Search results for: memory making

Authors: Musarrat Jabeen

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Thoughtful intelligence offers a sustainable position to enhance the influence of decision-makers. Thoughtful Intelligence implies the understanding to realize the impact of one’s thoughts, words and actions on the survival, dignity and development of the individuals, groups and nations. Thoughtful intelligence has received minimal consideration in the area of Decision Support Systems, with an end goal to evaluate the quantity of knowledge and its viability. This pattern degraded the imbibed contribution of thoughtful intelligence required for sustainable decision making. Given the concern, this paper concentrates on the question: How to present a model of Thoughtful Decision Support System (TDSS)? The aim of this paper is to appreciate the concepts of thoughtful intelligence and insinuate a Decision Support System based on thoughtful intelligence. Thoughtful intelligence includes three dynamic competencies: i) Realization about long term impacts of decisions that are made in a specific time and space, ii) A great sense of taking actions, iii) Intense interconnectivity with people and nature and; seven associate competencies, of Righteousness, Purposefulness, Understanding, Contemplation, Sincerity, Mindfulness, and Nurturing. The study utilizes two methods: Focused group discussion to count prevailing Decision Support Systems; 70% results of focus group discussions found six decision support systems and the positive inexistence of thoughtful intelligence among decision support systems regarding sustainable decision making. Delphi focused on defining thoughtful intelligence to model (TDSS). 65% results helped to conceptualize (definition and description) of thoughtful intelligence. TDSS is offered here as an addition in the decision making literature. The clients are top leaders.

Keywords: thoughtful intelligence, sustainable decision making, thoughtful decision support system

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Authors: Saad Saeed Althiabi

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There is great progress in formulating and executing legislative policies in GCC, however, the public participation in formulating and in major decision making still remains weak. Drawing attention on the international law of public participation in construction and natural resource management, this paper aims in creating a feasible legislative framework for extensive public participation in the industries such as construction and oil and gas decision-making that GCC can implement. This paper would address the conflicts associated with the management and creation of legislation and ensuring public participation for the creation of a practical framework. A feasible legislative framework must take into account the various factors that shape the effectiveness of participation and the elements that promote the objectives of participation. It is premised on the ground that viewing to international prescriptions might help to reveal gaps in domestic laws, as well as alternatives to overcome them.

Keywords: legislative policies, public participation, planning legislation, GCC countries, international law

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Authors: Aditya, Ganapati Joshi, Vinod Kumar

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IN THE MODERN-WARFARE ERA, THE PRIME REQUIREMENT IS A HIGH SPEED AND MACH NUMBER. WHEN THE MISSILES STRIKE IN THE HYPERSONIC REGIME THE OPPONENT CAN DETECT IT WITH THE ANTI-DEFENSE SYSTEM BUT CAN NOT STOP IT FROM CAUSING DAMAGE. SO, TO ACHIEVE THE SPEEDS OF THIS LEVEL THERE ARE TWO ENGINES THAT ARE AVAILABLE WHICH CAN WORK IN THIS REGION ARE RAMJET AND SCRAMJET. THE PROBLEM WITH RAMJET STARTS TO OCCUR WHEN MACH NUMBER EXCEEDS 4 AS THE STATIC PRESSURE AT THE INLET BECOMES EQUAL TO THE EXIT PRESSURE. SO, SCRAMJET ENGINE DEALS WITH THIS PROBLEM AS IT NEARLY HAS THE SAME WORKING BUT HERE THE FLOW IS NOT MUCH SLOWED DOWN AS COMPARED TO RAMJET IN THE DIFFUSER BUT IT SUFFERS FROM THE PROBLEMS SUCH AS INLET BUZZ, THERMAL CHOCKING, MIXING OF FUEL AND OXIDIZER, THERMAL HEATING, AND MANY MORE. HERE THE NEW ENGINE IS DEVELOPED ON THE SAME PRINCIPLE AS THE SCRAMJET ENGINE BUT BURNING HAPPENS DUE TO DETONATION INSTEAD OF DEFLAGRATION. THE PROBLEM WITH THE ENGINE STARTS WHEN THE MACH NUMBER BECOMES VARIABLE AND THE INLET GEOMETRY IS FIXED AND THIS LEADS TO INLET SPILLAGE WHICH WILL AFFECT THE THRUST ADVERSELY. SO, HERE ADAPTIVE INLET IS MADE OF SHAPE MEMORY ALLOYS WHICH WILL ENHANCE THE INLET MASS FLOW RATE AS WELL AS THRUST.

