion mining with the rapid growth in the availability of social networks has attracted a lot of opportunities for research in the various domains of Sentiment Analysis and Natural Language Processing (NLP) using Artificial Intelligence approaches. The latest trend allows the public to actively use the internet for analyzing an individual’s opinion and explore the effectiveness of published facts. The main theme of this research is to account the public opinion on the most crucial and extensively discussed development projects, China Pakistan Economic Corridor (CPEC), considered as a game changer due to its promise of bringing economic prosperity to the region. So far, to the best of our knowledge, the theme of CPEC has not been analyzed for sentiment determination through the ML approach. This research aims to demonstrate the use of ML approaches to spontaneously analyze the public sentiment on Twitter tweets particularly about CPEC. Support Vector Machine SVM is used for classification task classifying tweets into positive, negative and neutral classes. Word2vec and TF-IDF features are used with the SVM model, a comparison of the trained model on manually labelled tweets and automatically generated lexicon is performed. The contributions of this work are: Development of a sentiment analysis system for public tweets on CPEC subject, construction of an automatic generation of the lexicon of public tweets on CPEC, different themes are identified among tweets and sentiments are assigned to each theme. It is worth noting that the applications of web mining that empower e-democracy by improving political transparency and public participation in decision making via social media have not been explored and practised in Pakistan region on CPEC yet.

Keywords: machine learning, natural language processing, sentiment analysis, support vector machine, Word2vec

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Authors: Misrak Assefa

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The Amharic language is the second most widely spoken Semitic language in the world. There are several new overloaded on the web. Searching some useful documents from the web on a specific topic, which is written in the Amharic language, is a challenging task. Hence, document categorization is required for managing and filtering important information. In the classification of Amharic text news, there is still a gap in the domain of information that needs to be launch. This study attempts to design an automatic Amharic news classification using a supervised learning mechanism on four un-touch classes. To achieve this research, 4,182 news articles were used. Naive Bayes (NB) and Decision tree (j48) algorithms were used to classify the given Amharic dataset. In this paper, k-fold cross-validation is used to estimate the accuracy of the classifier. As a result, it shows those algorithms can be applicable in Amharic news categorization. The best average accuracy result is achieved by j48 decision tree and naïve Bayes is 95.2345 %, and 94.6245 % respectively using three categories. This research indicated that a typical decision tree algorithm is more applicable to Amharic news categorization.

Keywords: text categorization, supervised machine learning, naive Bayes, decision tree

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Authors: Deyu Zhou, Xiao Xue, Lizhen Cui

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With the increasing collaboration among various services and the growing complexity of user demands, there are more and more factors affecting the stable development of the cloud manufacturing service economic system (CMSE). This poses new challenges to the evolution analysis of the CMSE. Many researchers have modeled and analyzed the evolution process of CMSE from the perspectives of individual learning and internal factors influencing the system, but without considering other important characteristics of the system's individuals (such as heterogeneity, bounded rationality, etc.) and the impact of external environmental factors. Therefore, this paper proposes an integrated artificial social model for the cloud manufacturing service economic system, which considers both the characteristics of the system's individuals and the internal and external influencing factors of the system. The model consists of three parts: the Agent model, environment model, and rules model (Agent-Environment-Rules, AER): (1) the Agent model considers important features of the individuals, such as heterogeneity and bounded rationality, based on the adaptive behavior mechanisms of perception, action, and decision-making; (2) the environment model describes the activity space of the individuals (real or virtual environment); (3) the rules model, as the driving force of system evolution, describes the mechanism of the entire system's operation and evolution. Finally, this paper verifies the effectiveness of the AER model through computational and experimental results.

Keywords: cloud manufacturing service economic system (CMSE), AER model, artificial social modeling, integrated framework, computing experiment, agent-based modeling, social networks

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Authors: Sihem Oujdi, Hafida Belbachir

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Existing methods of data mining cannot be applied on spatial data because they require spatial specificity consideration, as spatial relationships. This paper focuses on the classification with decision trees, which are one of the data mining techniques. We propose an extension of the C4.5 algorithm for spatial data, based on two different approaches Join materialization and Querying on the fly the different tables. Similar works have been done on these two main approaches, the first - Join materialization - favors the processing time in spite of memory space, whereas the second - Querying on the fly different tables- promotes memory space despite of the processing time. The modified C4.5 algorithm requires three entries tables: a target table, a neighbor table, and a spatial index join that contains the possible spatial relationship among the objects in the target table and those in the neighbor table. Thus, the proposed algorithms are applied to a spatial data pattern in the accidentology domain. A comparative study of our approach with other works of classification by spatial decision trees will be detailed.

