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Authors: Kemal Efe Eseller, Göktuğ Yazici

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Laser-induced breakdown spectroscopy (LIBS) is a rapid optical atomic emission spectroscopy which is used for material identification and analysis with the advantages of in-situ analysis, elimination of intensive sample preparation, and micro-destructive properties for the material to be tested. LIBS delivers short pulses of laser beams onto the material in order to create plasma by excitation of the material to a certain threshold. The plasma characteristics, which consist of wavelength value and intensity amplitude, depends on the material and the experiment’s environment. In the present work, medicine samples’ spectrum profiles were obtained via LIBS. Medicine samples’ datasets include two different concentrations for both paracetamol based medicines, namely Aferin and Parafon. The spectrum data of the samples were preprocessed via filling outliers based on quartiles, smoothing spectra to eliminate noise and normalizing both wavelength and intensity axis. Statistical information was obtained and principal component analysis (PCA) was incorporated to both the preprocessed and raw datasets. The machine learning models were set based on two different train-test splits, which were 70% training – 30% test and 80% training – 20% test. Cross-validation was preferred to protect the models against overfitting; thus the sample amount is small. The machine learning results of preprocessed and raw datasets were subjected to comparison for both splits. This is the first time that all supervised machine learning classification algorithms; consisting of Decision Trees, Discriminant, naïve Bayes, Support Vector Machines (SVM), k-NN(k-Nearest Neighbor) Ensemble Learning and Neural Network algorithms; were incorporated to LIBS data of paracetamol based pharmaceutical samples, and their different concentrations on preprocessed and raw dataset in order to observe the effect of preprocessing.

Keywords: machine learning, laser-induced breakdown spectroscopy, medicines, principal component analysis, preprocessing

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Authors: Gulhan Sen

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Disasters could result in many deaths and injuries. In these difficult times, accessible resources are limited, demand and supply balance is distorted, and there is a need to make urgent interventions. Disproportionateness between accessible resources and intervention capacity makes triage a necessity in every stage of disaster response. Healthcare professionals, who are in charge of triage, have to evaluate swiftly and make ethical decisions about which patients need priority and urgent intervention given the limited available resources. For such critical times in disaster triage, 'doing the greatest good for the greatest number of casualties' is adopted as a code of practice. But there is no guide for healthcare professionals about ethical decision-making during disasters, and this study is expected to use as a source in the preparation of the guide. This study aimed to examine whether the qualities healthcare professionals in Izmir related to disaster triage were adequate and whether these qualities influence their capacity to make ethical decisions. The researcher used a survey developed for data collection. The survey included two parts. In part one, 14 questions solicited information about socio-demographic characteristics and knowledge levels of the respondents on ethical principles of disaster triage and allocation of scarce resources. Part two included four disaster scenarios adopted from existing literature and respondents were asked to make ethical decisions in triage based on the provided scenarios. The survey was completed by 215 healthcare professional working in Emergency-Medical Stations, National Medical Rescue Teams and Search-Rescue-Health Teams in Izmir. The data was analyzed with SPSS software. Chi-Square Test, Mann-Whitney U Test, Kruskal-Wallis Test and Linear Regression Analysis were utilized. According to results, it was determined that 51.2% of the participants had inadequate knowledge level of ethical principles of disaster triage and allocation of scarce resources. It was also found that participants did not tend to make ethical decisions on four disaster scenarios which included ethical dilemmas. They stayed in ethical dilemmas that perform cardio-pulmonary resuscitation, manage limited resources and make decisions to die. Results also showed that participants who had more experience in disaster triage teams, were more likely to make ethical decisions on disaster triage than those with little or no experience in disaster triage teams(p < 0.01). Moreover, as their knowledge level of ethical principles of disaster triage and allocation of scarce resources increased, their tendency to make ethical decisions also increased(p < 0.001). In conclusion, having inadequate knowledge level of ethical principles and being inexperienced affect their ethical decision-making during disasters. So results of this study suggest that more training on disaster triage should be provided on the areas of the pre-impact phase of disaster. In addition, ethical dimension of disaster triage should be included in the syllabi of the ethics classes in the vocational training for healthcare professionals. Drill, simulations, and board exercises can be used to improve ethical decision making abilities of healthcare professionals. Disaster scenarios where ethical dilemmas are faced should be prepared for such applied training programs.

Keywords: disaster triage, medical ethics, ethical principles of disaster triage, ethical decision-making

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Authors: Thifhuriwi Emmanuel Madzunye, Patricia Harpur, Ephias Ruhode

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A review of the pertinent literature identified a gap concerning the hindrances and opportunities accompanying the implementation of real-time online learning systems (RTOLs) in rural areas. Whilst RTOLs present a possible solution to teaching and learning issues in rural areas, little is known about the implementation of digital strategies among schools in isolated communities. This study explores associated guidelines that have the potential to inform decision-making where Internet-based education could improve educational opportunities. A systematic literature review has the potential to consolidate and focus on disparate literature served to collect interlinked data from specific sources in a structured manner. During qualitative data analysis (QDA) of selected publications via the application of a QDA tool - ATLAS.ti, the following overarching themes emerged: digital divide, educational strategy, human factors, and support. Furthermore, findings from data collection and literature review suggest that signiant factors include a lack of digital knowledge, infrastructure shortcomings such as a lack of computers, poor internet connectivity, and handicapped real-time online may limit students’ progress. The study recommends that timeous consideration should be given to the influence of the digital divide. Additionally, the evolution of educational strategy that adopts digital approaches, a focus on training of role-players and stakeholders concerning human factors, and the seeking of governmental funding and support are essential to the implementation and success of RTOLs.