Keywords: detonation, ramjet engine, shape memory alloy, ignition delay, shock-boundary layer interaction, eddy dissipation, asymmetric nozzle

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Authors: A. Van Staden, A. Tolmie, E. Vorster

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Research confirms the multifaceted nature of spelling development and underscores the importance of both cognitive and linguistic skills that affect sound spelling development such as working and long-term memory, phonological and orthographic awareness, mental orthographic images, semantic knowledge and morphological awareness. This has clear implications for many South African English second language spellers (L2) who attempt to become proficient spellers. Since English has an opaque orthography, with irregular spelling patterns and insufficient sound/grapheme correspondences, L2 spellers can neither rely, nor draw on the phonological awareness skills of their first language (for example Sesotho and many other African languages), to assist them to spell the majority of English words. Epistemologically, this research is informed by social constructivism. In addition the researchers also hypothesized that the principles of the Overlapping Waves Theory was an appropriate lens through which to investigate whether L2 spellers could significantly improve their spelling skills via the implementation of an alternative route to spelling development, namely the orthographic route, and more specifically via the application of visual imagery. Post-test results confirmed the results of previous research that argues for the interactive nature of different cognitive and linguistic systems such as working memory and its subsystems and long-term memory, as learners were systematically guided to store visual orthographic images of words in their long-term lexicons. Moreover, the results have shown that L2 spellers in the experimental group (n = 9) significantly outperformed L2 spellers (n = 9) in the control group whose intervention involved phonological awareness (and coding) including the teaching of spelling rules. Consequently, L2 learners in the experimental group significantly improved in all the post-test measures included in this investigation, namely the four sub-tests of short-term memory; as well as two spelling measures (i.e. diagnostic and standardized measures). Against this background, the findings of this study look promising and have shown that, within a social-constructivist learning environment, learners can be systematically guided to apply higher-order thinking processes such as visual imagery to successfully store and retrieve mental images of spelling words from their output lexicons. Moreover, results from the present study could play an important role in directing research into this under-researched aspect of L2 literacy development within the South African education context.

Keywords: English second language spellers, phonological and orthographic coding, social constructivism, visual imagery as spelling strategy

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Authors: Rolla Monib, Chris Ian Goodier, Alistair Gibb

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This paper aims to investigate decision support strategies in the EC sector to determine the most appropriate degree of modularization. This is achieved through three oil and gas (O&G) and two power plant case studies via semi-structured interviews (n=59 and n=27, respectively), analysis of project documents, and case study-specific semi-structured validation interviews (n=12 and n=8). New terminology to distinguish degrees of modularization is proposed, along with a decision-making support checklist and a diagrammatic decision-making support figure. Results indicate that the EC sub-sectors were substantially more satisfied with the application of component, structural, or traditional modularization compared with system modularization for some types of modules. Key drivers for decisions on the degree of modularization vary across module types. This paper can help the EC sector determine the most suitable degree of modularization via a decision-making support strategy.

Keywords: modularization, engineering construction, case study, decision support

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Authors: Insiya Bhalloo

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It is quite common in the Muslim faith for non-Arabic speakers to be able to convert written Arabic, especially Quranic Arabic, into a phonological code without significant semantic or syntactic knowledge. This is due to prior experience learning to read the Quran (a religious text written in Classical Arabic), from a very young age such as via enrolment in Quranic Arabic classes. As compared to native speakers of Arabic, these Arabic readers do not have a comprehensive morpho-syntactic knowledge of the Arabic language, nor can understand, or engage in Arabic conversation. The study seeks to investigate whether mere phonological experience (as indicated by the Arabic readers’ experience with Arabic phonology and the sound-system) is sufficient to cause phonological-interference during word recognition of previously-heard words, despite the participants’ non-native status. Both native speakers of Arabic and non-native speakers of Arabic, i.e., those individuals that learned to read the Quran from a young age, will be recruited. Each experimental session will include two phases: An exposure phase and a test phase. During the exposure phase, participants will be presented with Arabic words (n=40) on a computer screen. Half of these words will be common words found in the Quran while the other half will be words commonly found in Modern Standard Arabic (MSA) but either non-existent or prevalent at a significantly lower frequency within the Quran. During the test phase, participants will then be presented with both familiar (n = 20; i.e., those words presented during the exposure phase) and novel Arabic words (n = 20; i.e., words not presented during the exposure phase. ½ of these presented words will be common Quranic Arabic words and the other ½ will be common MSA words but not Quranic words. Moreover, ½ the Quranic Arabic and MSA words presented will be comprised of nouns, while ½ the Quranic Arabic and MSA will be comprised of verbs, thereby eliminating word-processing issues affected by lexical category. Participants will then determine if they had seen that word during the exposure phase. This study seeks to investigate whether long-term phonological memory, such as via childhood exposure to Quranic Arabic orthography, has a differential effect on the word-recognition capacities of native Arabic speakers and Arabic readers; we seek to compare the effects of long-term phonological memory in comparison to short-term phonological exposure (as indicated by the presentation of familiar words from the exposure phase). The researcher’s hypothesis is that, despite the lack of lexical knowledge, early experience with converting written Quranic Arabic text into a phonological code will help participants recall the familiar Quranic words that appeared during the exposure phase more accurately than those that were not presented during the exposure phase. Moreover, it is anticipated that the non-native Arabic readers will also report more false alarms to the unfamiliar Quranic words, due to early childhood phonological exposure to Quranic Arabic script - thereby causing false phonological facilitatory effects.