Keywords: C4.5 algorithm, decision trees, S-CART, spatial data mining

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Authors: Martin Doran, Roy Sterritt, George Wilkie

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NASA, ESA, and NSSC space agencies have plans to put planetary rovers on Mars in 2020. For these future planetary rovers to succeed, they will heavily depend on sensors to detect obstacles. This will also become of vital importance in the future, if rovers become less dependent on commands received from earth-based control and more dependent on self-configuration and self-decision making. These planetary rovers will face harsh environments and the possibility of hardware failure is high, as seen in missions from the past. In this paper, we focus on using Autonomic principles where self-healing, self-optimization, and self-adaption are explored using the MAPE-K model and expanding this model to encapsulate the attributes such as Awareness, Analysis, and Adjustment (AAA-3). In the experimentation, a Pioneer P3-DX research robot is used to simulate a planetary rover. The sonar sensors on the P3-DX robot are used to simulate the sensors on a planetary rover (even though in reality, sonar sensors cannot operate in a vacuum). Experiments using the P3-DX robot focus on how our software system can be adapted with the loss of sonar sensor functionality. The autonomic manager system is responsible for the decision making on how to make use of remaining ‘enabled’ sonars sensors to compensate for those sonar sensors that are ‘disabled’. The key to this research is that the robot can still detect objects even with reduced sonar sensor capability.

Keywords: autonomic, self-adaption, self-healing, self-optimization

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Authors: Michel Patiño-Sáenz, Martín Haissiner, Jorge Martínez-Cotrina, Daniel Pastor, Hernando Santamaría-García, Maria-Alejandra Tangarife, Agustin Ibáñez, Sandra Baez

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It has been shown that gruesome descriptions of harm can increase the punishment given to a transgressor. This biasing effect is mediated by negative emotions, which are elicited upon the presentation of gruesome descriptions. However, there is a lack of studies inquiring the influence of such descriptions on moral decision-making in people involved in the criminal justice system. Such populations are of special interest since they have experience dealing with gruesome evidence, but also formal education on how to assess evidence and gauge the appropriate punishment according to the law. Likewise, they are expected to be objective and rational when performing their duty, because their decisions can impact profoundly people`s lives. Considering these antecedents, the objective of this study was to explore the influence gruesome written descriptions on moral decision-making in this group of people. To that end, we recruited attorneys, judges and public prosecutors (Criminal justice group, CJ, n=30) whose field of specialty is criminal law. In addition, we included a control group of people who did not have a formal education in law (n=30), but who were paired in age and years of education with the CJ group. All participants completed an online, Spanish-adapted version of a moral decision-making task, which was previously reported in the literature and also standardized and validated in the Latin-American context. A series of text-based stories describing two characters, one inflicting harm on the other, were presented to participants. Transgressor's intentionality (accidental vs. intentional harm) and language (gruesome vs. plain) used to describe harm were manipulated employing a within-subjects and a between-subjects design, respectively. After reading each story, participants were asked to rate (a) the harmful action's moral adequacy, (b) the amount of punishment deserving the transgressor and (c) how damaging was his behavior. Results showed main effects of group, intentionality and type of language on all dependent measures. In both groups, intentional harmful actions were rated as significantly less morally adequate, were punished more severely and were deemed as more damaging. Moreover, control subjects deemed more damaging and punished more severely any type of action than the CJ group. In addition, there was an interaction between intentionality and group. People in the control group rated harmful actions as less morally adequate than the CJ group, but only when the action was accidental. Also, there was an interaction between intentionality and language on punishment ratings. Controls punished more when harm was described using gruesome language. However, that was not the case of people in the CJ group, who assigned the same amount of punishment in both conditions. In conclusion, participants with job experience in the criminal justice system or criminal law differ in the way they make moral decisions. Particularly, it seems that they are less sensitive to the biasing effect of gruesome evidence, which is probably explained by their formal education or their experience in dealing with such evidence. Nonetheless, more studies are needed to determine the impact this phenomenon has on the fulfillment of their duty.

Keywords: criminal justice system, emotions, gruesome descriptions, intentionality, moral decision-making

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Authors: Ahmad Masduki Bin Selamat, Kang Chia Yang

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The International Standard Organization (ISO) is an international consensus on good management practice. It is derived from the Greek word “isos” meaning equal. ISO is aimed to give organization guidelines on what bring quality management system that leads to continuous improvement. The need of quality product is essential these days, especially in the manufacturing and service sectors. The requirement to produce good product is demanded, hence the certification of ISO enables the company to gain the trust from the public. Due to this, organizations whether government or private sectors in Malaysia are going for the ISO certification. However recently there has been an introduction of Islamic standard known as Islamic Standard Institute 2020 (ISI 2020). The ISI standards emphasize more on values that should be in the employees’ mind. By possessing good values, employees will work only for the betterment of the company. Currently only the feelings of being paid for the job exist in the employees’ mind. The non-Malays like Chinese and others, which comprise 40% of the sample size, are not aware about the existence of any Islamic quality system. As for the Malay managers, they support the Islamic quality systems. For them such values are encouraged by religion. By imitating religion, Allah promises a better life in this world and hereafter. Even though ISI 2020 is still new but the majority of Malays would support the need of Islamic quality system. Our findings suggest that integration of these two-quality systems running parallel would bring a better result.