Keywords: communication, digital divide, digital skills, distance, educational strategy, government, ICT, infrastructures, learners, limpopo, lukalo, network, online learning systems, political-unrest, real-time, real-time online learning, real-time online learning system, pass-rate, resources, rural area, school, support, teachers, teaching and learning and training

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Authors: Evonne Kaplan-Liss, Val Lantz-Gefroh

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Arts and humanities are often incorporated into medical education to help deepen understanding of the human condition and the ability to communicate from a place of compassion. However, a gap remains in our knowledge of compassionate communication training for postgraduate medical professionals (as opposed to students and residents); how training opportunities include and impact the artists themselves, and how train-the-trainer models can support learners to become teachers. In this report, the authors present results from a pilot evaluation of the UC San Diego Health: Sanford Compassionate Communication Fellowship, a 60-hour experiential program that uses theater, narrative reflection, poetry, literature, and journalism techniques to train a multidisciplinary cohort of medical professionals and artists in compassionate communication. In the culminating project, fellows design and implement their own projects as teachers of compassionate communication in their respective workplaces. Qualitative methods, including field notes and 30-minute Zoom interviews with each fellow, were used to evaluate the impact of the fellowship. The cohort included both artists (n=2) and physicians representing a range of specialties (n=7), such as occupational medicine, palliative care, and pediatrics. The authors coded the data using thematic analysis for evidence of how the multidisciplinary nature of the fellowship impacted the fellows’ experiences. The findings show that the multidisciplinary cohort contributed to a greater appreciation of compassionate communication in general. Fellows expressed that the ability to witness how those in different fields approached compassionate communication enhanced their learning and helped them see how compassion can be expressed in various contexts, which was both “exhilarating” and “humbling.” One physician expressed that the fellowship has been “really helpful to broaden my perspective on the value of good communication.” Fellows shared how what they learned in the fellowship translated to increased compassionate communication, not only in their professional roles but in their personal lives as well. A second finding was the development of a supportive community. Because each fellow brought their own experiences and expertise, there was a sense of genuine ability to contribute as well as a desire to learn from others. A “brave space” was created by the fellowship facilitators and the inclusion of arts-based activities: a space that invited vulnerability and welcomed fellows to make their own meaning without prescribing any one answer or right way to approach compassionate communication. This brave space contributed to a strong connection among the fellows and reports of increased well-being, as well as multiple collaborations post-fellowship to carry forward compassionate communication training at their places of work. Results show initial evidence of the value of a multidisciplinary fellowship for promoting compassionate communication for both artists and physicians. The next steps include maintaining the supportive fellowship community and collaborations with a post-fellowship affiliate faculty program; scaling up the fellowship with non-physicians (e.g., nurses and physician assistants); and collecting data from family members, colleagues, and patients to understand how the fellowship may be creating a ripple effect outside of the fellowship through fellows’ compassionate communication.

Keywords: compassionate communication, communication in healthcare, multidisciplinary learning, arts in medicine

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Authors: Crystal Shackleford, Michael Pasek, Allon Vishkin, Jeremy Ginges

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In the Middle East, conflict is often viewed as religiously motivated. In this context, an important question is how we think the religion of the other drives their behavior. If people see conflicts as religious, they may expect the belief of the other to motivate intergroup bias. Beliefs about the motivations of the other impact how we engage with them. Conflict may result if actors believe the other’s religion promotes parochialism. To examine how actors on the ground in Israel-Palestine think about the God of the other as it relates to the other’s behavior towards them, we ran two studies in winter 2019 with an online sample of Jewish Israelis and fieldwork with Palestinians in the West Bank. We asked participants to predict the behavior of an outgroup member participating in an economic game task, dividing the money between themselves and another person, who is either an ingroup or outgroup member. Our experimental manipulation asks participants to predict the behavior of the other when the other is thinking of their God. Both Israelis and Palestinians believed outgroup members would show in-group favoritism, and that group members would give more to their in-group when thinking of their God. We also found that participants thought outgroup members would give more to their own ingroup when thinking of God. In other words, Palestinians predicted that Israelis would give more to fellow Israelis when thinking of God, but also more to Palestinians. Our results suggest that religious belief is seen to promote universal moral reasoning, even in a context with over 70 years of intense conflict. More broadly, this challenges the narrative that religion necessarily motivates intractable conflict.

Keywords: conflict, psychology, religion, meta-cognition, morality

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Authors: Elizabeth Howarth, Dawn Green, Sean Connolly, Geena Vabulas, Sara Smolley

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Through the EU Horizon 2020 Nuvoic Project, the project team recruited 70 individuals in the UK and Ireland to test the Voiceitt speech recognition app and provide user feedback to developers. The app is designed for people with dysarthric speech, to support communication with unfamiliar people and access to speech-driven technologies such as smart home equipment and smart assistants. Participants with atypical speech, due to a range of conditions such as cerebral palsy, acquired brain injury, Down syndrome, stroke and hearing impairment, were recruited, primarily through organisations supporting disabled people. Most had physical or learning disabilities in addition to dysarthric speech. The project team worked with individuals, their families and local support teams, to provide access to the app, including through additional assistive technologies where needed. Testing was user-led, with participants asked to identify and test use cases most relevant to their daily lives over a period of three months or more. Ongoing technical support and training were provided remotely and in-person throughout the testing period. Structured interviews were used to collect feedback on users' experiences, with delivery adapted to individuals' needs and preferences. Informal feedback was collected through ongoing contact between participants, their families and support teams and the project team. Focus groups were held to collect feedback on specific design proposals. User feedback shared with developers has led to improvements to the user interface and functionality, including faster voice training, simplified navigation, the introduction of gamification elements and of switch access as an alternative to touchscreen access, with other feature requests from users still in development. This work offers a case-study in successful and inclusive co-design with the disabled community.