Keywords: modern standard arabic, phonological facilitation, phonological memory, Quranic arabic, word recognition

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Authors: Christina Zourna, Ioanna Papavassiliou-Alexiou

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The purpose of this multi-phased action research PhD study in Greece was to investigate if and how Drama in Education (DiE) – used as an innovative group counselling method – may have positive effects on secondary education students’career self-efficacy and career decision-making skills development. Using both quantitative and qualitative research tools, high quality data were gathered at various stages of the research and were analysed through multivariate methods and open-source computer aided data analysis software such as R Studio, QualCoder, and SPSS packages. After a five-month-long educational intervention based on DiE method, it was found that 9th, 10th, and 11th gradersameliorated their self-efficacy and learned the process of making an informed career decision – through targeted information gathering about themselves and possible study paths – thus, developing career problem-solving and career management skills. Gender differences were non statistically important, while differences in grades showed a minor influence on some of the measured factorssuch as general career indecisiveness and self-evaluation. Students in the 11th grade scored significantly higher than younger students in the career self-efficacy scale and have stronger faith in their abilities e.g., choosing general over vocational school and major study orientation. The study has shown that DiE can be effective in group career guidance, especially concerning the pillars of self-awareness, self-efficacy, and career decision-making processes.

Keywords: career decision-making skills, career self-efficacy, CDDQ scale, CDMSE-SF scale, drama in education method

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Authors: Jacqueline Rose T. Alipo-on, Francesca Isabelle F. Escobar, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar Al Dahoul

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Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases, which are considered one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis of ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heartbeat types. The dataset used in this work is the synthetic MIT-BIH Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: heartbeat classification, convolutional neural network, electrocardiogram signals, generative adversarial networks, long short-term memory, ResNet-50

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Authors: Laura V. Gonzalez, Juan B. Duarte, Luis A. Palacio

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Decision making can be conditioned by factors such as the environments, circumstances, behavioral biases, emotions, beliefs and preferences of the participants. The objective of this paper is to analyze the effect ‘amount of information’ and ‘number of options’, on the behavior of competitors under a bilateral negotiation context. For the above, it has been designed an experiment as a classroom game where they negotiate goods, under the condition that none of the players knows exactly the real value of the asset. The game is designed under the concept of zero-sum (non-cooperative game) and focuses on the fact that agents must anticipate the strategies of their opponent to improve their chances of winning in the negotiation. The empirical results show that, contrary to the traditional view of expected utility theory, players prefer to obtain low profits and losses, when faced with a higher expectation of losses, using sub-optimal strategies not in accordance with game theory.

Keywords: bilateral negotiation, classroom game, decision making, game theory

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Authors: Evangelia-Chrysanthi Kouklari, Evdokia Tagkouli, Vassiliki Ntre, Artemios Pehlivanidis, Stella Tsermentseli, Gerasimos Kolaitis, Katerina Papanikolaou

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Executive Function (EF) is a set of goal-directed cognitive skills essentially needed in problem-solving and social behavior. Developmental EF research has indicated that EF emerges early in life and marks dramatic changes before the age of 5. Research evidence has suggested that it may continue to develop up to adolescence as well, following the development of the prefrontal cortex. Over the last decade, research evidence has suggested distinguished domains of cool and hot EF, but traditionally the development of EF in Autism Spectrum Disorder (ASD) has been examined mainly with tasks that address the “cool” cognitive aspects of EF. Thus, very little is known about the development of “hot” affective EF processes and whether the cross-sectional developmental pathways of cool and hot EF present similarities in ASD. Cool EF has also been proven to have a strong correlation with Theory of Mind (ToM) in young and middle childhood in typical development and in ASD, but information about the relationship of hot EF to ToM skills is minimal. The present study’s objective was to explore the age-related changes of cool and hot EF in ASD participants from middle childhood to adolescence, as well as their relationship to ToM. This study employed an approach of cross-sectional developmental trajectories to investigate patterns of cool and hot EF relative to chronological age within ASD. Eighty-two participants between 7 and 16 years of age were recruited to undertake measures that assessed cool EF (working memory, cognitive flexibility, planning & inhibition), hot EF (affective decision making & delay discounting) and ToM (false belief and mental state/emotion recognition). Results demonstrated that trajectories of all cool EF presented age-related changes in ASD (improvements with age). With regards to hot EF, affective decision-making presented age-related changes, but for delay discounting, there were no statistically significant changes found across younger and older ASD participants. ToM was correlated only to cool EF. Theoretical implications are discussed as the investigation of the cross-sectional developmental trajectories of the broader EF (cool and hot domains) may contribute to better defining cognitive phenotypes in ASD. These findings highlight the need to examine developmental trajectories of both hot and cool EF in research and clinical practice as they may aid in enhancing diagnosis or better-informed intervention programs.

