Search results for: spiritual intelligence

Authors: Husni Mohd Radzi, Lilie Zahara Ramly, Sapora Sipon, Salhah Abdullah

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Malaysia have been experiencing series of huge floods all around the country for the past decades despide planned development done by local authorities. The floods incurred due to factors like natural climate change or man-made disaster. Floods have caused a lot of damages, destructions and losses in term of infrastructure, financial implications and physical health. However, other damaging aspect was not being given much attention are the psychological need of the flood victim. The traumatic impact from the natural disaster like floods may cause serious psychological and spiritual deterioration. Many flood relief shelters in the past did not provide counseling services for flood victims to consult, and as a result, it contributes to added stress among the flood victims, as the issue were not being addressed. Some studies indicates that flood victims did not look for counseling service being offered. A total of 257 flood victim was involved in this study. Main area of the study was Kg Bukit Changgang, Kg. Rancangan Tanah Belia, Kg. Labohan Dagang and Kg.Olak Lempit in Kuala Langat, Selangor. The flood victims have responded to the survey given and the data was analyze using SPSS for descriptive information and other measures. At least 13 victims were reported to have experienced moderate to severe level of stress and anxiety over the flood disaster incidents and a total of 88 respondents admitted to have at least thought and consider getting counseling service.

Keywords: perception, acceptance towards counseling, counseling service for flood victim, disaster

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Authors: Ghassan Kbar, Shady Aly, Ibrahim Alsharawy, Akshay Bhatia, Nur Alhasan, Ronaldo Enriquez

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The Smart Help for persons with disability (PWD) is a part of the project SMARTDISABLE which aims to develop relevant solution for PWD that target to provide an adequate workplace environment for them. It would support PWD needs smartly through smart help to allow them access to relevant information and communicate with other effectively and flexibly, and smart editor that assist them in their daily work. It will assist PWD in knowledge processing and creation as well as being able to be productive at the work place. The technical work of the project involves design of a technological scenario for the Ambient Intelligence (AmI) - based assistive technologies at the workplace consisting of an integrated universal smart solution that suits many different impairment conditions and will be designed to empower the Physically disabled persons (PDP) with the capability to access and effectively utilize the ICTs in order to execute knowledge rich working tasks with minimum efforts and with sufficient comfort level. The proposed technology solution for PWD will support voice recognition along with normal keyboard and mouse to control the smart help and smart editor with dynamic auto display interface that satisfies the requirements for different PWD group. In addition, a smart help will provide intelligent intervention based on the behavior of PWD to guide them and warn them about possible misbehavior. PWD can communicate with others using Voice over IP controlled by voice recognition. Moreover, Auto Emergency Help Response would be supported to assist PWD in case of emergency. This proposed technology solution intended to make PWD very effective at the work environment and flexible using voice to conduct their tasks at the work environment. The proposed solution aims to provide favorable outcomes that assist PWD at the work place, with the opportunity to participate in PWD assistive technology innovation market which is still small and rapidly growing as well as upgrading their quality of life to become similar to the normal people at the workplace. Finally, the proposed smart help solution is applicable in all workplace setting, including offices, manufacturing, hospital, etc.

Keywords: ambient intelligence, ICT, persons with disability PWD, smart application, SHW

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Authors: Sharon Ost Mor, Yuval Palgi, Ddikla Segel-Karpas

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Solitude and positive solitude (PS) are used in literature interchangeably, yet they have different attributes and effects. While solitude might have devastating outcomes such as depression or health deterioration, PS has beneficial outcomes. Yet, both solitude and PS have no clear unanimous definition. Most researches focus on solitude, while the phenomenon of PS is somewhat neglected. Most research deals with young people and adults, while the current research is interested in PS concepts especially in old age. A qualitative study, with 124 participants was performed in order to understand the essence of PS in different age groups. The findings revealed seven categories related to PS, including: Quietness, religious and spiritual experience, escapism, experience in nature or abroad, controlling stress or thoughts, facilitation achievements and recreation-hobbies-routines. Moreover, three meta-themes emerged: PS is a matter of choice, it is meaningful and enjoyable. One stand alone category was found: PS preconditions. Differences between younger and older adults were found in several categories and in PS preconditions, while the meta-themes were equally mentioned by all participants. Based on the participant's reflections and descriptions a new PS paradigm was built and will be presented as well as a new definition of PS. PS was renamed as 'Soulitude' in order to emphasize its' positive nature. Conclusions: PS serves well most people, yet it has different attributes in different ages. By giving PS a unanimous definition and by understanding its' contribution for the elderly, PS might be addressed as a legitimate, stand alone phenomenon. The paradigm might serve theory as well as clinicians for further PS research.

Keywords: old-old, positive solitude, solitude, soulitude

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Authors: Ekrem Aksoy, Nihat Adar, Selçuk Canbek

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Ambient Computing or Ambient Intelligence (AmI) is emerging area in computer science aiming to create intelligently connected environments and Internet of Things. In this paper, we propose communication middleware architecture for AmI. This middleware architecture addresses problems of communication, networking, and abstraction of applications, although there are other aspects (e.g. HCI and Security) within general AmI framework. Within this middleware architecture, any application developer might address HCI and Security issues with extensibility features of this platform.