Keywords: co-design, assistive technology, dysarthria, inclusive speech recognition

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Authors: D. Kokt, T. F. Dreyer

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The main objective of the study was to design a mentoring programme aimed at developing the soft skills of mentors. The mentors are all employed by a multinational corporation. The company had a mentoring plan in place that did not yield the required results, especially related to the development of soft skills. This prompted the researchers to conduct an extensive literature review followed by a mixed methods approach to ascertain the best practices in developing the soft skills of mentors. The outcomes of the study led to the development of a structured mentoring programme using 25 modules to be completed by mentors. The design incorporated a blended modular approach using both face-to-face teaching and teaching supported by Information Communication Technology (ICT). Blended learning was ideal as the ICT component helped to minimise instructor-mentor physical contact as part of the health measures during the Covid-19 pandemic. The blended learning approach also allowed instructors and mentors an online or offline mode, so that mentors could have more time for creative and cooperative exercises. A range of delivery methodologies were spread out across the different modules to ensure mentor engagement and accelerate mentor development. This included concept development through in-person instructor-led training sessions, concept development through virtual instructor-led training sessions, simulations, case studies, e-learning, role plays, interactive learning using mentoring toolkits, and experiential learning through application. The mentor development journey included formal modular competency assessments. All modules contained post-competency assessment consisting of 10 questions (comprising of a combination of explanatory questions and multiple-choice questions) to ensure understanding and deal with identified competency gaps. The minimum pass mark for all modular competency assessments was 80%. Mentors were allowed to retake the assessment if they scored less than 80% until they demonstrated understanding at the required level.

Keywords: mentor, mentee, soft skills, mentor development, blended learning, modular approach

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Authors: Olga Hernán-Vega, Patricia López-Rodríguez, David Escot-Bocanegra, Raúl Fernández-Recio, Ignacio Bravo

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Non-Cooperative Target Identification has become a key research domain in the Defense industry since it provides the ability to recognize targets at long distance and under any weather condition. High Resolution Range Profiles, one-dimensional radar images where the reflectivity of a target is projected onto the radar line of sight, are widely used for identification of flying targets. According to that, to face this problem, an approach to Non-Cooperative Target Identification based on the exploitation of Singular Value Decomposition to a matrix of range profiles is presented. Target Identification based on one-dimensional radar images compares a collection of profiles of a given target, namely test set, with the profiles included in a pre-loaded database, namely training set. The classification is improved by using Singular Value Decomposition since it allows to model each aircraft as a subspace and to accomplish recognition in a transformed domain where the main features are easier to extract hence, reducing unwanted information such as noise. Singular Value Decomposition permits to define a signal subspace which contain the highest percentage of the energy, and a noise subspace which will be discarded. This way, only the valuable information of each target is used in the recognition process. The identification algorithm is based on finding the target that minimizes the angle between subspaces and takes place in a transformed domain. Two metrics, F1 and F2, based on Singular Value Decomposition are accomplished in the identification process. In the case of F2, the angle is weighted, since the top vectors set the importance in the contribution to the formation of a target signal, on the contrary F1 simply shows the evolution of the unweighted angle. In order to have a wide database or radar signatures and evaluate the performance, range profiles are obtained through numerical simulation of seven civil aircraft at defined trajectories taken from an actual measurement. Taking into account the nature of the datasets, the main drawback of using simulated profiles instead of actual measured profiles is that the former implies an ideal identification scenario, since measured profiles suffer from noise, clutter and other unwanted information and simulated profiles don't. In this case, the test and training samples have similar nature and usually a similar high signal-to-noise ratio, so as to assess the feasibility of the approach, the addition of noise has been considered before the creation of the test set. The identification results applying the unweighted and weighted metrics are analysed for demonstrating which algorithm provides the best robustness against noise in an actual possible scenario. So as to confirm the validity of the methodology, identification experiments of profiles coming from electromagnetic simulations are conducted, revealing promising results. Considering the dissimilarities between the test and training sets when noise is added, the recognition performance has been improved when weighting is applied. Future experiments with larger sets are expected to be conducted with the aim of finally using actual profiles as test sets in a real hostile situation.

Keywords: HRRP, NCTI, simulated/synthetic database, SVD

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Authors: Annika Kjallman Alm, Ove Hellzen, Malin Rising-Homlstrom

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The concept of dementia‐friendly communities focuses on the lived experience of people who have dementia and is most relevant to addressing their needs and the needs of those people who live with and provide support for them. The goal of communities becoming dementia‐friendly is for dementia to be normalized and recognized as a disabling condition. People with dementia find being connected to self, to others, and to the environment by meaningful activities as important. According to the concept underlying dementia-friendly communities, people with dementia or cognitive decline can continue to live in the community if their residential community has sufficiently strong social capital. The aim of this study is to explore staff and leaders’ experiences in implementing interventions to enhance a more inclusive dementia-friendly community. A municipality in northern Sweden with a population of approx. 100 000 inhabitants decided to create a dementia friendly municipality. As part of the initiative, a Centre for support was established. The Centre offered support for both individuals and groups, did home visits, and provided information about Dementia. Interviews were conducted with staff who had undergone training in a structured form of multidimensional support, the PER-model®, and worked at the Centre for support. The staff consisted of registered nurses, occupational therapists, and specialized nurses who had worked there for more than five years, and all had training in dementia. All interviews were audio-recorded and transcribed verbatim. The transcribed data were analyzed using qualitative content analysis. Results suggest that implementing the PER-model® of support for persons in the early stages of dementia and their next of kin added a much-needed form of support and perceived possibilities to enhance daily life in the early stages of dementia. The staff appreciated that the structure of PER-model® was evidenced based. They also realized that they never even considered that the person with dementia also needed support in the early stages but that they now had tools for that as well. Creating a dementia friendly municipality offering different kinds of support for all stages of dementia is a challenge. However, evidence-based tools and a broad spectrum of different types of support, whether individual or group, are needed to tailor to everyone’s needs. A conviction that all citizens are equal and should all be involved in the community is a strong motivator.