Keywords: International Standard Organization (ISO), Islamic standard, quality, ISI 2020

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Authors: Jawaher Bakheet Almudarra

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The Saudi Arabian educational system shared the philosophical principles, in its foundation, which concentrated on the achievement of goals, thereby taking up authoritative styles of leadership. However, organisations are beginning to be more liberal in today’s environment than in the 1940s and 1950s, and appealing to emotional intelligence as a tool and skill are needed for effective leadership. In the Saudi Arabian case, such developments are characterised by changes such as that of the educational supervisor having the role redefined to that of a director. This review tracks several parts: the first section helps western reader to understand the subtleties, complexities, and intricacies of the Saudi Arabia education system and its approach to leadership system of education, history, culture and political contribution. This can lead to the larger extent understand if emotional intelligence is a provocation for better leadership of Saudi Arabian education sector or not. The second part is the growth of educational supervision in Saudi Arabia, focusing on the education system, and evaluates the impact of emotional intelligence as a necessary skill in leadership. The third section looks at emotions and emotional intelligence, gender roles, and contributions by emotional intelligence in the education system. The education system of Saudi Arabia has undergone significant transformation. To fully understand the current climate of Saudi Arabia, it is essential to review this process of transformation in terms of the historical, cultural, political and social positions and transformations. Over the years, the education system in Saudi Arabia has undergone significant metamorphosis. The Saudi government has instituted a wide range of reforms in an attempt to improve education standards and outcomes, facilitate improvements and ensure that high standards of education standards are upheld to keep pace with the global environment and knowledge economy. Leadership itself has become an increasingly prominent aspect of educational reform worldwide. Emotional intelligence is often considered a significant aspect of leadership, but it is in its early stages in Saudi Arabia. Its recognition and adoption may improve leadership practices, particularly among educational supervisors and contribute to national and international understandings of leadership in Saudi Arabia. Studying leadership in the Saudi Arabian context is imperative as the new generation of leaders need to cultivate pertinent skills that will allow them to become fundamentally and positively involved in the regions’ decision making processes in order to impact the progression of the Saudi Arabian education system. Understanding leadership in the education context will allow for suitable inculcation of leadership skills. These skills include goal-setting, sound decision-making as well as problem-solving within the education system of Saudi Arabia.

Keywords: educational supervision, educational administration, emotional intelligence, educational leadership

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Authors: Ziraguen O. Williams, Shield B. Lin, Fouad N. Matari, Leslie J. Quiocho

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In a task to assist NASA in analyzing the dynamic forces caused by operational countermeasures of an astronaut’s exercise platform impacting the spacecraft, feedback delay, and signal noise were added to a simulation model of an active-controlled vibration isolation system to regulate the movement of the exercise platform. Previous simulation work was conducted primarily via MATLAB/Simulink. Two additional simulation tools used in this study were Trick and MBDyn, NASA co-developed software simulation environments. Simulation results obtained from these three tools were very similar. All simulation results support the hypothesis that an active-controlled vibration isolation system outperforms a passive-controlled system even with the addition of feedback delay and signal noise to the active-controlled system. In this paper, squat exercise was used in creating excited force to the simulation model. The exciter force from a squat exercise was calculated from the motion capture of an exerciser. The simulation results demonstrate much greater transmitted force reduction in the active-controlled system than the passive-controlled system.

Keywords: control, counterweight, isolation, vibration

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Authors: Zohra Mekranfar, Ahmed Saidi, Abdellah Mebrek

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This work aims to develop multi-criteria decision making (MCDM) and spatial data warehouse (SDW) methods, which will be integrated into a GIS according to a ‘GIS dominant’ approach. The GIS operating tools will be operational to operate the SDW. The MCDM methods can provide many solutions to a set of problems with various and multiple criteria. When the problem is so complex, integrating spatial dimension, it makes sense to combine the MCDM process with other approaches like data mining, ascending analyses, we present in this paper an experiment showing a geo-decisional methodology of SWD construction, On-line analytical processing (OLAP) technology which combines both basic multidimensional analysis and the concepts of data mining provides powerful tools to highlight inductions and information not obvious by traditional tools. However, these OLAP tools become more complex in the presence of the spatial dimension. The integration of OLAP with a GIS is the future geographic and spatial information solution. GIS offers advanced functions for the acquisition, storage, analysis, and display of geographic information. However, their effectiveness for complex spatial analysis is questionable due to their determinism and their decisional rigor. A prerequisite for the implementation of any analysis or exploration of spatial data requires the construction and structuring of a spatial data warehouse (SDW). This SDW must be easily usable by the GIS and by the tools offered by an OLAP system.