Keywords: AmI, ambient computing, middleware, distributed-systems, software-defined networking

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Authors: Chukwudi Chidume

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This paper considers the symbolism of kola nut according to Igbo worldview. How kola nut helps to shape the people’s philosophical ideology, especially in relation to religion. The roles of kola nut within the Igbo socio-cultural context and the values attached to these roles will be examined. The roles of kola nut as a means of socialization, education and transmission of cultural values from the preceding to succeeding generations will come under consideration. Equally, this paper looks at the traditional rules regarding not only the uses but more essentially the mode of kola nut presentation, blessing, breaking and sharing of kola nut. How these rules and kola nut have persisted in the face of social and cultural changes which have affected the Igbo people shall be reviewed. The roles played by kola nut in Igbo religion will come under study, which is to correct some of the misconceptions by writers who are motivated by eurocentric idealism but quite oblivious of the Igbo cultural setting and the place of kola nut in it. The onslaught of Western civilization causing the change of attitude among the young generation towards kola nut as a vital aspect of our culture tends to pose a threat to the future and survival of kola nut. Again, the study of Igbo culture as many have done rarely gives an in depth knowledge on the concept, roles and symbolism of kola nut as one of the sacred objects like Ofo and Shrines in Igboland. Mostly it is forgotten that without kola nut, shrines cannot be attended to. Many people think that the spiritual significance and sacramental symbolism are not worth exploring. They, therefore, refuse to try and discover the ritual ramifications, claiming that to probe into the mystery demystifies the matter. Kola nut symbolism is not mysteriously inexplicable. It is a revered symbol of social intercourse with deep social relevance.

Keywords: communion, consecration, Igbo, kola nut, religion

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Authors: Somnath Bhattachryya, Montree Bunruangses, Somchat Sonasang, Preecha Yupapin

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In this study and research on meditation and insight, the design and experiment with electronic circuits to manipulate the meditators' mental circles that call the chakras to have the same size is proposed. The shape of the circuit is 4-ports, called an add-drop multiplexer, that studies the meditation structure called the four-mindfulness foundation, then uses an AC power signal as an input instead of the meditation time function, where various behaviors with the method of re-filtering the signal (successive filtering), like eight noble paths. Start by inputting a signal at a frequency that causes the velocity of the wave on the perimeter of the circuit to cause particles to have the speed of light in a vacuum. The signal changes from electromagnetic waves and matter waves according to the velocity (frequency) until it reaches the point of the relativistic limit. The electromagnetic waves are transformed into photons with properties of wave-particle overcoming the limits of the speed of light. As for the matter wave, it will travel to the other side and cannot pass through the relativistic limit, called a shadow signal (echo) that can have power from increasing speed but cannot create speed faster than light or insight. In the experiment, the only the side where the velocity is positive, only where the speed above light or the corresponding frequency indicates intelligence. Other side(echo) can be done by changing the input signal to the other side of the circuit to get the same result. But there is no intelligence or speed beyond light. It is also used to study the stretching, contraction of time and wormholes that can be applied for teleporting, Bose-Einstein condensate and teleprinting, quantum telephone. The teleporting can happen throughout the system with wave-particle and echo, which is when the speed of the particle is faster than the stretching or contraction of time, the particle will submerge in the wormhole, when the destination and time are determined, will travel through the wormhole. In a wormhole, time can determine in the future and the past. The experimental results using the microstrip circuit have been found to be by the principle of quantum relativity, which can be further developed for both tools and meditation practitioners for quantum technology.

Keywords: quantu meditation, insight picture, quantum circuit, absolute time, teleportation

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Authors: László Schmidt

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Technological and digital innovation is constantly and dynamically evolving, which poses an enormous challenge to both lawmaking and law enforcement. To legislation because artificial intelligence permeates many areas of people’s daily lives that the legislator must regulate. it can see how challenging it is to regulate e.g. self-driving cars/taxis/camions etc. Not to mention cryptocurrencies and Chat GPT, the use of which also requires legislative intervention. Artificial intelligence also poses an extraordinary challenge to law enforcement. In criminal cases, police and prosecutors can make great use of AI in investigations, e.g. in forensics, DNA samples, reconstruction, identification, etc. But it can also be of great help in the detection of crimes committed in cyberspace. In the case of cybercrime, on the one hand, it can be viewed as a new type of crime that can only be committed with the help of information systems, and that has a specific protected legal object, such as an information system or data. On the other hand, it also includes traditional crimes that are much easier to commit with the help of new tools. According to Hungarian Criminal Code section 375 (1), any person who, for unlawful financial gain, introduces data into an information system, or alters or deletes data processed therein, or renders data inaccessible, or otherwise interferes with the functioning of the information system, and thereby causes damage, is guilty of a felony punishable by imprisonment not exceeding three years. The Covid-19 coronavirus epidemic has had a significant impact on our lives and our daily lives. It was no different in the world of crime. With people staying at home for months, schools, restaurants, theatres, cinemas closed, and no travel, criminals have had to change their ways. Criminals were committing crimes online in even greater numbers than before. These crimes were very diverse, ranging from false fundraising, the collection and misuse of personal data, extortion to fraud on various online marketplaces. The most vulnerable age groups (minors and elderly) could be made more aware and prevented from becoming victims of this type of crime through targeted programmes. The aim of the study is to show the Hungarian judicial practice in relation to cybercrime and possible preventive solutions.