Keywords: autism spectrum disorder, developmental trajectories, executive function, theory of mind

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Authors: Serhat Tuzun, Tufan Demirel

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Multi-Criteria Decision Making (MCDM) is the modelling of real-life to solve problems we encounter. It is a discipline that aids decision makers who are faced with conflicting alternatives to make an optimal decision. MCDM problems can be classified into two main categories: Multi-Attribute Decision Making (MADM) and Multi-Objective Decision Making (MODM), based on the different purposes and different data types. Although various MADM techniques were developed for the problems encountered, their methodology is limited in modelling real-life. Moreover, objective results are hard to obtain, and the findings are generally derived from subjective data. Although, new and modified techniques are developed by presenting new approaches such as fuzzy logic; comprehensive techniques, even though they are better in modelling real-life, could not find a place in real world applications for being hard to apply due to its complex structure. These constraints restrict the development of MADM. This study aims to conduct a comprehensive analysis of preference methods in MADM and propose an approach based on information. For this purpose, a detailed literature review has been conducted, current approaches with their advantages and disadvantages have been analyzed. Then, the approach has been introduced. In this approach, performance values of the criteria are calculated in two steps: first by determining the distribution of each attribute and standardizing them, then calculating the information of each attribute as informational energy.

Keywords: literature review, multi-attribute decision making, operations research, preference method, informational energy

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Authors: Omar Mayyas

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Clinical decision-making (CDM) is essential to community health nursing (CHN) education. For this reason, nursing educators are responsible for developing these skills among nursing students because nursing students are exposed to highly critical conditions after graduation. However, due to limited exposure to real-world situations, many nursing students need help developing clinical decision-making skills in this area. Therefore, the impact of Virtual Simulation (VS) on community health nursing students' clinical decision-making in nursing education has to be investigated. This study aims to examine the difference in CDM ability among CHN students who received traditional education compared to those who received VS classes, to identify the factors that may influence CDM ability differences between CHN students who received a traditional education and VS classes, and to provide recommendations for educational programs that can enhance the CDM ability of CHN students and improve the quality of care provided in community settings. A mixed-method study will conduct. A randomized controlled trial will compare the CDM ability of CHN students who received 1hr traditional class with another group who received 1hr VS scenario about diabetic patient nursing care. Sixty-four students in each group will randomly select to be exposed to the intervention from undergraduate nursing students who completed the CHN course at York University. The participants will receive the same Clinical Decision Making in Nursing Scale (CDMNS) questionnaire. The study intervention will follow the Medical Research Council (MRC) approach. SPSS and content analysis will use for data analysis.

Keywords: clinical decision-making, virtual simulation, community health nursing students, community health nursing education

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Authors: Junjie Zhong, Kai Hong, Lei Wang

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Passage Retrieval (PR) plays an important role in many Natural Language Processing (NLP) tasks. Traditional efficient retrieval models relying on exact term-matching, such as TF-IDF or BM25, have nowadays been exceeded by pre-trained language models which match by semantics. Though they gain effectiveness, deep language models often require large memory as well as time cost. To tackle the trade-off between efficiency and effectiveness in PR, this paper proposes Graph Passage Retriever (GraphPR), a graph-based model inspired by the development of graph learning techniques. Different from existing works, GraphPR is end-to-end and integrates both term-matching information and semantics. GraphPR constructs a passage-level graph from BM25 retrieval results and trains a GCN-like model on the graph with graph-based objectives. Passages were regarded as nodes in the constructed graph and were embedded in dense vectors. PR can then be implemented using embeddings and a fast vector-similarity search. Experiments on a variety of real-world retrieval datasets show that the proposed model outperforms related models in several evaluation metrics (e.g., mean reciprocal rank, accuracy, F1-scores) while maintaining a relatively low query latency and memory usage.

Keywords: efficiency, effectiveness, graph learning, language model, passage retrieval, term-matching model

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Authors: K. Biswas, U. H. Armin, S. M. J. Prodhan, J. A. Prithul, S. Sarker, F. Afrin

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Alzheimer’s disease (AD) (a progressive neurodegenerative disorder) is mostly predominant cause of dementia in the elderly. Prolonging the function of acetylcholine by inhibiting both acetylcholinesterase and butyrylcholinesterase is most effective treatment therapy of AD. Traditionally Pterocarpus santalinus L. is widely known for its medicinal use. In this study, in vitro acetylcholinesterase inhibitory activity was investigated and methanolic extract of the plant showed significant activity. To confirm this activity (in vivo), learning and memory enhancing effects were tested in mice. For the test, memory impairment was induced by scopolamine (cholinergic muscarinic receptor antagonist). Anti-amnesic effect of the extract was investigated by the passive avoidance task in mice. The study also includes brain acetylcholinesterase activity. Results proved that scopolamine induced cognitive dysfunction was significantly decreased by administration of the extract solution, in the passive avoidance task and inhibited brain acetylcholinesterase activity. These results suggest that bark extract of Pterocarpus santalinus can be better option for further studies on AD via their acetylcholinesterase inhibitory actions.