Keywords: data warehouse, GIS, MCDM, SOLAP

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Authors: Malte Brettel, David Bendig, Michael Keller, Marius Rosenberg

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What are the core competences necessary in order to sustain manufacturing in high-wage countries? Aspiring countries all over the world gain market share in manufacturing and rapidly close the productivity and quality gap that has until now protected some parts of the industry in Europe and the United States from dislocation. However, causal production planning and manufacturing, the basis for productivity and quality, is challenged by the ever-greater need for flexibility and customized products in an uncertain business environment. This article uses a case-study-based approach to assess how production managers in high-wage countries can apply decision-making principals from successful entrepreneurs. 'Effectuation' instead of causal decision making can be applied to handle uncertainty of mass customization, to seek the right partners in alliances and to advance towards virtual production. The findings help managers to use their resources more efficiently and contribute to bridge the gap between production research and entrepreneurship.

Keywords: case studies, decision-making behavior, effectuation, production planning

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Authors: Vasoontara Yiengprugsawan, Sam-ang Seubsman

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As Thais live longer, caregivers will become even more important to social and healthcare systems. Commonly reported in many low and middle‐income countries in Asia, formal social welfare services to support caregivers are lacking and informal family support will be required for all levels of care. In 2005, 87,151 open‐university adults were recruited to the Thai Cohort Study, with the majority aged between 25 and 39 years, and residing nationwide. At the 4‐year follow up in 2009 (n=60569) and the 8‐year follow‐up in 2013 (n=42785), prospective cohort participants were asked if they provide care for chronically ill, disabled, or frail family members. Among Thai cohort members reporting between 2009 and 2013, approximately 56% were not caregivers in either year, 24.5% reported providing care in 2009 only, 8.6% in 2013 only, and 10.6% reported providing care at both time points. Caregivers in the cohort reported providing financial support, help with shopping, emotional support, and assist with daily activities. Kessler 6 psychological distress scale, measured in both 2009 and 2013, was used as the primary outcome of a relationship between caregiving status and mental health. Using multivariate logistic regression, our 4‐year longitudinal findings revealed that cohort members who reported providing care at both time points were 1.4 to 1.6 times more likely to report high psychological distress than non‐caregivers, after accounting for potential covariates. With increasing needs for informal care provided by family members, the future health and social welfare system will need to provide adequate support to caregivers (e.g., respite care, clinical support and information for the family, and awareness of mental health among caregivers).

Keywords: family caregivers, psychological distress, prospective cohort, longitudinal study, Thailand

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Authors: Brian Connett, Bryan O'Halloran

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Systems assets within critical infrastructures were seemingly safe from the exploitation or attack by nefarious cyberspace actors. Now, critical infrastructure is a target and the resources to exploit the cyber physical systems exist. These resources are characterized in terms of patience, stealth, replication-ability and extraordinary robustness. System owners are obligated to maintain a high level of protection measures. The difficulty lies in knowing when to fortify a critical infrastructure against an impending attack. Models currently exist that demonstrate the value of knowing the attacker’s capabilities in the cyber realm and the strength of the target. The shortcomings of these models are that they are not designed to respond to the inherent fast timing of an attack, an impetus that can be derived based on open-source reporting, common knowledge of exploits of and the physical architecture of the infrastructure. A useful model will inform systems owners how to align infrastructure architecture in a manner that is responsive to the capability, willingness and timing of the attacker. This research group has used an existing theoretical model for estimating parameters, and through analysis, to develop a decision tool for would-be target owners. The continuation of the research develops further this model by estimating the variable parameters. Understanding these parameter estimations will uniquely position the decision maker to posture having revealed the vulnerabilities of an attacker’s, persistence and stealth. This research explores different approaches to improve on current attacker-defender models that focus on cyber threats. An existing foundational model takes the point of view of an attacker who must decide what cyber resource to use and when to use it to exploit a system vulnerability. It is valuable for estimating parameters for the model, and through analysis, develop a decision tool for would-be target owners.

Keywords: critical infrastructure, cyber physical systems, modeling, exploitation

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Authors: Kang-Mo Jung

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Least squares support vector machine (LS-SVM) is a penalized regression which considers both fitting and generalization ability of a model. However, the squared loss function is very sensitive to even single outlier. We proposed a weighted absolute deviation loss function for the robustness of the estimates in least absolute deviation support vector machine. The proposed estimates can be obtained by a quadratic programming algorithm. Numerical experiments on simulated datasets show that the proposed algorithm is competitive in view of robustness to outliers.