Keywords: cybercrime, COVID-19, Hungary, criminal law

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Authors: Suraj Mehrotra

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The stock market is a volatile, bustling marketplace that is a cornerstone of economics. It defines whether companies are successful or in spiral. A thorough understanding of it is important - many companies have whole divisions dedicated to analysis of both their stock and of rivaling companies. Linking the world of finance and artificial intelligence (AI), especially the stock market, has been a relatively recent development. Predicting how stocks will do considering all external factors and previous data has always been a human task. With the help of AI, however, machine learning models can help us make more complete predictions in financial trends. Taking a look at the stock market specifically, predicting the open, closing, high, and low prices for the next day is very hard to do. Machine learning makes this task a lot easier. A model that builds upon itself that takes in external factors as weights can predict trends far into the future. When used effectively, new doors can be opened up in the business and finance world, and companies can make better and more complete decisions. This paper explores the various techniques used in the prediction of stock prices, from traditional statistical methods to deep learning and neural networks based approaches, among other methods. It provides a detailed analysis of the techniques and also explores the challenges in predictive analysis. For the accuracy of the testing set, taking a look at four different models - linear regression, neural network, decision tree, and naïve Bayes - on the different stocks, Apple, Google, Tesla, Amazon, United Healthcare, Exxon Mobil, J.P. Morgan & Chase, and Johnson & Johnson, the naïve Bayes model and linear regression models worked best. For the testing set, the naïve Bayes model had the highest accuracy along with the linear regression model, followed by the neural network model and then the decision tree model. The training set had similar results except for the fact that the decision tree model was perfect with complete accuracy in its predictions, which makes sense. This means that the decision tree model likely overfitted the training set when used for the testing set.

Keywords: machine learning, testing set, artificial intelligence, stock analysis

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Authors: Yanting Cao, Kazumitsu Nawata

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As smartphones upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described as more refined, complex, and detailed. In this context, we analyzed a set of experimental data obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model becomes extremely challenging. After a series of feature selection and parameters adjustment, a well-performed SVM classifier has been trained.

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

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Authors: Yu-Chieh Chen, Kuei-Feng Shen, Chia-Ling Chao

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The purpose of this report was to present the nursing experience and case of an unexpected cerebellar hemorrhagic stroke with acute hydrocephalus patient after lumbar spine surgery. The patient had been suffering from an emergent external ventricular drainage and stayed in the Surgical Intensive Care Unit from July 8, 2016, to July 22, 2016. During the period of the case, the data were collected for attendance, evaluation, observation, interview, searching medical record, etc. An integral evaluation of the patient's physiological 'psychological' social and spiritual states was also noted. The author noticed the following major nursing problems including ineffective cerebral perfusion 'physical activity dysfunction' family resource preparation for disability. The author provided nursing care to maintain normal intracranial pressure, along with a well-therapeutic relationship and applied interdisciplinary medical/nursing team to draft an individualized and appropriate nursing plan for them to face the psychosocial impact of the patient disabilities. We also actively participated in the rehabilitation treatments to improve daily activity and confidence. This was deemed necessary to empower them to a more positive attitude in the future.

Keywords: family resourace preparation inability, hemorrhagic sroke, ineffective tissue cerebral perfusion, lumbar spine surgery

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Authors: Beatriz Delgado

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Although social anxiety is one of the most prevalent disorders in adolescents and causes considerable difficulties and social distress in those with the disorder, to date very few studies have explored the impact of social anxiety on academic adjustment in student populations. The aim of this study was analyze the effect of social anxiety on school functioning in Secondary Education. Specifically, we examined the relationship between social anxiety and self-concept, academic goals, causal attributions, intellectual aptitudes, and learning strategies, personality traits, and academic performance, with the purpose of creating a causal-explanatory model of academic performance. The sample consisted of 2,022 students in the seven to ten grades of Compulsory Secondary Education in Spain (M = 13.18; SD = 1.35; 51.1% boys). We found that: (a) social anxiety has a direct positive effect on internal attributional style, and a direct negative effect on self-concept. Social anxiety also has an indirect negative effect on internal causal attributions; (b) prior performance (first academic trimester) exerts a direct positive effect on intelligence, achievement goals, academic self-concept, and final academic performance (third academic trimester), and a direct negative effect on internal causal attributions. It also has an indirect positive effect on causal attributions (internal and external), learning goals, achievement goals, and study strategies; (c) intelligence has a direct positive effect on learning goals and academic performance (third academic trimester); (d) academic self-concept has a direct positive effect on internal and external attributional style. Also, has an indirect effect on learning goals, achievement goals, and learning strategies; (e) internal attributional style has a direct positive effect on learning strategies and learning goals. Has a positive but indirect effect on achievement goals and learning strategies; (f) external attributional style has a direct negative effect on learning strategies and learning goals and a direct positive effect on internal causal attributions; (g) learning goals have direct positive effect on learning strategies and achievement goals. The structural equation model fit the data well (CFI = .91; RMSEA = .04), explaining 93.8% of the variance in academic performance. Finally, we emphasize that the new causal-explanatory model proposed in the present study represents a significant contribution in that it includes social anxiety as an explanatory variable of cognitive-motivational constructs.