Keywords: dementia, dementia-friendly, municipality, support

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Authors: Hussein Lujuo Mohamed

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Introduction: Public health has always been influenced by climate and weather. Changes in climate and climate variability, particularly changes in weather extremes affect the environment that provides people with clean air, food, water, shelter, and security. Tanzania is not an exception to the threats of climate change. The health sector is mostly affected due to emergence and proliferation of infectious diseases, thereby affecting health of the population and thus impacting achievement of sustainable development goals. Methodology: A desk review on documented issues pertaining to climate change and health in Tanzania was done using Google search engine. Keywords included climate change, link, health, climate initiatives. In cases where information was not available, documents from Ministry of Health, Vice Presidents Office-Environment, Local Government Authority, Ministry of Water, WHO, research, and training institutions were reviewed. Some of the reviewed documents from these institutions include policy brief papers, fieldwork activity reports, training manuals, and guidelines. Results: Six main climate resilience activities were identified in Tanzania. These were development and implementation of climate resilient water safety plans guidelines both for rural and urban water authorities, capacity building of rural and urban water authorities on implementation of climate-resilient water safety plans, and capacity strengthening of local environmental health practitioners on mainstreaming climate change and health into comprehensive council health plans. Others were vulnerability and adaptation assessment for the health sector, mainstreaming climate change in the National Health Policy, and development of risk communication strategy on climate. In addition information, education, and communication materials on climate change and to create awareness were developed aiming to sensitize and create awareness among communities on climate change issues and its effect on public health. Conclusion: Proper implementation of these interventions will help the country become resilient to many impacts of climate change in the health sector and become a good example for other least developed countries.

Keywords: climate, change, Tanzania, health

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Authors: York Neudel

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The phenomenon of tourism has been considered as tool to overcome cultural frontiers, to comprehend the other and to cope with mutual mistrust and suspicion. Well, that has been a myth, at least when it comes to mass-tourism. Other approaches, like community-based tourism, still are based on the idea of embracing the other in order to help or to understand the cultural difference. In 1997, two American NGOs incentivized a tourism-project in a community in the highlands of Ecuador, in order to protect the cloud forest from destructive exploitation of its own inhabitants. Nineteen years after that, I analyze in this investigation the interactions between the Ecuadorian hosts in the mestizo-community of Yunguilla and the foreign tourist in the quest for “authentic life” in the Ecuadorian cloud forest. As a sort of “contemporary pilgrim” the traveller tries to find authenticity in other times and places far away from their everyday life in Europe or North America. Therefore, tourists are guided by stereotypes and expectations that are produced by the touristic industry. The host, on the other hand, has to negotiate this pre-established imaginary. That generates a kind of theatre-play with front- and backstage in organic gardens, little fabrics and even private housing, since this alternative project offers to share the private space of the host with the tourist in the setting the community-based tourism. In order to protect their privacy, the community creates new hybrid spaces that oscillate between front- and backstages that culminates in a game of hide and seek – a phenomenon that promises interesting frictions for an anthropological case-study.

Keywords: Tourism, Authenticity, Community-based tourism, Ecuador, Yunguilla

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Authors: Tiron-Tudor Adriana, Ciolomic Ioana, Farcas Teodora

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The mission of a business school is to train students for business careers in which practical skills- based on theoretical knowledge- are needed. These skills include a thorough knowledge of languages, creative skills, and well-founded professional and practical knowledge. With those skills, the graduates are highly competitive in the labour market. The paper objective is to disseminate the results of an international project by revealing how a HEI are prepared for higher vocational training course leading to professional diplomas.

Keywords: vocational education, business schools, international projects, HEI

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Authors: Mihir Halder

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The main aim and objective of the eighteen-month long Diploma in Primary Education (DPED) teacher education training course for in-service primary teachers in Bangladesh is to acquire professional knowledge as well as make them proficient in professional practice. The training, therefore, introduces a variety of theoretical and practical approaches as well as some professional development activities—lesson study being one of them. But, in the field of mathematics teaching, even after implementing the lesson study method, the desired practical teaching skills of the teachers have not been developed. In addition, elementary students also remain quite raw in mathematics. Although there have been various studies to solve the problem, the need for the teachers' views on mathematical ideas has not been taken into consideration. The researcher conducted the research to find out the cause of the discussed problem. In this case, two teams of nine DPED trainee teachers and two instructors conducted two lesson studies in two schools located in the city and town of Khulna Province, Bangladesh. The researcher observed group lesson planning by trainee teachers, followed by a trainee teacher teaching the planned lesson plan to an actual mathematics classroom, and finally, post-teaching reflective discussion in each lesson study. Two DPED instructors acted as mentors in the lesson study. DPED trainee teachers and instructors were asked about mathematical concepts and classroom practices through questionnaires as well as videotaped mathematics classroom teaching. For this study, the DPED mathematics course, curriculum, and assessment activities were analyzed. In addition, the mathematics lesson plans prepared by the trainee teachers for the lesson study and their pre-teaching and post-teaching reflective discussions were analyzed by some analysis categories and rubrics. As a result, it was found that the trainee teachers' views of mathematics are not mature, and therefore, their mathematics teaching practice is not appropriate. Therefore, in order to improve teachers' mathematics teaching, the researcher recommended including some action-oriented aspects in each phase of mathematics lesson study in DPED—for example, emphasizing mathematics concepts of the trainee teachers, preparing appropriate teaching materials, presenting lessons using the problem-solving method, using revised rubrics for assessing mathematics lesson study, etc.

Keywords: mathematics lesson study, knowledge of mathematics, knowledge of teaching mathematics, teachers' views

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Authors: Tamer E. Yared

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The use of driving simulators has made laboratory testing easier. It has been proven to be valid for testing driving ability by many researchers. One benefit of using driving simulators is keeping the human subjects away from traffic hazards, which drivers usually face in a real driving environment while performing a driving experiment. In this study, a driving simulator was developed with a navigation system using a game development software (Unity 3D) and C-sharp codes to measure and evaluate driving performance, safety, and workload for different driving tasks. The driving simulator hardware included a gaming steering wheel and pedals as well as a monitor to view the driving tasks. Moreover, driver distraction was evaluated by utilizing an eye-tracking system working in conjunction with the driving simulator. Twenty subjects were recruited to evaluate driver distraction, workload, driving safety, and performance, as well as provide their feedback about the driving simulator. The subjects’ feedback was obtained by filling a survey after conducting several driving tasks. The main question of that survey was asking the subjects to compare driving on the driving simulator with real driving. Furthermore, other aspects of the driving simulator were evaluated by the subjects in the survey. The survey revealed that the recruited subjects gave an average score of 7.5 out of 10 to the driving simulator when compared to real driving, where the scores ranged between 6 and 8.5. This study is a preliminary effort that opens the door for more improvements to the driving simulator in terms of hardware and software development, which will contribute significantly to driving ability testing.