Keywords: least absolute deviation, quadratic programming, robustness, support vector machine, weight

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Authors: Chitra Rajagopal, Indra Deo Kumar, Ruchi Joshi, Binoy Bhargavan

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Role of fighter planes in modern network centric military warfare scenarios has changed significantly in the recent past. New generation fighter planes have multirole capability of engaging both air and ground targets with high precision. Multirole aircraft undertakes missions such as Air to Air combat, Air defense, Air to Surface role (including Air interdiction, Close air support, Maritime attack, Suppression and Destruction of enemy air defense), Reconnaissance, Electronic warfare missions, etc. Designers have primarily focused on development of technologies to enhance the combat performance of the fighter planes and very little attention is given to human factor aspects of technologies. Unique physical and psychological challenges are imposed on the pilots to meet operational requirements during these missions. Newly evolved technologies have enhanced aircraft performance in terms of its speed, firepower, stealth, electronic warfare, situational awareness, and vulnerability reduction capabilities. This paper highlights the impact of emerging technologies on human factors for various military operations and missions. Technologies such as ‘cooperative knowledge-based systems’ to aid pilot’s decision making in military conflict scenarios as well as simulation technologies to enhance human performance is also studied as a part of research work. Current and emerging pilot protection technologies and systems which form part of the integrated life support systems in new generation fighter planes is discussed. System safety analysis application to quantify the human reliability in military operations is also studied.

Keywords: combat effectiveness, emerging technologies, human factors, systems safety analysis

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Authors: A. Luft, S. Bremen, N. Balc

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The task of flexibility planning and design, just like factory planning, for example, is to create the long-term systemic framework that constitutes the restriction for short-term operational management. This is a strategic challenge since, due to the decision defect character of the underlying flexibility problem, multiple types of flexibility need to be considered over the course of various scenarios, production programs, and production system configurations. In this context, an evaluation model has been developed that integrates both conventional and additive resources on a basic task level and allows the quantification of flexibility enhancement in terms of mix and volume flexibility, complexity reduction, and machine capacity. The model helps companies to decide in early decision-making processes about the potential gains of implementing additive manufacturing technologies on a strategic level. For companies, it is essential to consider both additive and conventional manufacturing beyond pure unit costs. It is necessary to achieve an integrative view of manufacturing that incorporates both additive and conventional manufacturing resources and quantifies their potential with regard to flexibility and manufacturing complexity. This also requires a structured process for the strategic production systems design that spans the design of various scenarios and allows for multi-dimensional and comparative analysis. A respective guideline for the planning of additive resources on a strategic level is being laid out in this paper.

Keywords: additive manufacturing, production system design, flexibility enhancement, strategic guideline

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Authors: Umar D. M., Aminu A. M., Izaddeen K. Y.

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Deployments of mini macrocell base stations also referred to as femtocells, improve the quality of service of indoor and outdoor users. Nevertheless, mobility management remains a key issue with regards to their deployment. This paper is leaned towards this issue, with an in-depth focus on the most important aspect of mobility management -handover. In handover management, making a handover decision in the LTE two-tier macrocell femtocell network is a crucial research area. Decision algorithms in this research are classified and comparatively analyzed according to received signal strength, user equipment speed, cost function, and interference. However, it was observed that most of the discussed decision algorithms fail to consider cell selection with hybrid access policy in a single macrocell multiple femtocell scenario, another observation was a majority of these algorithms lack the incorporation of user equipment residence parameter. Not including this parameter boosts the number of unnecessary handover occurrence. To deal with these issues, a sophisticated handover decision algorithm is proposed. The proposed algorithm considers the user’s velocity, received signal strength, residence time, as well as the femtocell base station’s access policy. Simulation results have shown that the proposed algorithm reduces the number of unnecessary handovers when compared to conventional received signal strength-based handover decision algorithm.

Keywords: user-equipment, radio signal service, long term evolution, mobility management, handoff

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Authors: Edoba Bright Omoregie

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Nigeria became a federation in 1954 six years before it gained independence away from British colonial rule. The country has remained a federation since then despite the challenging circumstances of military rule and civil strife which have tasked its federal credentials. Since 1961, when it first decided a federalism dispute, cases over vertical and horizontal powers have inundated the country’s Supreme Court. In its current practice of federalism after democratic rule was resumed in 1999, the country has witnessed a spell of intergovernmental disputes over a good number of federalism issues. Such conflicts have eventually found their way to the Supreme Court for resolution, not as a final appellate court (which it is in other non-federal matters) but as a court of first and final instance following the constitutional provision granting the court such power. However, in April 2014 one of such disputes was denied hearing by the court when it declined original jurisdiction to determine the matter. The suit was instituted by one state of the federation against the federal government and the other 35 states challenging the collection of value added tax (a consumption tax)on certain goods and services within the state. The paper appraises the rationale of the court’s decision and reason that its decision to decline jurisdiction is the result of an avoidable misunderstanding of the dual sovereignty instituted by the federal system of Nigeria as well as a misconception of the role which the court is constitutionally assigned to play in resolving intergovernmental schisms in the federal system.