Keywords: academic performance, adolescence, cognitive-motivational variables, social anxiety

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Authors: Mark N. Abello, Betina Velanie L. Cruz, Angelo Joachim D. C. De Castro, Arnel A. Diego, John Ezequel V. Murillo

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Embalmers are widely recognized as someone who mends the cadavers, but behind that is a great deal of work. These professionals are competent in physiology, chemicals, and cosmetics. Another is that such professionals face cadavers day-to-day. Given this background, the researchers intended to find out the lived experience of embalmers. The purpose of the present study is to discover the essence of the work of these professionals, to determine factors that influence their work, the depths of their life and on how the occupation affects upon physical, emotional-mental, spiritual, moral and social aspects. The researchers used the Consensual Qualitative Research, and eight embalmers, seven male and one female, from Manila and Bulacan were interviewed using open-ended questions and were used to triangulate the results. A primary research team conducted the consensus of domains, and an external auditor reviewed the results. A personal data sheet was also used, this helped the researchers group the respondents according to demographic profile. The results of the consensual qualitative research investigation revealed the four core components of the lived experience of embalmers which are motivation, struggles, acceptance, and contentment. The results revealed core components that play an important role in their everyday lives as an embalmer, daily hardships, and source of their pleasures. The present study will help future researchers, embalmers, and society.

Keywords: embalmers, consensual qualitative research, lived experience, embalming

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Authors: Shreya Poddar

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Legal drafting and revising are recognized as highly demanding tasks for legal professionals. This paper introduces an approach to automate and refine these processes through the use of advanced Artificial Intelligence (AI). The method employs Large Language Models (LLMs), with a specific focus on 'Chain of Thoughts' (CoT) and knowledge injection via prompt engineering. This approach differs from conventional methods that depend on comprehensive training or fine-tuning of models with extensive legal knowledge bases, which are often expensive and time-consuming. The proposed method incorporates knowledge injection directly into prompts, thereby enabling the AI to generate more accurate and contextually appropriate legal texts. This approach substantially decreases the necessity for thorough model training while preserving high accuracy and relevance in drafting. Additionally, the concept of guardrails is introduced. These are predefined parameters or rules established within the AI system to ensure that the generated content adheres to legal standards and ethical guidelines. The practical implications of this method for legal work are considerable. It has the potential to markedly lessen the time lawyers allocate to document drafting and revision, freeing them to concentrate on more intricate and strategic facets of legal work. Furthermore, this method makes high-quality legal drafting more accessible, possibly reducing costs and expanding the availability of legal services. This paper will elucidate the methodology, providing specific examples and case studies to demonstrate the effectiveness of 'Chain of Thoughts' and knowledge injection in legal drafting. The potential challenges and limitations of this approach will also be discussed, along with future prospects and enhancements that could further advance legal work. The impact of this research on the legal industry is substantial. The adoption of AI-driven methods by legal professionals can lead to enhanced efficiency, precision, and consistency in legal drafting, thereby altering the landscape of legal work. This research adds to the expanding field of AI in law, introducing a method that could significantly alter the nature of legal drafting and practice.

Keywords: AI-driven legal drafting, legal automation, futureoflegalwork, largelanguagemodels

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Authors: Eduardo Álvarez, Gerardo Quiroga, Jorge Orozco, Gabriel Chavira

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AmI proposes a new way of thinking about computers, which follows the ideas of the Ubiquitous Computing vision of Mark Weiser. In these, there is what is known as a Disappearing Computer Initiative, with users immersed in intelligent environments. Hence, technologies need to be adapted so that they are capable of replacing the traditional inputs to the system by embedding these in every-day artifacts. In this work, we present an approach, which uses Radiofrequency Identification (RFID) and Near Field Communication (NFC) technologies. In the latter, a new form of interaction appears by contact. We compare both technologies by analyzing their requirements and advantages. In addition, we propose using a combination of RFID and NFC.

Keywords: touching interaction, ambient intelligence, ubiquitous computing, interaction, NFC and RFID

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Authors: Tori Reddy Dodla, Laura Ann Jones

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

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

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Authors: Genevieve Jorolan-Quintero

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After the devastation caused by typhoon Haiyan in the southeastern part of the Philippines in 2012, there was this intense need among the indigenous communities to ‘reconcile’ with nature. The belief that the deluge, which claimed thousands of lives, was caused by the destruction of the environment because of humanities’ greed and carelessness was widespread and strong. The rift had to be mended. Nature had to be appeased. For this, the balyan (priestess) was called in to perform a ritual. Only she can communicate with the spirits. The communities depend on her spiritual intervention as she alone has the power to invoke the spirits of nature. Among the indigenous people, the balyan is most often also a magdadawot (bard) who possesses the knowledge especially about the folk epics and the skill to chant them. The balyan is the communities’ repository of knowledge. When one passes away, a whole library of tribal knowledge and wisdom is lost. The oral traditions embody the life values, ideals, customs, and even the history of the First Nations People. These include the myths, epics, legends, riddles, and songs. The indigenous system is patriarchal, but is actually indirectly matriarchal reflecting the authority of the woman. Disputes within the community are heard and tried by the Council of Elders. However, the balyan is often consulted for her opinion. Her advice is deemed significant and most often necessary. These are three instances that highlight the significant role of the balyan among the indigenous communities in the Philippines, especially among the Mandaya tribe who live in the southern region of the country. This paper highlights the unique kind of leadership of the Mandaya woman – as priestess and bard - and her impact on the lives of her people.