Keywords: Pterocarpus santalinus, cholinesterase inhibitor, passive avoidance, Alzheimer’s disease

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Authors: Khaled Asfour

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Going for LEED certification is the latest concern in Egyptian practice that only materialized during the last 4 years. Egyptian Consultant Group (ECG) together with Credit Agricole had the vision to design a headquarters (Cairo) that delivers a serious sustainable design. The bank is a strong advocator of “green banking” and supports renewable energy and energy saving projects. Their HQ in Cairo has passed all the hurdles to become the first platinum LEED certificate holder in Egypt. With this design Egyptian practice has finally re-engaged in a serious way with its long-standing traditions in sustainable architecture. Perhaps the closest to our memory is the medieval houses of Cairo. Few centuries later these qualities disappeared with the advent of Modern Movement that focused more on standard modernist image making than real localized quality of living environments. The first person to note this disappearance was Hassan Fathy half a century ago. Despite international applaud for his efforts he had no effect on prevailing local practice that continued senselessly adopting recycled modernist templates. The Egyptian society was not ready to accept any reference to historic architecture. Disciples of Hassan Fathy, few decades later sought, of tackling the lack of interest in green architecture in a different way. Mohamed Awad introduced in his design sustainable ideals inspired from traditional architecture rather than recycling directly historic forms and images. Despite success, this approach did not go far enough to influence the prevailing practice. Since year 2000 Egyptian economy was ebbing and flowing dramatically. This staggering fluctuation coupled by energy crisis has disillusioned architects and clients on the issue of modern image making. No more shining architecture under the sun with high running cost of fossil fuel. They sought of adopting contemporary green measures that offer pleasant living while saving on energy. A revival is on its way but is very slow and timid. The paper will present this problem of reviving sustainable architecture. How this process can be accelerated in order to give stronger impact on current practice will be addressed through the works of Mario Cucinella and Norman Foster.

Keywords: LEED certification, Hasan Fathy, Medieval architecture, Mario Cucinella, Norman Foster

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Authors: Zainurrasyid Abdullah, Mohamed Fadzlee Sulaiman, Muhammad Fadzlan Zainal, M. Zabri Adil Talib, Aswami Fadillah M. Ariffin

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The Onion Router (Tor) browser is a well-known tool and widely used by people who seeking for web anonymity when browsing the internet. Criminals are taking this advantage to be anonymous over the internet. Accessing the dark web could be the significant reason for the criminal in order for them to perform illegal activities while maintaining their anonymity. For a digital forensic analyst, it is crucial to extract the trail of evidence in proving that the criminal’s computer has used Tor browser to conduct such illegal activities. By applying the digital forensic methodology, several techniques could be performed including application analysis, memory analysis, and registry analysis. Since Windows 10 is the latest operating system released by Microsoft Corporation, this study will use Windows 10 as the operating system platform that running Tor browser. From the analysis, significant artifacts left by Tor browser were discovered such as the execution date, application installation date and browsing history that can be used as an evidence. Although Tor browser was designed to achieved anonymity, there is still some trail of evidence can be found in Windows 10 platform that can be useful for investigation.

Keywords: artifacts analysis, digital forensics, forensic analysis, memory analysis, registry analysis, tor browser, Windows 10

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Authors: Mohammad Ahangari

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Schizophrenia is a psychiatric disorder with symptoms that include cognitive deficits and nicotine has been suggested to have an effect on cognition. In recent years, the advents of Genome-Wide Association Studies(GWAS) has evolved our understanding about the genetic causes of complex disorders such as schizophrenia and studying the role of genome-wide significant genes could potentially lead to the development of new therapeutic agents for treatment of cognitive deficits in schizophrenia. The current study identified six Single Nucleotide Polymorphisms (SNP) from schizophrenia and smoking GWAS that are located on or in close proximity to the nicotinic receptor gene cluster (CHRN) and studied their association with cognition in an Irish sample of 1297 cases and controls using linear regression analysis. Further on, the interaction between CHRN gene cluster and Dopamine receptor D2 gene (DRD2) during working memory was investigated. The effect of these polymorphisms on nicotinic and dopaminergic neurotransmission, which is disrupted in schizophrenia, have been characterized in terms of their effects on memory, attention, social cognition and IQ as measured by a neuropsychological test battery and significant effects in two polymorphisms were found across global IQ domain of the test battery.

Keywords: cognition, dopamine, GWAS, nicotine, schizophrenia, SNPs

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Authors: Szilvia Halmos

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Hungary was one of the first countries to sign and ratify the UN Convention on the Rights of Persons with Disabilities (hereinafter: CRPD). Consequently, Hungary assumed an obligation under international law to review the national law in the light of the Article 12 of the CRPD requiring the States parties to guarantee the equality of persons with disabilities in terms of legal capacity, and to replace the regimes of substitute decision-making by the instruments of supported decision-making. This article is often characterized as one of the key norms of the CRPD, since the legal autonomy of the persons with disabilities is an essential precondition of their participation in the social life on an equal basis with others, envisaged by the social paradigm of disability. This paper examines the impact of the CRPD on the relevant Hungarian national legal norms, with special focus on the relevant rules of the recently codified Civil Code. The employed research methodologies include (1) the specification of the implementation requirements imposed by the Article 12 of the CRPD, (2) the determination of the indicators of the appropriate implementation, (3) the critical analysis of compliance of the relevant Hungarian legal regulation with the indicators, (4) with respect to the relevant case law of the Hungarian Constitutional Court and ordinary courts, the European Court of Human Rights and the Committee of Rights of Persons with Disabilities and (5) to the available empirical figures on the functioning of substitute and supported decision-making regimes. It will be established that the new Civil Code has made large steps toward the equality of persons with disabilities in terms of legal capacity and the support model of decision-making by the introduction of some specific instruments of supported decision-making and the restriction of the application of guardianship. Nevertheless, the regulation currently in effect fails to represent some crucial principles of the Article 12 of the CRPD, such as the non-discrimination of persons with psycho-social disabilities, the support of the articulation of the will and preferences of the individual instead of his/her best interest in the course of decision-making. The changes in the practice of the substitute and the support model brought about by the new legal norms can also be assessed as significant, however, so far unsatisfactory. The number of registered supporters is rather low, and the preconditions of the effective functioning of the support (e.g. the proper training of the supporters) are not ensured.