Keywords: dual sovereignty, federalism, intergovernmental conflict, Supreme Court

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Authors: Hamna Hamid, Kashmala Zaman

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The aim of this study was to evaluate the relationship between self-efficacy, resilience, and social support among clinical psychologists, counselors, and teachers of special schools. The study also assesses the gender differences in self-efficacy, resilience, social support, and vicarious trauma and also vicarious trauma differences among three professions, i.e., clinical psychologists, counselors, and teachers of special schools. A sample of 150 women and 97 men were handed out a set questionnaire to complete: a General Self-Efficacy Scale, Brief Resilience Scale, Multidimensional Scale of Perceived Social Support, and Vicarious Trauma Scale. Results showed that there is a significant negative correlation between self-efficacy, resilience, and vicarious trauma. Women experience higher levels of vicarious trauma as compared to men. At the same time, clinical psychologists and counselors experience higher levels of vicarious trauma as compared to teachers of special schools. The moderation effect of social support is not significant towards resilience and vicarious trauma.

Keywords: self-efficacy, resilience, vicarious-trauma social-support, social support

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Authors: Rania Ajmi, Faiza Allouche Khebour, Aude Nuscia Taibi, Sirine Essasi

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Urban green spaces (UGS) as an important contributor can be a significant part of sustainable development. A spatial method was employed to assess and map the spatial distribution of UGS in five districts in Sousse, Tunisia. Ecological management of UGS is an essential factor for the sustainable development of the city; hence the municipality of Sousse has decided to support the districts according to different green spaces characters. And to implement this policy, (1) a new GIS web application was developed, (2) then the implementation of the various green spaces was carried out, (3) a spatial mapping of UGS using Quantum GIS was realized, and (4) finally a data processing and statistical analysis with RStudio programming language was executed. The intersection of the results of the spatial and statistical analyzes highlighted the presence of an imbalance in terms of the spatial UGS distribution in the study area. The discontinuity between the coast and the city's green spaces was not designed in a spirit of network and connection, hence the lack of a greenway that connects these spaces to the city. Finally, this GIS support will be used to assess and monitor green spaces in the city of Sousse by decision-makers and will contribute to improve the well-being of the local population.

Keywords: distributions, GIS, green space, imbalance, spatial analysis

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Authors: Rosy Chaudhary, Pushpa Parajuli

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Background and Objectives: Informational support to family members has a significant potential for reducing this distress related to hospitalization of their patient into the critical care unit, enabling them to cope better and support the patient. The objective of the study is to assess family members’ perception of informational support, anxiety, satisfaction with care and to reveal the association with selected socio-demographic variables and to investigate the correlation between informational support, anxiety and satisfaction with care. Materials and Methods: A descriptive cross-sectional study was conducted in 39 family caregivers of patients admitted in critical care unit of BPKIHS(B.P. Koirala Institute of Health Sciences). Consecutive sampling technique was used wherein data was collected over duration of one month using interview schedule. Descriptive and inferential statistics were used. Results: The mean age of the respondents was 34.97 ± 10.64 and two third (66.70%) were male. Mean score for informational support was 25.72(SD = 5.66; theoretical range of 10 - 40). Mean anxiety was 10.41 (SD = 5.02; theoretical range of 7 - 21). Mean score for satisfaction with care was 40.77 (SD = 6.77; theoretical range of 14 - 64). A moderate positive correlation was found between informational support and satisfaction with care (r = 0.551, p < .001) and a moderate negative correlation was found between anxiety and satisfaction with care (r = -0.590; p = 0.000). No relationship was noted between informational support and anxiety. Conclusion: The informational support and satisfaction of the family caregivers with the care provided to their patients was satisfactory. More than three fourth of the family caregivers had anxiety; the factors associated being educational status of the caregivers, the family income and duration of visiting hours. There was positive correlation between informational support and satisfaction with care provided justifying the need for comprehensive information to the family caregivers by the health personnel. There was negative correlation between anxiety and satisfaction with care.

Keywords: anxiety, caregivers, critical care unit, informational support, family

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Authors: Parya Tabei, Maryam Habibifar

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Decision-making is an important cognitive function that can be defined as the process of choosing an option among available options to achieve a specific goal. Consumer ‘need’ is the main reason for purchasing decisions. Human decision-making while buying products online is subject to various factors, one of which is the quality and effect of advertising photos. Advertising photo editing can have a significant impact on people's virtual purchase decisions. This technique helps improve the quality and overall appearance of photos by adjusting various aspects such as brightness, contrast, colors, cropping, resizing, and adding filters. This study, by examining the effect of editing advertising photos on the virtual purchase decision using EEG data, tries to investigate the effect of edited images on the decision-making of customers. A group of 30 participants were asked to react to 24 edited and unedited images while their EEG was recorded. Analysis of the EEG data revealed increased alpha wave activity in the occipital regions (O1, O2) for both edited and unedited images, which is related to visual processing and attention. Additionally, there was an increase in beta wave activity in the frontal regions (FP1, FP2, F4, F8) when participants viewed edited images, suggesting involvement in cognitive processes such as decision-making and evaluating advertising content. Gamma wave activity also increased in various regions, especially the frontal and parietal regions, which are associated with higher cognitive functions, such as attention, memory, and perception, when viewing the edited images. While the visual processing reflected by alpha waves remained consistent across different visual conditions, editing advertising photos appeared to boost neural activity in frontal and parietal regions associated with decision-making processes. These Findings suggest that photo editing could potentially influence consumer perceptions during virtual shopping experiences by modulating brain activity related to product assessment and purchase decisions.