Keywords: balyan, bard, magdadawot, mandaya

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Authors: Mona Isazad Mashinchi, Davood Roshan Sangachin, Francis J. Sullivan, Dietrich Rebholz-Schuhmann

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Background: Decision-making processes are nowadays driven by data, data analytics and Business Intelligence (BI). BI as a software platform can provide a wide variety of capabilities such as organization memory, information integration, insight creation and presentation capabilities. Visualizing data through dashboards is one of the BI solutions (for a variety of areas) which helps managers in the decision making processes to expose the most informative information at a glance. In the healthcare domain to date, dashboard presentations are more frequently used to track performance related metrics and less frequently used to monitor those quality parameters which relate directly to patient outcomes. Providing effective and timely care for patients and improving the health outcome are highly dependent on presenting and visualizing data and information. Objective: In this research, the focus is on the presentation capabilities of BI to design a dashboard for prostate cancer (PC) data that allows better decision making for the patients, the hospital and the healthcare system related to a cancer dataset. The aim of this research is to customize a retrospective PC dataset in a dashboard interface to give a better understanding of data in the categories (risk factors, treatment approaches, disease control and side effects) which matter most to patients as well as other stakeholders. By presenting the outcome in the dashboard we address one of the major targets of a value-based health care (VBHC) delivery model which is measuring the value and presenting the outcome to different actors in HC industry (such as patients and doctors) for a better decision making. Method: For visualizing the stored data to users, three interactive dashboards based on the PC dataset have been developed (using the Tableau Software) to provide better views to the risk factors, treatment approaches, and side effects. Results: Many benefits derived from interactive graphs and tables in dashboards which helped to easily visualize and see the patients at risk, better understanding the relationship between patient's status after treatment and their initial status before treatment, or to choose better decision about treatments with fewer side effects regarding patient status and etc. Conclusions: Building a well-designed and informative dashboard is related to three important factors including; the users, goals and the data types. Dashboard's hierarchies, drilling, and graphical features can guide doctors to better navigate through information. The features of the interactive PC dashboard not only let doctors ask specific questions and filter the results based on the key performance indicators (KPI) such as: Gleason Grade, Patient's Age and Status, but may also help patients to better understand different treatment outcomes, such as side effects during the time, and have an active role in their treatment decisions. Currently, we are extending the results to the real-time interactive dashboard that users (either patients and doctors) can easily explore the data by choosing preferred attribute and data to make better near real-time decisions.

Keywords: business intelligence, dashboard, decision making, healthcare, prostate cancer, value-based healthcare

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Authors: Thomai Voulgari, Vasilis Vasilopoulos, Antonis Skamnakis

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The aim of this study is to investigate the effect of the European election campaigns (May 23-26, 2019) on Twitter achieving with artificial intelligence tools such as troll factories and automated inauthentic accounts. Our research focuses on the last European Parliamentary elections that took place between 23 and 26 May 2019 specifically in Italy, Greece, Germany and France. It is difficult to estimate how many Twitter users are actually bots (Echeverría, 2017). Detection for fake accounts is becoming even more complicated as AI bots are made more advanced. A political bot can be programmed to post comments on a Twitter account for a political candidate, target journalists with manipulated content or engage with politicians and artificially increase their impact and popularity. We analyze variables related to 1) the scope of activity of automated bots accounts and 2) degree of coherence and 3) degree of interaction taking into account different factors, such as the type of content of Twitter messages and their intentions, as well as the spreading to the general public. For this purpose, we collected large volumes of Twitter accounts of party leaders and MEP candidates between 10th of May and 26th of July based on content analysis of tweets based on hashtags while using an innovative network analysis tool known as MediaWatch.io (https://mediawatch.io/). According to our findings, one of the highest percentage (64.6%) of automated “bot” accounts during 2019 European election campaigns was in Greece. In general terms, political bots aim to proliferation of misinformation on social media. Targeting voters is a way that it can be achieved contribute to social media manipulation. We found that political parties and individual politicians create and promote purposeful content on Twitter using algorithmic tools. Based on this analysis, online political advertising play an important role to the process of spreading misinformation during elections campaigns. Overall, inauthentic accounts and social media algorithms are being used to manipulate political behavior and public opinion.

Keywords: artificial intelligence tools, human-bot interactions, political manipulation, social networking, troll factories

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Authors: Simone Cinquemani, Lorenzo Mantovani, Aleksander Dabek