Keywords: driver distraction, driving performance, driving safety, driving simulator, driving workload, navigation system

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Authors: Pejman Taghibeikzadehbadr

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Background and Aim: PGC-1 alpha is a transcription factor that was first detected in brown adipose tissue. Since its discovery, PGC-1 alpha has been known to facilitate beneficial adaptations such as mitochondrial biogenesis and increased angiogenesis in skeletal muscle following aerobic exercise. Therefore, the purpose of this study was to investigate the expression of PGC-1 alpha isoforms in response to eccentric and concentric resistance training in healthy subjects. Materials and Methods: Ten healthy men were randomly divided into two groups (5 patients in eccentric group - 5 in eccentric group). Isokinetic contraction protocols included eccentric and concentric knee extension with maximum power and angular velocity of 60 degrees per second. The torques assigned to each subject were considered to match the workload in both protocols, with a rotational speed of 60 degrees per second. Contractions consisted of a maximum of 12 sets of 10 repetitions for the right leg, a rest time of 30 seconds between each set. At the beginning and end of the study, biopsy of the lateral broad muscle tissue was performed. Biopsies were performed in both distal and proximal directions of the lateral flank. To evaluate the expression of PGC1α-1 and PGC1α-4 genes, tissue analysis was performed in each group using Real-Time PCR technique. Data were analyzed using dependent t-test and covariance test. SPSS21 software and Exell 2013 software were used for data analysis. Results: The results showed that intra-group changes of PGC1α-1 after one session of activity were not significant in eccentric (p = 0.168) and concentric (p = 0.959) groups. Also, inter-group changes showed no difference between the two groups (p = 0.681). Also, intra-group changes of PGC1α-4 after one session of activity were significant in an eccentric group (p = 0.012) and concentric group (p = 0.02). Also, inter-group changes showed no difference between the two groups (p = 0.362). Conclusion: It seems that the lack of significant changes in the desired variables due to the lack of exercise pressure is sufficient to stimulate the increase of PGC1α-1 and PGC1α-4. And with regard to reviewing the answer, it seems that the compatibility debate has different results that need to be addressed.

Keywords: eccentric contraction, concentric contraction, PGC1α-1 و PGC1α-4, human subject

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Authors: M. Naidoo

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Artificial intelligence often requires large amounts of good quality data. Within important fields, such as healthcare, the training of AI systems predominately relies on health and personal data; however, the usage of this data is complicated by various layers of law and ethics that seek to protect individuals’ privacy rights. This research seeks to establish the challenges AI and data sciences pose to (i) informational rights, (ii) privacy rights, and (iii) data protection. To solve some of the issues presented, various methods are suggested, such as embedding values in technological development, proper balancing of rights and interests, and others.

Keywords: artificial intelligence, data science, law, policy

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Authors: Seungsik Yu, Minho Kang

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As the threat of terrorism to nuclear facilities is increasing globally after the attacks of September 11, we are striving to recognize the physical protection system and strengthen the emergency response system. Since 2015, Korea has implemented physical protection security exercise for nuclear facilities. The exercise should be carried out with full cooperation between the operator and response forces. Performance testing of the physical protection system should include appropriate exercises, for example, force-on-force exercises, to determine if the response forces can provide an effective and timely response to prevent sabotage. Significant deficiencies and actions taken should be reported as stipulated by the competent authority. The IAEA(International Atomic Energy Agency) is also preparing force-on-force exercise program documents to support exercise of member states. Currently, ROK(Republic of Korea) is implementing exercise on the force-on-force exercise evaluation system which is developed by itself for the nuclear power plant, and it is necessary to establish the exercise procedure considering the use of the force-on-force exercise evaluation system. The purpose of this study is to establish the work procedures of the three major organizations related to the force-on-force exercise of nuclear power plants in ROK, which conduct exercise using force-on-force exercise evaluation system. The three major organizations are composed of licensee, KINAC (Korea Institute of Nuclear Nonproliferation and Control), and the NSSC(Nuclear Safety and Security Commission). Major activities are as follows. First, the licensee establishes and conducts an exercise plan, and when recommendations are derived from the result of the exercise, it prepares and carries out a force-on-force result report including a plan for implementation of the recommendations. Other detailed tasks include consultation with surrounding units for adversary, interviews with exercise participants, support for document evaluation, and self-training to improve the familiarity of the MILES (Multiple Integrated Laser Engagement System). Second, KINAC establishes a force-on-force exercise plan review report and reviews the force-on-force exercise plan report established by licensee. KINAC evaluate force-on-force exercise using exercise evaluation system and prepare training evaluation report. Other detailed tasks include MILES training, adversary consultation, management of exercise evaluation systems, and analysis of exercise evaluation results. Finally, the NSSC decides whether or not to approve the force-on-force exercise and makes a correction request to the nuclear facility based on the exercise results. The most important part of ROK's force-on-force exercise system is the analysis through the exercise evaluation system implemented by KINAC after the exercise. The analytical method proceeds in the order of collecting data from the exercise evaluation system and analyzing the collected data. The exercise application process of the exercise evaluation system introduced in ROK in 2016 will be concretely set up, and a system will be established to provide objective and consistent conclusions between exercise sessions. Based on the conclusions drawn up, the ultimate goal is to complement the physical protection system of licensee so that the system makes licensee respond effectively and timely against sabotage or unauthorized removal of nuclear materials.