Keywords: virtual purchase decision, advertising photo, EEG parameters, decision Making

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Authors: Ayelet Siman-Tov, Shlomo Kaniel

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Objectives: The research validates a multivariate model that predicts parental adjustment to coping successfully with an autistic child. The model comprises four elements: parental stress, parental resources, parental adjustment and the child's autism symptoms. Background and aims: The purpose of the current study is the construction and validation of a model for the adjustment of parents and a child with autism. The suggested model is based on theoretical views on stress and links personal resources, stress, perception, parental mental health and quality of marriage and child adjustment with autism. The family stress approach focuses on the family as a system made up of a dynamic interaction between its members, who constitute interdependent parts of the system, and thus, a change in one family member brings about changes in the processes of the entire family system. From this perspective, a rise of new demands in the family and stress in the role of one family member affects the family system as a whole. Materials and methods: 176 parents of children aged between 6 to 16 diagnosed with ASD answered several questionnaires measuring parental stress, personal resources (sense of coherence, locus of control, social support), adjustment (mental health and marriage quality) and the child's autism symptoms. Results: Path analysis showed that a sense of coherence, internal locus of control, social support and quality of marriage increase the ability to cope with the stress of parenting an autistic child. Directions for further research are suggested.

Keywords: stress, adjustment, resources, Autism, parents, coherence

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Authors: A. Uludağ, F. G. Tufekci, N. Ceviz

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Aim: The research has been carried out in order to evaluate caregiver burden, life satisfaction and received social support level of the parents whose children have congenital heart disease; to examine the relationship between the social supports received by them and caregiver burden and life satisfaction. Material and Method: The research which is descriptive and which is searching a relationship has been carried out between the dates June 7, 2012- June 30, 2014, in Erzurum Ataturk University Research and Application Hospital, Department of Pediatrics and Children Cardiology Polyclinic. In the research, it was collaborated with the parents (N = 157) who accepted to participate in, of children who were between the ages of 3 months- 12 years. While gathering the data, a questionnaire, Zarit Caregiver Burden, Life Satisfaction and Social Support Scales have been used. The statistics of the data acquired has been produced by using percentage distribution, mean, and variance and correlation analysis. Ethical principles are followed in the research. Results: In the research, caregiver burden, life satisfaction and social support level received from family (p < 0.05), have been determined higher in the parents whose children have serious congenital heart disease than that of parents whose children have slight disease and social support received from friends has been found lower. It has been determined that there is a strong relation (p < 0.001) through negative direction between both social support levels and caregiver burden of parents; and that there is a strong relation (p < 0.001) through positive direction between both support levels and life satisfaction. Conclusion: That Social Support is in a strong relation with Caregiver Burden through a negative direction and a strong relation with Life Satisfaction through positive direction in parents of all the children who have congenital heart disease requires social support systems to be reinforced. Parents can be led or guided so as to prompt social support systems more.

Keywords: congenital heart disease, child, parents, caregiver burden, life satisfaction, social support

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Authors: Julia Brudzinski, Ashley Croswell, Jade Mardin, Hannah Shilling, Jennifer Berg-Carnegie

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Adults with brain injuries and mental illnesses commonly experience cognitive impairments that interfere with their participation in activities of daily living (ADLs). Prior research states that electronic reminder systems can support adults with cognitive impairments; however, previous studies focus primarily on one-way reminder systems. Research on adults with chronic diseases reported that two-way reminder systems yield better health outcomes and disease self-management compared to one-way reminder systems. Literature was identified through systematically searching 7 databases and hand-searching relevant reference lists. Retrieved studies were independently screened and reviewed by at least two members of the research team. Data was extracted on study design, participant characteristics, intervention details, study objectives, outcome measures, and important results. 574 articles were screened and reviewed. Nine articles met all inclusion criteria and were included. The literature focused on three main areas: system feasibility (n=8), stakeholder satisfaction (n=6), and efficacy of the two-way reminder systems (n=6). Participants in eight of the studies had brain injuries, with participants in only one study having a mental illness (i.e., schizophrenia). Two-way reminder systems were used to support participation in a wide range of ADLs. The current literature on two-way reminder systems to support ADLs for adults with cognitive impairments focuses on feasibility, stakeholder satisfaction, and system efficacy. Future research should focus on addressing the barriers to accessing and implementing two-way reminder systems and identifying specific client characteristics that would benefit most from using these systems.