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New technologies in agriculture are opening new challenges and new opportunities. Among these, certainly, robotics, vision, and artificial intelligence are the ones that will make a significant leap, compared to traditional agricultural techniques, possible. In particular, the indoor farming sector will be the one that will benefit the most from these solutions. Vertical farming is a new field of research where mechanical engineering can bring knowledge and know-how to transform a highly labor-based business into a fully autonomous system. The aim of the research is to develop a multi-purpose, modular, and perfectly integrated platform for crop production in indoor vertical farming. Activities will be based both on hardware development such as automatic tools to perform different activities on soil and plants, as well as research to introduce an extensive use of monitoring techniques based on machine learning algorithms. This paper presents the preliminary results of a research project of a vertical farm living lab designed to (i) develop and test vertical farming cultivation practices, (ii) introduce a very high degree of mechanization and automation that makes all processes replicable, fully measurable, standardized and automated, (iii) develop a coordinated control and management environment for autonomous multiplatform or tele-operated robots in environments with the aim of carrying out complex tasks in the presence of environmental and cultivation constraints, (iv) integrate AI-based algorithms as decision support system to improve quality production. The coordinated management of multiplatform systems still presents innumerable challenges that require a strongly multidisciplinary approach right from the design, development, and implementation phases. The methodology is based on (i) the development of models capable of describing the dynamics of the various platforms and their interactions, (ii) the integrated design of mechatronic systems able to respond to the needs of the context and to exploit the strength characteristics highlighted by the models, (iii) implementation and experimental tests performed to test the real effectiveness of the systems created, evaluate any weaknesses so as to proceed with a targeted development. To these aims, a fully automated laboratory for growing plants in vertical farming has been developed and tested. The living lab makes extensive use of sensors to determine the overall state of the structure, crops, and systems used. The possibility of having specific measurements for each element involved in the cultivation process makes it possible to evaluate the effects of each variable of interest and allows for the creation of a robust model of the system as a whole. The automation of the laboratory is completed with the use of robots to carry out all the necessary operations, from sowing to handling to harvesting. These systems work synergistically thanks to the knowledge of detailed models developed based on the information collected, which allows for deepening the knowledge of these types of crops and guarantees the possibility of tracing every action performed on each single plant. To this end, artificial intelligence algorithms have been developed to allow synergistic operation of all systems.

Keywords: automation, vertical farming, robot, artificial intelligence, vision, control

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Authors: Ryan Dale B. Elnar

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This study developed a multidimensional need assessment scale for college students called The University of Mindanao Needs Assessment Scale (UMNAS). Although there are context-specific instruments measuring the needs of clinical and non-clinical samples, literature reveals no standardized scales to measure the needs of the college students thus a four-phase item development process was initiated to support its content validity. Comprising seven broad facets namely spiritual-moral, intrapersonal, socio-personal, psycho-emotional, cognitive, physical and sexual, a pyramid model of college needs was deconstructed through FGD sample to support the literature review. Using various construct validity procedures, the model was further tested using a total of 881 Filipino college samples. The result of the study revealed evidences of the reliability and validity of the UMNAS. The reliability indices range from .929-.933. Exploratory and confirmatory factor analyses revealed a one-factor-six-dimensional instrument to measure the needs of the college students. Using multivariate regression analysis, year level and course are found predictors of students’ needs. Content analysis attested the usefulness of the instrument to diagnose students’ personal and academic issues and concerns in conjunction with other measures. The norming process includes 1728 students from the different colleges of the University of Mindanao. Further validation is recommended to establish a national norm for the instrument.

Keywords: needs assessment scale, validity, factor analysis, college students

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Authors: Justin Byrne, Jose Ramon Cobo

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The growing importance of cross- or intercultural competencies (used here interchangeably) for the business and management professionals is now a commonplace in both academic and professional literature. This reflects two parallel developments. On the one hand, it is a consequence of the increased attention paid to a whole range of 'soft skills', now seen as fundamental in both individuals' and corporate success. On the other hand, and more specifically, the increasing demand for interculturally competent professionals is a corollary of ongoing processes of globalization, which multiply and intensify encounters between individuals and companies from different cultural backgrounds. Business schools have, for some decades, responded to the needs of the job market and their own students by providing students with training in intercultural skills, as they are encouraged to do so by the major accreditation agencies on both sides of the Atlantic. Adapting Early and Ang's (2003) formulation of Cultural Intelligence (CQ), this paper aims to help fill the lagunae in the current literature on intercultural training in three main ways. First, it offers an in-depth analysis of the CQ of a little studied group: contemporary Millenial and 'Generation Z' Business School students. The level of analysis distinguishes between the four different dimensions of CQ, cognition, metacognition, motivation and behaviour, and thereby provides a detailed picture of the strengths and weaknesses in CQ of the group as a whole, as well as of different sub-groups and profiles of students. Secondly, by crossing these individual-level findings with respondents' socio-cultural and educational data, this paper also proposes and tests hypotheses regarding the relative impact and importance of four possible antecedents of intercultural skills identified in the literature: prior international experience; intercultural training, foreign language proficiency, and experience of cultural diversity in habitual country of residence. Third, we use this analysis to suggest data-based intercultural training priorities for today's management students. These conclusions are based on the statistical analysis of individual responses of some 300 Bachelor or Masters students in a major European Business School provided to two on-line surveys: Ang, Van Dyne, et al's (2007) standard 20-question self-reporting CQ Scale, and an original questionnaire designed by the authors to collate information on respondent's socio-demographic and educational profile relevant to our four hypotheses and explanatory variables. The data from both instruments was crossed in both descriptive statistical analysis and regression analysis. This research shows that there is no statistically significant and positive relationship between the four antecedents analyzed and overall CQ level. The exception in this respect is the statistically significant correlation between international experience, and the cognitive dimension of CQ. In contrast, the results show that the combination of international experience and foreign language skills acting together, does have a strong overall impact on CQ levels. These results suggest that selecting and/or training students with strong foreign language skills and providing them with international experience (through multinational programmes, academic exchanges or international internships) constitutes one effective way of training culturally intelligent managers of tomorrow.