Keywords: Force-on-Force exercise, nuclear power plant, physical protection, sabotage, unauthorized removal

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Authors: Ahmad Alqatan

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Purpose: The purpose of this study is to analyze how the adoption of cloud accounting systems influences the governance practices and performance of boards of directors in MENA countries. The research aims to identify the benefits and challenges associated with cloud accounting and its role in improving board efficiency and oversight. Methodology: This research employs a mixed-method approach, combining quantitative surveys and qualitative interviews with board members and financial officers from a diverse range of companies in the MENA region. The quantitative data is analyzed to determine patterns and correlations, while qualitative insights provide a deeper understanding of the contextual factors influencing cloud accounting adoption and its impacts. Findings: The findings indicate that cloud accounting significantly enhances the decision-making capabilities of boards by providing real-time financial information and facilitating better communication among board members. Companies using cloud accounting reports improved financial oversight and more timely and accurate financial reporting. However, the research also identifies challenges such as cybersecurity concerns, resistance to change, and the need for ongoing training and support. Practical Implications: The study suggests that MENA companies can benefit from investing in cloud accounting technologies to improve board governance and strategic decision-making. It highlights the importance of addressing cybersecurity issues and providing adequate training for board members to maximize the advantages of cloud accounting. Originality: This research contributes to the limited literature on cloud accounting in the MENA region, offering valuable insights for policymakers, business leaders, and academics. It underscores the transformative potential of cloud accounting for enhancing board performance and corporate governance in emerging markets.

Keywords: cloud accounting, board of directors, MENA region, corporate governance, financial transparency, real-time data, decision-making, cybersecurity, technology adoption

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Authors: Majda Ibrahim Aljaroudi, Jwaher Alburake

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The study aimed to identify the active role of the teacher in the management of the effective classroom environment for high school students from the viewpoint of the teachers, and to identify whether there were statistically significant differences between the averages of the respondents regarding the active role of the high school teachers in managing effective classroom environment in Riyadh, and also the total score depending on the variables of the study (qualifications, years of experience, training and development programs). This study used the descriptive survey approach where a questionnaire has been built and consisted of (35) items about five areas as a tool to measure the teacher's role in the management of effective classroom environment for high school students. The study population consisted of (1313) high school teachers in the government schools in south of Riyadh. It consisted of (70) teachers who were selected randomly. It used the appropriate statistical methods to analyze data by using statistical packages (SPSS). The study found the following results: • Most of the study sample members agreed on their role in the effective classroom environment management for high school students in government schools in Riyadh with an average (3.91 out of 5), which falls in the fifth category of Quintet scale (from 3.41 to 4.20) that refers to the option "often". • There are statistically significant differences between the mean responses of the study sample about the active role of the teacher in the effective classroom environment management for high school students regarding the concept of order in the classroom depending on the variable of years of experience for the benefit of teachers who have over 10 years of experience. There are statistically significant differences between the mean responses of the study sample about the teacher's active role in the effective classroom environment management for high school students regarding the educational process for maintaining the order in the classroom depending on the variable of training and development programs for the benefit of the teachers who have more than (5) courses. Due to the results of the study the researcher recommended a number of recommendations to improve the teacher's role in the effective classroom environment management for high school students.

Keywords: effective management, active learning, educational sciences, pedagogical sciences

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Authors: Renata Roma, Christine Tardif-Williams

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Engaging in daily walks with a dog (f.e. Canis lupus familiaris) during the COVID-19 pandemic may be linked to feelings of greater social-connectedness and global self-worth, and lower stress after controlling for mental health issues, lack of physical contact with others, and other stressors associated with the current pandemic. Therefore, maintaining a routine of dog walking might mitigate the effects of stressors experienced during the pandemic and promote well-being. However, many dog owners do not walk their dogs for many reasons, which are related to the owner’s and the dog’s personalities. Note that the consistency of certain personality characteristics among dogs demonstrates that it is possible to accurately measure different dimensions of personality in both dogs and their human counterparts. In addition, behavioural ratings (e.g., the dog personality questionnaire - DPQ) are reliable tools to assess the dog’s personality. Clarifying the relevance of personality factors in the context of young adult-dog relationships can shed light on interactional aspects that can potentially foster protective behaviours and promote well-being among young adults during the pandemic. This study examines if and how nine combinations of dog- and young adult-related personality characteristics (e.g., neuroticism-fearfulness) can amplify the influence of personality factors in the context of dog walking during the COVID-19 pandemic. Responses to an online large-scale survey among 440 (389 females; 47 males; 4 nonbinaries, Mage=20.7, SD= 2.13 range=17-25) young adults living with a dog in Canada were analyzed using structural equation modeling (SEM). As extraversion, conscientiousness, and neuroticism, measured through the five-factor model (FFM) inventory, are related to maintaining a routine of physical activities, these dimensions were selected for this analysis. Following an approach successfully adopted in the field of dog-human interactions, the FFM was used as the organizing framework to measure and compare the human’s and the dog’s personality in the context of dog walking. The dog-related personality dimensions activity/excitability, responsiveness to training, and fearful were correlated dimensions captured through DPQ and were added to the analysis. Two questions were used to assess dog walking. The actor-partner interdependence model (APIM) was used to check if the young adult’s responses about the dog were biased; no significant bias was observed. Activity/excitability and responsiveness to training in dogs were greatly associated with dog walking. For young adults, high scores in conscientiousness and extraversion predicted more walks with the dog. Conversely, higher scores in neuroticism predicted less engagement in dog walking. For participants high in conscientiousness, the dog’s responsiveness to training (standardized=0.14, p=0.02) and the dog’s activity/excitability (standardized=0.15, p=0.00) levels moderated dog walking behaviours by promoting more daily walks. These results suggest that some combinations in young adult and dog personality characteristics are associated with greater synergy in the young adult-dog dyad that might amplify the impact of personality factors on young adults’ dog-walking routines. These results can inform programs designed to promote the mental and physical health of young adults during the Covid-19 pandemic by highlighting the impact of synergy and reciprocity in personality characteristics between young adults and dogs.