Keywords: brain injury, digital health, occupational therapy, activities of daily living, two-way reminder systems

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Authors: Fidelia A. Orji, Julita Vassileva

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This research aims to develop machine learning models for students' academic performance and study strategy prediction, which could be generalized to all courses in higher education. Key learning attributes (intrinsic, extrinsic, autonomy, relatedness, competence, and self-esteem) used in building the models are chosen based on prior studies, which revealed that the attributes are essential in students’ learning process. Previous studies revealed the individual effects of each of these attributes on students’ learning progress. However, few studies have investigated the combined effect of the attributes in predicting student study strategy and academic performance to reduce the dropout rate. To bridge this gap, we used Scikit-learn in python to build five machine learning models (Decision Tree, K-Nearest Neighbour, Random Forest, Linear/Logistic Regression, and Support Vector Machine) for both regression and classification tasks to perform our analysis. The models were trained, evaluated, and tested for accuracy using 924 university dentistry students' data collected by Chilean authors through quantitative research design. A comparative analysis of the models revealed that the tree-based models such as the random forest (with prediction accuracy of 94.9%) and decision tree show the best results compared to the linear, support vector, and k-nearest neighbours. The models built in this research can be used in predicting student performance and study strategy so that appropriate interventions could be implemented to improve student learning progress. Thus, incorporating strategies that could improve diverse student learning attributes in the design of online educational systems may increase the likelihood of students continuing with their learning tasks as required. Moreover, the results show that the attributes could be modelled together and used to adapt/personalize the learning process.

Keywords: classification models, learning strategy, predictive modeling, regression models, student academic performance, student motivation, supervised machine learning

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Authors: K. C. Ching

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There is growing public concern over the increasing prevalence of student suicide in Hong Kong. Some identify the problem with insufficient social support, while some attribute it to the vast fluctuations in emotional experience and the hindrances to emotion-regulation, both typical of adolescence and emerging adulthood. This study is thus designed to explore the respective effect of perceived social support and emotion self-confidence, on positive emotions and negative emotions. Fifty-seven Hong Kong higher-education students (17 males, 40 females) aged between 18 and 25 (M = 21.78) responded to an online questionnaire consisted of self-reported measures of perceived social support, emotional self-confidence, positive emotions, and negative emotions. Hierarchical regression analysis revealed that emotional self-confidence positively associated with positive emotions and negatively with negative emotions, while perceived social support positively associated with positive emotions but was not related to negative emotions. Perceived social support and emotional self-confidence both predicted positive emotions, but did not interact to predict any emotional outcome. It is concluded that students’ positive and negative emotional experiences are closely related to their emotion-regulation process. But for social support, its effect is merely protective, meaning that although perceived social support generally promotes positive emotions, it alone does not suffice to alleviate students’ negative emotions. These conclusions carry profound implications to suicide prevention practices, including that most existing suicide prevention campaigns should advance from merely fostering mutual support to directly promoting adaptive coping of emotional negativity.

Keywords: emerging adulthood, emotional self-confidence, hong kong, perceived social support, suicide prevention

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Authors: Ashwin Belle, Bryce Benson, Mark Salamango, Fadi Islim, Rodney Daniels, Kevin Ward

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A reliable, real-time, and non-invasive system that can identify patients at risk for hemodynamic instability is needed to aid clinicians in their efforts to anticipate patient deterioration and initiate early interventions. The purpose of this pilot study was to explore the clinical capabilities of a real-time analytic from a single lead of an electrocardiograph to correctly distinguish between rapid response team (RRT) activations due to hemodynamic (H-RRT) and non-hemodynamic (NH-RRT) causes, as well as predict H-RRT cases with actionable lead times. The study consisted of a single center, retrospective cohort of 21 patients with RRT activations from step-down and telemetry units. Through electronic health record review and blinded to the analytic’s output, each patient was categorized by clinicians into H-RRT and NH-RRT cases. The analytic output and the categorization were compared. The prediction lead time prior to the RRT call was calculated. The analytic correctly distinguished between H-RRT and NH-RRT cases with 100% accuracy, demonstrating 100% positive and negative predictive values, and 100% sensitivity and specificity. In H-RRT cases, the analytic detected hemodynamic deterioration with a median lead time of 9.5 hours prior to the RRT call (range 14 minutes to 52 hours). The study demonstrates that an electrocardiogram (ECG) based analytic has the potential for providing clinical decision and monitoring support for caregivers to identify at risk patients within a clinically relevant timeframe allowing for increased vigilance and early interventional support to reduce the chances of continued patient deterioration.

Keywords: critical care, early warning systems, emergency medicine, heart rate variability, hemodynamic instability, rapid response team

Procedia PDF Downloads 134