Keywords: business school, cultural intelligence, millennial, training

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Authors: John Rosswell Cummings III

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This research examines the discourse ancient Maya ritual practice manifest and maintained through language in a contemporary society as led by a daykeeper— a Maya spiritual leader— with the objective of discovering if the Maya Calendar has an influence on worldview. Through an ethnography of communication and discursive analysis framework, this research examines the discourse of and around the Maya calendar through original research. Data collected includes the ceremonial performance of the Tzolkin ritual, a ritual that takes place every 13 days to ceremonially welcome one of the 20 Universal Forces. During the ceremony, participants supplicate, sacrifice, and venerate. This ritual, based off the Tzolkin cycle in the Mayan Calendar, contains strong, culture-binding ideologies. This research performs a close analysis of the 20 energies of the Tzolkin and their glyphs so as to gain a better understanding of current ideologies in Maya communities. Through a linguistic relativity frame of reference, including both the strong and weak versions, the 20 Universal Forces are shown to influence ways of life. This research argues that it is not just the native language, but the discourses native to the community as held through the calendar, influence thought and have the potential to offer an alternate worldview, thus shaping the cultural narrative which in return influences identity of the community. Research of this kind, on calendric systems and linguistic relativity, has the power to make great discoveries about the societies of the world and their worldviews.

Keywords: anthropological linguistics, discourse analysis, cultural studies, sociolinguistics

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Authors: Yoon Suh Song

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Though music education can broaden one’s capacity for mathematical performance, many countries lag behind in music education. Little empirical evidence is found to identify the connection between math and music. Therefore, this research was set out to explore what music-related variables are associated with mathematical performance. The result of our analysis is as follows: A Pearson's Correlation analysis revealed that PISA math score is strongly correlated with students' Intelligence Quotient (IQ). This lays the foundation for further research as to what factors in students’ IQ lead to a better performance in math.

Keywords: music education, mathematical performance, education, IQ

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Authors: Roberto Cabezas H

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The current work shows the methodology developed to create narrative lighting spaces for the multimedia performance piece 'cluster: the vanished paradise.' This empirical research is focused on exploring unconventional roles for machines in subjective creative processes, by delving into the semantics of data and machine intelligence algorithms in hybrid technological, creative contexts to expand epistemic domains trough human-machine cooperation. The creative process in scenic and performing arts is guided mostly by intuition; from that idea, we developed an approach to embed collective intuition in computational creative systems, by joining the properties of Generative Adversarial Networks (GAN’s) and Fuzzy Clustering based on a semi-supervised data creation and analysis pipeline. The model makes use of GAN’s to learn from phenomenological data (data generated from experience with lighting scenography) and algorithmic design data (augmented data by procedural design methods), fuzzy logic clustering is then applied to artificially created data from GAN’s to define narrative transitions built on membership index; this process allowed for the creation of simple and complex spaces with expressive capabilities based on position and light intensity as the parameters to guide the narrative. Hybridization comes not only from the human-machine symbiosis but also on the integration of different techniques for the implementation of the aided design system. Machine intelligence tools as proposed in this work are well suited to redefine collaborative creation by learning to express and expand a conglomerate of ideas and a wide range of opinions for the creation of sensory experiences. We found in GAN’s and Fuzzy Logic an ideal tool to develop new computational models based on interaction, learning, emotion and imagination to expand the traditional algorithmic model of computation.

Keywords: fuzzy clustering, generative adversarial networks, human-machine cooperation, hybrid collective data, multimedia performance

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Authors: Ursula Das, Manavjit Singh Dhindsa, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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Wildland fires, also known as forest fires or wildfires, are exhibiting an alarming surge in frequency in recent times, further adding to its perennial global concern. Forest fires often lead to devastating consequences ranging from loss of healthy forest foliage and wildlife to substantial economic losses and the tragic loss of human lives. Despite the existence of substantial literature on the detection of active forest fires, numerous potential research avenues in forest fire management, such as preventative measures and ancillary effects of forest fires, remain largely underexplored. This paper undertakes a systematic review of these underexplored areas in forest fire research, meticulously categorizing them into distinct phases, namely pre-fire, during-fire, and post-fire stages. The pre-fire phase encompasses the assessment of fire risk, analysis of fuel properties, and other activities aimed at preventing or reducing the risk of forest fires. The during-fire phase includes activities aimed at reducing the impact of active forest fires, such as the detection and localization of active fires, optimization of wildfire suppression methods, and prediction of the behavior of active fires. The post-fire phase involves analyzing the impact of forest fires on various aspects, such as the extent of damage in forest areas, post-fire regeneration of forests, impact on wildlife, economic losses, and health impacts from byproducts produced during burning. A comprehensive understanding of the three stages is imperative for effective forest fire management and mitigation of the impact of forest fires on both ecological systems and human well-being. Artificial intelligence and machine learning (AI/ML) methods have garnered much attention in the cyber-physical systems domain in recent times leading to their adoption in decision-making in diverse applications including disaster management. This paper explores the current state of AI/ML applications for managing the activities in the aforementioned phases of forest fire. While conventional machine learning and deep learning methods have been extensively explored for the prevention, detection, and management of forest fires, a systematic classification of these methods into distinct AI research domains is conspicuously absent. This paper gives a comprehensive overview of the state of forest fire research across more recent and prominent AI/ML disciplines, including big data, classical machine learning, computer vision, explainable AI, generative AI, natural language processing, optimization algorithms, and time series forecasting. By providing a detailed overview of the potential areas of research and identifying the diverse ways AI/ML can be employed in forest fire research, this paper aims to serve as a roadmap for future investigations in this domain.