Keywords: Covid-19 pandemic, dog walking, personality, structural equation modeling, well-being

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Authors: A. Giannakopoulos, S. B. Buckley

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Problem solving in any field is recognised as a prerequisite for any advancement in knowledge. For example in South Africa it is one of the seven critical outcomes of education together with critical thinking. As a systematic way to problem solving was initiated in mathematics by the great mathematician George Polya (the father of problem solving), more detailed and comprehensive ways in problem solving have been developed. This paper is based on the findings by the author and subsequent recommendations for further research in problem solving and critical thinking. Although the study was done in mathematics, there is no doubt by now in almost anyone’s mind that mathematics is involved to a greater or a lesser extent in all fields, from symbols, to variables, to equations, to logic, to critical thinking. Therefore it stands to reason that mathematical principles and learning cannot be divorced from any field. In management of knowledge situations, the types of problems are similar to mathematics problems varying from simple to analogical to complex; from well-structured to ill-structured problems. While simple problems could be solved by employees by adhering to prescribed sequential steps (the process), analogical and complex problems cannot be proceduralised and that diminishes the capacity of the organisation of knowledge creation and innovation. The low efficiency in some organisations and the low pass rates in mathematics prompted the author to view problem solving as a product. The authors argue that using mathematical approaches to knowledge management problem solving and treating problem solving as a product will empower the employee through further training to tackle analogical and complex problems. The question the authors asked was: If it is true that problem solving and critical thinking are indeed basic skills necessary for advancement of knowledge why is there so little literature of knowledge management (KM) about them and how they are connected and advance KM?This paper concludes with a conceptual model which is based on general accepted principles of knowledge acquisition (developing a learning organisation), knowledge creation, sharing, disseminating and storing thereof, the five pillars of knowledge management (KM). This model, also expands on Gray’s framework on KM practices and problem solving and opens the doors to a new approach to training employees in general and domain specific areas problems which can be adapted in any type of organisation.

Keywords: critical thinking, knowledge management, mathematics, problem solving

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Authors: Zhai Yuan, Wu Xueqing

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This article statistics the technology which used by Chinese and foreign excellent players in the game, including types and serves areas,receive technology and effect and utilization ratio receiving and losing points. The sample is che videos which is world's top matches of excellent badminton athletes of che single, including Chinese players’ 43 games and foreign players’ 38 games. Conclusion: For the serving, Chinese and foreign single players are to give priority to forehand short-low serve and the long-high serve. And Chinese and foreign players in using forehand short-low serve and drive server exist significant differences; For the serves areas, Chinese and foreign players serve area is concentrated in area 1,5,6. Area 6 has the highest rate of all the district areas, following by the area 1and area 5. Among the 2ed serve area Sino-foreign player, there exist significant differences; In the receiver, when returning the frontcourt shutter, players is given priority to net lift and push. When returning the backcourt shutter, receiver's the best ball is smash, followed by clear and drop shot. Foreign players have higher utilization rate in smash than Chinese players in the backcourt; In the receiver result, Chinese players give priority to actively and equally situation than foreign players, but in negatively receiving is just opposite.

Keywords: badminton, woman’s singles, technique and tactics, comparative analysis

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Authors: Helen Coronel, Will Brewer, Peggy Bergeron, Clarissa Hall, Victoria Casson

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Simulation-based training provides the nurse practitioner (NP) student with a safe and controlled environment in which they can practice a real-life scenario. This type of learning fosters critical thinking skills essential to practice. The expectation of this study was that students would have an increase in their competency and confidence after performing the simulation. Approximately 8.4% of Americans suffer from depression. The state of Alabama is ranked 47th out of 50 for access to mental health care. As a result of this significant shortage of mental health providers, primary care providers are frequently put in the position of screening for and treating mental health conditions, such as depression. Family nurse practitioners are often utilized as primary care providers, making their ability to assess, diagnose and treat these disorders a necessary skill. The expected outcome of this simulation is an increase in confidence, competency and the empowerment of the nurse practitioner student’s ability to assess, diagnose and treat a common mood disorder they may encounter in practice. The Kirkpatrick Module was applied for this study. A non-experimental design using descriptive statistical analysis was utilized. The simulation was based on a common psychiatric mood disorder frequently observed in primary care and mental health clinics. Students were asked to watch a voiceover power point presentation prior to their on-campus simulation. The presentation included training on the assessment, diagnosis, and treatment of a patient with depression. Prior to the simulation, the students completed a pre-test, then participated in the simulation, and completed a post-test when done. Apple iPads were utilized to access a simulated health record. Major findings of the study support an increase in students’ competency and confidence when assessing, diagnosing, and treating an adult patient with depression.

Keywords: advanced practice, nurse practitioner, simulation, primary care, depression

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Authors: Pedram Saadati, Zahra Nazari

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Today, the role and importance of financial technology businesses in Iran have increased significantly. Although, in Iran, there is no Islamic or non-Islamic personal financial planning field of study in the universities or educational centers, the profession of personal financial planning is not defined, and there is no software introduced in this regard for advisors or consumers. The largest sales network of financial services in Iran belongs to the insurance industry, and there is an untapped market for international companies in Iran that can contribute to 130 thousand representatives in the insurance industry and 28 million families by providing training and personal financial advisory software. To the best of the author's knowledge, despite the lack of previous internal studies in this field, the present study investigates the level of readiness of the salesforce of the insurance industry to accept this career and its technology. The statistical population of the research is made up of managers, insurance sales representatives, assistants and heads of sales departments of insurance companies. An 18-minute video was prepared that introduced and taught the job of Islamic personal financial planning and explained its difference from its non-Islamic model. This video was provided to the respondents. The data collection tool was a research-made questionnaire. To investigate the factors affecting technology acceptance and job change, independent T descriptive statistics and Pearson correlation were used, and Friedman's test was used to rank the effective factors. The results indicate the mental perception and very positive attitude of the insurance industry activists towards the usefulness of this job and its technology, and the studied sample confirmed the intention of training in this knowledge. Based on research results, the change in the customer's attitude towards the insurance advisor and the possibility of increasing income are considered as the reasons for accepting. However, Restrictions on using investment opportunities due to Islamic financial services laws and the uncertainty of the position of the central insurance in this regard are considered as the most important obstacles.