Keywords: Article 12 of the UN CRPD, Hungarian law on legal capacity, persons with intellectual and psycho-social disabilities, supported decision-making

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Authors: Sanjal Gavande, Thomas Mazzuchi, Shahram Sarkani

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In a complex aerospace operational environment, identifying failures in a procedure involving multiple human-machine interactions are difficult. These failures could lead to accidents causing loss of hardware or human life. The likelihood of failure further increases if operational procedures are tested for a novel system with multiple human-machine interfaces and with no prior performance data. The existing approach in the literature of reviewing complex operational tasks in a flowchart or tabular form doesn’t provide any insight into potential system failures due to human decision-making ability. To address these challenges, this research explores an agent-based simulation approach for reliability assessment and fault detection in complex human-machine systems while utilizing a human decision-making model. The simulation will predict the emergent behavior of the system due to the interaction between humans and their decision-making capability with the varying states of the machine and vice-versa. Overall system reliability will be evaluated based on a defined set of success-criteria conditions and the number of recorded failures over an assigned limit of Monte Carlo runs. The study also aims at identifying high-likelihood failure locations for the system. The research concludes that system reliability and failures can be effectively calculated when individual human and machine agent states are clearly defined. This research is limited to the operations phase of a system lifecycle process in an aerospace environment only. Further exploration of the proposed agent-based and human decision-making model will be required to allow for a greater understanding of this topic for application outside of the operations domain.

Keywords: agent-based model, complex human-machine system, human decision-making model, system reliability assessment

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Authors: Norhayati Ayob, Shamsu Mohamad

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This paper aims to provide an initial background of the process of making traditional ceramic pottery, focusing on the materials and the influence of culture heritage. Ceramic pottery is one of the hallmarks of Sabah’s heirloom, not only use as cooking and storage containers but also closely linked with folk cultures and heritage. The Bajau Laut ethnic community of Semporna or better known as the Sea Gypsies, mostly are boat dwellers and work as fishermen in the coast. This ethnic community is famous for their own artistic traditional heirloom, especially the traditional hand-made clay stove called Lapohan. It is found that in the daily life of Bajau Laut community, Lapohan (clay stove) is used to prepare the meal and as a food warmer while they are at the sea. Besides, Lapohan pottery conveys symbolic meaning of natural objects, which portrays the identity, and values of Bajau Laut community. It is acknowledged that the basic process of making potterywares was much the same for people all across the world, nevertheless, it is crucial to consider that different ethnic groups may have their own styles and choices of raw materials. Furthermore, it is still unknown why and how the Bajau Laut ethnic of Semporna get started making their own pottery and to survive until today by heavily depending on the raw materials available in Semporna. In addition, the emergent problem faced by the pottery maker in Sabah is the absence of young successor to continue the heirloom legacy. Therefore, this research aims to explore the traditional pottery making in Sabah, by investigating the background history of Lapohan pottery and to propose the classification of Lapohan based on design and motifs of traditional pottery that will be recognised throughout the study. It is postulated that different techniques and forms of making traditional pottery may produce different types of pottery in terms of surface decoration, shape, and size that portrays different cultures. This study will be conducted at Selakan Island, Semporna, which is the only location that still has Lapohan making. This study is also based on the chronological process of making pottery and taboos of the process of preparing the clay, forming, decoration technique, motif application and firing techniques. The relevant information for the study will be gathered from field study, including observation, in-depth interview and video recording. In-depth interviews will be conducted with several potters and the conversation and pottery making process will be recorded in order to understand the actual process of making Lapohan. The findings hope to provide several types of Lapohan based on different designs and cultures, for example, the one with flat-shape design or has round-shape on the top of clay stove will be labeled with suitable name based on their culture. In conclusion, it is hoped that this study will contribute to conservation for traditional pottery making in Sabah as well as to preserve their culture and heirloom for future generations.

Keywords: Bajau Laut, culture, Lapohan, traditional pottery

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Authors: Lokes Parvatha Kumaran S., Sakthi Jay Mahenthar C., Sathyaprakash P., Jayakumar V., Shobanadevi A.