Keywords: artificial intelligence, computer vision, deep learning, during-fire activities, forest fire management, machine learning, pre-fire activities, post-fire activities

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Authors: Driss Kettani

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ICT4D actors are naturally attempted to include AI in the range of enabling technologies and tools that could support and boost the Development process, and to refer to these as AI4D. But, doing so, assumes that AI complies with the very specific features of ICT4D context, including, among others, affordability, relevance, openness, and ownership. Clearly, none of these is fulfilled, and the enthusiastic posture that AI4D is a natural part of ICT4D is not grounded and, to certain extent, does not serve the purpose of Technology for Development at all. In the context of Development, it is important to emphasize and prioritize ICT4D, in the national digital transformation strategies, instead of borrowing "trendy" waves of the IT Industry that are motivated by business considerations, with no specific care/consideration to Development.

Keywords: AI, ICT4D, technology for development, position paper

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Authors: Karnsunaphat Balthip, Bunrome Suwanphahu

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Purpose in life is one attribute of the concept of spirituality which is used in health promotion to promote holistic wellbeing. Purpose is a significant foundation of motivation and achievement that guides adolescents down positive life paths. Adolescents who have life purpose are more likely to achieve greater success and wellbeing in their lives. The current study used qualitative research methodology to describe the experiences that enhanced the purpose in life of 27 Thai adolescents from different backgrounds, living in urban areas in southern Thailand. Data were gathered through in-depth interviews and observation. Thematic analysis methods guided data analysis. The results showed that love and connectedness are important in enhancing purpose in life. They illustrate four attributes of love and connection reflecting the four attributes of gratitude that enhance purpose in life: (1) self-love, or gratitude to oneself, whereby participants endeavor to live life in a positive way by taking care of themselves based on moral and ethical values; (2) connectedness or gratitude to parents or significant others, whereby participants are committed to taking holistic care (physical, psychological, and spiritual) of their significant others; (3) connectedness or gratitude to peers, whereby participants support their peers to help them live their own lives in a positive way; and (4) connectedness or gratitude to the wider world (environment, society, nation and beyond), through a sense of altruism towards others. The findings provide helpful insights for parents, nurses, and other health professionals supporting adolescents to obtain a purpose in life.

Keywords: adolescent, gratitude, purpose in life, spirituality

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Authors: Dulani Jayasuriya

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This study outlines the developmental steps of a chatbot for administrative purposes of a large undergraduate course. The chatbot is able to handle student queries about administrative details, including assessment deadlines, course documentation, how to navigate the course, group formation, etc. The development window screenshots are that of a free account on the Snatchbot platform such that this can be adopted by the wider public. While only one connection to an answer based on possible keywords is shown here, one needs to develop multiple connections leading to different answers based on different keywords for the actual chatbot to function. The overall flow of the chatbot showing connections between different interactions is depicted at the end.

Keywords: chatbots, education, technology, snatch bot, artificial intelligence

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Authors: Jui-Hung Hung, Ching-Liang Hsieh, Yi-Wen Lin

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Modern medicine highly emphasizes the importance of palliative treatment. The inception of palliative and hospice care recently developed into the concept of caring for the patients’ and families’ physical, psychological and spiritual problems. There are several benefits related to palliative care such as reducing medical expenses, decreasing patients’ suffer, and supporting patient go through the finale of the life. Nowadays, in Taiwan, over 60-70% terminal cancer patients were covered in hospice care, and the coverage rate increased annually. Acupuncture is a well-known therapy used more than thousand years to relieve symptoms of cancer patient. Many reports showed that, even in the Western society, many reputable medical centers can provide Acupuncture therapy for patients. Accordingly, using Acupuncture for cancer patient care is a global trend. There are increased evidences indicate that Acupuncture can relieve the symptoms for cancer patients including pain, reduce the dosage of anesthetic, improve the cancer-related fatigue, relieve the chemotherapy-related nausea and vomiting, ease anxiety mood and even improving the quality of life. Furthermore, some trials show that Acupuncture may help relieve xerostomia, hot flash, sleep disorders, and some GI discomfort and so on. Acupuncture therapy has many advantages for clinical use with effective, low-cost, minimal side effect, suitable for cancer patients and even for elderly population. Especially in nowadays, there are more diversified challenges in modern medicine, all of them will make the higher medical budget. We suggest that Acupuncture will be one of methods for palliative care for cancer patients.

Keywords: Acupuncture, cancer, integrative medicine, palliative care

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Authors: Reham Banwair, Lana Alshehri, Sara Hadrawi

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The purpose of this project is to identify user satisfaction with the AI functions on Snapchat, in order to generate improvement proposals that allow its development within the app. To achieve this, a qualitative analysis was carried out through interviews to people who usually use the application, revealing their satisfaction or dissatisfaction with the usefulness of the AI. In addition, the background of the company and its introduction in these algorithms were analyzed. Furthermore, the characteristics of the three main functions of AI were explained: identify songs, solve mathematical problems, and recognize plants. As a result, it was obtained that 50% still do not know the characteristics of AI, 50% still believe song recognition is not always correct, 41.7% believe that math problems are usually accurate and 91.7% believes the plant detection tool is working properly.

Keywords: artificial intelligence, scanning, Snapchat, machine learning

Procedia PDF Downloads 134