Keywords: fintech, insurance, personal financial planning, wealth management

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Authors: Marisa Galiza Filipe

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In 1942, at the height of the Second World War, Roosevelt and Churchill planned to occupy the Azores to establish air and naval bases. The islands' privileged position in the middle of the Atlantic made them a strategic location for both the Axis and the Allies. For the Germans, the occupation of the island was also a strategic place to launch an attack on the United States of America, and for the British and Americans, the islands were the perfect spot to counterattack the German sinking of British boats and submarines. Salazar avoided the concession of the islands until 1943, claiming, on the one hand, the policy of neutrality, a decision made in agreement with England, and on the other hand, the reaffirmation of Portuguese sovereignty over the territory. Aware of the constant changes and supported by a network of informers on the islands, the German and British spies played a crucial role in the negotiations between Portugal and the Allies and the ceding of the bases by Salazar, which prevented their forced occupation. The espionage caused several diplomatic tensions, and the large number of German spies denounced by the British, operating on the islands under the watchful eye of the PVDE and Salazar, weakened the Portuguese-British alliance. Using primary source documents in the Ministério dos Negócios Estrangeiros (MNE) archives, this paper introduces the spies that operated on the islands, their missions and motives, organizations, and modus operandi. As a chess game, any move was careful thinking and the spies were valuable assets to control and use information that could lead to the occupation of the islands and, ultimately, change the tide of the war.

Keywords: espionage, Azores, WWI, neutrality

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Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Computational linguistics is a growing field dealing with such issues of data collection for technological development. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Computational analysis on such linguistic data is used to find patterns of misogyny. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: computational analysis, gendered grammar, misogynistic language, neural networks

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Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

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Authors: Godfrey Muiya Mukala

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This research looks at an array of fields in Sub-Saharan Africa comprising agriculture, food enterprises, medicine, organisms genetically modified, microbiology, and nanotechnology that can be gained from biotechnological research and development. Findings into dangerous organisms, mainly bacterial germs, rickettsia, fungi, parasites, or organisms that are genetically engineered, have immensely posed questions attributed to the biological danger they bring forth to human beings and the environment because of their uncertainties. In addition, the recurrence of previously managed diseases or the inception of new diseases are connected to biosafety challenges, especially in rural set-ups in low and middle-income countries. Notably, biotechnology laboratories are required to adopt biosafety measures to protect their workforce, community, environment, and ecosystem from unforeseen materials and organisms. Sensitization and inclusion of educational frameworks for laboratory workers are essential to acquiring a solid knowledge of harmful biological agents. This is in addition to human pathogenicity, susceptibility, and epidemiology to the biological data used in research and development. This article reviews and analyzes research intending to identify the proper implementation of universally accepted practices in laboratory safety and biological hazards. This research identifies ideal microbiological methods, adequate containment equipment, sufficient resources, safety barriers, specific training, and education of the laboratory workforce to decrease and contain biological hazards. Subsequently, knowledge of standardized microbiological techniques and processes, in addition to the employment of containment facilities, protective barriers, and equipment, is far-reaching in preventing occupational infections. Similarly, reduction of risks and prevention may be attained by training, education, and research on biohazards, pathogenicity, and epidemiology of the relevant microorganisms. In this technique, medical professionals in rural setups may adopt the knowledge acquired from the past to project possible concerns in the future.

Keywords: sub-saharan africa, biotechnology, laboratory, infections, health

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Authors: Akeel A. Shah, Tong Zhang

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Computational approaches to learning the properties of materials are commonplace, motivated by the need to screen or design materials for a given application, e.g., semiconductors and energy storage. Experimental approaches can be both time consuming and costly. Unfortunately, computational approaches such as ab-initio electronic structure calculations and classical or ab-initio molecular dynamics are themselves can be too slow for the rapid evaluation of materials, often involving thousands to hundreds of thousands of candidates. Machine learning assisted approaches have been developed to overcome the time limitations of purely physics-based approaches. These approaches, on the other hand, require large volumes of data for training (hundreds of thousands on many standard data sets such as QM7b). This means that they are limited by how quickly such a large data set of physics-based simulations can be established. At high fidelity, such as configuration interaction, composite methods such as G4, and coupled cluster theory, gathering such a large data set can become infeasible, which can compromise the accuracy of the predictions - many applications require high accuracy, for example band structures and energy levels in semiconductor materials and the energetics of charge transfer in energy storage materials. In order to circumvent this problem, multi-fidelity approaches can be adopted, for example the Δ-ML method, which learns a high-fidelity output from a low-fidelity result such as Hartree-Fock or density functional theory (DFT). The general strategy is to learn a map between the low and high fidelity outputs, so that the high-fidelity output is obtained a simple sum of the physics-based low-fidelity and correction, Although this requires a low-fidelity calculation, it typically requires far fewer high-fidelity results to learn the correction map, and furthermore, the low-fidelity result, such as Hartree-Fock or semi-empirical ZINDO, is typically quick to obtain, For high-fidelity outputs the result can be an order of magnitude or more in speed up. In this work, a new multi-fidelity approach is developed, based on a graph convolutional network (GCN) combined with semi-supervised learning. The GCN allows for the material or molecule to be represented as a graph, which is known to improve accuracy, for example SchNet and MEGNET. The graph incorporates information regarding the numbers of, types and properties of atoms; the types of bonds; and bond angles. They key to the accuracy in multi-fidelity methods, however, is the incorporation of low-fidelity output to learn the high-fidelity equivalent, in this case by learning their difference. Semi-supervised learning is employed to allow for different numbers of low and high-fidelity training points, by using an additional GCN-based low-fidelity map to predict high fidelity outputs. It is shown on 4 different data sets that a significant (at least one order of magnitude) increase in accuracy is obtained, using one to two orders of magnitude fewer low and high fidelity training points. One of the data sets is developed in this work, pertaining to 1000 simulations of quinone molecules (up to 24 atoms) at 5 different levels of fidelity, furnishing the energy, dipole moment and HOMO/LUMO.

Keywords: .materials screening, computational materials, machine learning, multi-fidelity, graph convolutional network, semi-supervised learning

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Authors: Tigabu Dagne Akal

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While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study.

Keywords: intrusion detection, data mining, computer science, data mining

Procedia PDF Downloads 295