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With the evolution of technology, the need to solve complex computational problems like machine learning and deep learning has shot up. But even the most powerful classical supercomputers find it difficult to execute these tasks. With the recent development of quantum computing, researchers and tech-giants strive for new quantum circuits for machine learning tasks, as present works on Quantum Machine Learning (QML) ensure less memory consumption and reduced model parameters. But it is strenuous to simulate classical deep learning models on existing quantum computing platforms due to the inflexibility of deep quantum circuits. As a consequence, it is essential to design viable quantum algorithms for QML for noisy intermediate-scale quantum (NISQ) devices. The proposed work aims to explore Variational Quantum Circuits (VQC) for Deep Reinforcement Learning by remodeling the experience replay and target network into a representation of VQC. In addition, to reduce the number of model parameters, quantum information encoding schemes are used to achieve better results than the classical neural networks. VQCs are employed to approximate the deep Q-value function for decision-making and policy-selection reinforcement learning with experience replay and the target network.

Keywords: quantum computing, quantum machine learning, variational quantum circuit, deep reinforcement learning, quantum information encoding scheme

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Authors: Boussoualim Nacira, Aklouf Youcef

Abstract:

Software as a Service (SaaS) is a software delivery paradigm in which the product is not installed on-premise, but it is available on Internet and Web. The customers do not pay to possess the software itself but rather to use it. This concept of pay per use is very attractive. Hence, we see increasing number of organizations adopting SaaS. However, each customer is unique, which leads to a very large variation in the requirements off the software. As several suppliers propose SaaS products, the choice of this latter becomes a major issue. When multiple criteria are involved in decision making, we talk about a problem of «Multi-Criteria Decision-Making» (MCDM). Therefore, this paper presents a method to help customers to choose a better SaaS product satisfying most of their conditions and alternatives. Also, we know that a good method of adaptive selection should be based on the correct definition of the different parameters of choice. This is why we started by extraction and analysis the various parameters involved in the process of the selection of a SaaS application.

Keywords: cloud computing, business operation, Multi-Criteria Decision-Making (MCDM), Software as a Service (SaaS)

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Authors: Michael T. Miller, G. David Gearhart

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Shared governance is an important element in higher education decision making. Through the joint decision making process, faculty members are provided an opportunity to help shape the future of an institution while increasing support for decisions that are made. Presidents, those leaders who are legally bound to guide their institutions, must find ways to collaborate effectively with faculty members in making decisions, and the first step in this process is understanding when and how presidents and faculty leaders interact. In the current study, a national sample of college presidents reported their preparation for the presidency, their perceptions of the functions of a faculty senate, and ultimately, the locations for important interactions between presidents and faculty senates. Results indicated that presidents, regardless of their preparation, found official functions to be the most important for communicating, although, those presidents with academic backgrounds were more likely to perceive faculty senates as having a role in all aspects of an institutions management.

Keywords: college faculty, college president, faculty senate, leadership

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Authors: Giovanni Cicceri, Roberta Maisano, Nathalie Morey, Salvatore Distefano

Abstract:

The main goal of this paper is to present a solution for a water purification system based on an Environmental Internet of Things (EIoT) platform to monitor and control water quality and machine learning (ML) models to support decision making and speed up the processes of purification of water. A real case study has been implemented by deploying an EIoT platform and a network of devices, called Gramb meters and belonging to the Gramb project, on wastewater purification systems located in Calabria, south of Italy. The data thus collected are used to control the wastewater quality, detect anomalies and predict the behaviour of the purification system. To this extent, three different statistical and machine learning models have been adopted and thus compared: Autoregressive Integrated Moving Average (ARIMA), Long Short Term Memory (LSTM) autoencoder, and Facebook Prophet (FP). The results demonstrated that the ML solution (LSTM) out-perform classical statistical approaches (ARIMA, FP), in terms of both accuracy, efficiency and effectiveness in monitoring and controlling the wastewater purification processes.

Keywords: environmental internet of things, EIoT, machine learning, anomaly detection, environment monitoring

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Authors: Tejinder Singh

Abstract:

Information system is the flow of data from different levels to different directions for decision making and data operations in information system (IS). Data can be violated by different manner like manual or technical errors, data tampering or loss of integrity. Security system called firewall of IS is effected by such type of violations. The flow of data among various levels of Information System is done by networking system. The flow of data on network is in form of packets or frames. To protect these packets from unauthorized access, virus attacks, and to maintain the integrity level, network security is an important factor. To protect the data to get pirated, various security techniques are used. This paper represents the various security techniques and signifies different harmful attacks with the help of detailed data analysis. This paper will be beneficial for the organizations to make the system more secure, effective, and beneficial for future decisions making.

Keywords: information systems, data integrity, TCP/IP network, vulnerability, decision, data

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Authors: Jan Franciszek Jacko

Abstract:

This investigation presents the principle of methodological rationality of decision making and discusses the impact of an organisation's members' methodologically rational or irrational decisions on its security. This study formulates and partially justifies some research hypotheses regarding the impact. The thinking experiment is used according to Max Weber's ideal types method. Two idealised situations("models") are compared: Model A, whereall decision-makers follow methodologically rational decision-making procedures. Model B, in which these agents follow methodologically irrational decision-making practices. Analysing and comparing the two models will allow the formulation of some research hypotheses regarding the impact of methodologically rational and irrational attitudes of members of an organisation on its security. In addition to the method, phenomenological analyses of rationality and irrationality are applied.

Keywords: methodological rationality, rational decisions, security of organisations, philosophy of economics

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Authors: Emanuel Koseos

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Data-Driven Decision Making (DDDM) refers to making decisions that are based on historical data in order to inform practice, develop strategies and implement policies that benefit organizational settings. In educational technology, DDDM facilitates the implementation of differential educational learning approaches such as Educational Data Mining (EDM) and Competency-Based Education (CBE), which commonly target university classrooms. There is a current need for DDDM models applied to middle and secondary schools from a concern for assessing the needs, progress and performance of students and educators with respect to regional standards, policies and evolution of curriculums. To address these concerns, we propose a DDDM reference model developed using educational key process initiatives as inputs to a machine learning framework implemented with statistical software (SAS, R) to provide a best-practices, complex-free and automated approach for educators at their regional level. We assessed the efficiency of the model over a six-year period using data from 45 schools and grades K-12 in the Langley, BC, Canada regional school district. We concluded that the model has wider appeal, such as business learning systems.

Keywords: competency-based learning, data-driven decision making, machine learning, secondary schools

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Authors: Pailin Klinkesorn

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The research aimed to study the use of learning strategies for Japanese language among college students with different learning achievements who study Japanese as a foreign language in the Higher Education’s level. The survey was conducted by using a questionnaire adapted from Strategy Inventory for language Learning or SILL (Oxford, 1990), consisting of two parts: questions about personal data and questions about the use of learning strategies for Japanese language. The samples of college students in the Japanese language program were purposively selected from Suansunandha Rajabhat University. The data from the questionnaire was statistically analyzed by using mean scores and one-way ANOVA. The results showed that Social Strategies was used by the greatest number of college students, whereas Memory Strategies was used by the least number of students. The students in different levels used various strategies, including Memory Strategies, Cognitive Strategies, Metacognitive Strategies and Social Strategies, at the significance level of 0.05. In addition, the students with different learning achievements also used different strategies at the significance level of 0.05. Further studies can explore learning strategies of other groups of Japanese learners, such as university students or company employees. Moreover, learning strategies for language skills, including listening, speaking, reading and writing, can be analyzed for better understanding of learners’ characteristics and for teaching applications.

Keywords: language learning strategies, achievement, Japanese, college students

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Authors: Lulu Wang, Yongjun Xu, Xiaoyang Qiao

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The Forbidden City is well known for being full of Chinese cultural and historical relics. However, the Masters in the Forbidden City, a documentary film, doesn’t just dwell on the stories of the past. Instead, it focuses on ordinary people—the restorers of the relics and antiquities, which has caught the sight of Chinese audiences. From this popular documentary film, a new way can be considered, that is to show the relics, antiquities and painting with a character of modern humanities by films and TV programs. Of course, it can’t just like a simple explanation from tour guides in museums. It should be a perfect combination of scenes, heritages, stories, storytellers and background music. All we want to do is trying to dig up the humanity behind the heritages and then create a virtual scene for the audience to have emotional resonance from the humanity. It is believed that there are two problems. One is that compared with the entertainment shows, why people prefer to see the boring restoration work. The other is that what the interaction is between those history documentary films, the heritages, the audiences and collective memory. This paper mainly used the methods of text analysis and data analysis. The audiences’ comment texts were collected from all kinds of popular video sites. Through analyzing those texts, there was a word cloud chart about people preferring to use what kind of words to comment the film. Then the usage rate of all comments words was calculated. After that, there was a Radar Chart to show the rank results. Eventually, each of them was given an emotional value classification according their comment tone and content. Based on the above analysis results, an interaction model among the audience, history films/TV programs and the collective memory can be summarized. According to the word cloud chart, people prefer to use such words to comment, including moving, history, love, family, celebrity, tone... From those emotional words, we can see Chinese audience felt so proud and shared the sense of Collective Identity, so they leave such comments: To our great motherland! Chinese traditional culture is really profound! It is found that in the construction of collective memory symbology, the films formed an imaginary system by organizing a ‘personalized audience’. The audience is not just a recipient of information, but a participant of the documentary films and a cooperator of collective memory. At the same time, it is believed that the traditional background music, the spectacular present scenes and the tone of the storytellers/hosts are also important, so it is suggested that the museums could try to cooperate with the producers of movie and TV program to create a vivid scene for the people. Maybe it’s a more artistic way for heritages to be open to all the world.

Keywords: audience, heritages, history movies, TV programs

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Authors: Abeba Nigussie Turi, Xiangming Samuel Li

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Data-driven business models are more typical for established businesses than early-stage startups that strive to penetrate a market. This paper provided an extensive discussion on the principles of data analytics for early-stage digital entrepreneurial businesses. Here, we developed data-driven decision-making (DDDM) framework that applies to startups prone to multifaceted barriers in the form of poor data access, technical and financial constraints, to state some. The startup DDDM framework proposed in this paper is novel in its form encompassing startup data analytics enablers and metrics aligning with startups' business models ranging from customer-centric product development to servitization which is the future of modern digital entrepreneurship.

Keywords: startup data analytics, data-driven decision-making, data acquisition, data generation, digital entrepreneurship

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