Search results for: developmental tasks

Authors: Sarra Hasni, Sami Faiz

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In recent years, location prediction on social networks has gained significant attention, with short and unstructured texts like tweets posing additional challenges. Advanced geolocation models have been proposed, increasing the need to explain their predictions. In this paper, we provide explanations for a geolocation black-box model using LIME and SHAP, two state-of-the-art XAI (eXplainable Artificial Intelligence) methods. We extend our evaluations to Large Language Models (LLMs) as post hoc explainers for tweet geolocation. Our preliminary results show that LLMs outperform LIME and SHAP by generating more accurate explanations. Additionally, we demonstrate that prompts with examples and meta-prompts containing phonetic spelling rules improve the interpretability of these models, even with informal input data. This approach highlights the potential of advanced prompt engineering techniques to enhance the effectiveness of black-box models in geolocation tasks on social networks.

Keywords: large language model, post hoc explainer, prompt engineering, local explanation, tweet geolocation

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Authors: Xiaoxiao Li, Shuangcheng Jia, Qian Li

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Keypoint detection has always been a challenge in the field of image recognition. This paper proposes a novelty keypoint detection method which is called Multi-Scale Feature Fusion Convolutional Network with Attention (MFFCNA). We verified that the multi-scale features with the attention mechanism module have better feature expression capability. The feature fusion between different scales makes the information that the network model can express more abundant, and the network is easier to converge. On our self-made street sign corner dataset, we validate the MFFCNA model with an accuracy of 97.8% and a recall of 81%, which are 5 and 8 percentage points higher than the HRNet network, respectively. On the COCO dataset, the AP is 71.9%, and the AR is 75.3%, which are 3 points and 2 points higher than HRNet, respectively. Extensive experiments show that our method has a remarkable improvement in the keypoint recognition tasks, and the recognition effect is better than the existing methods. Moreover, our method can be applied not only to keypoint detection but also to image classification and semantic segmentation with good generality.

Keywords: keypoint detection, feature fusion, attention, semantic segmentation

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Authors: Christopher Manyamba

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Women in Malawi produce perform between 50-70 percent of all agricultural tasks and yet the majority remain food insecure. The aim of his paper is to build on existing mixed evidence that indicates that empowering women in agriculture is conducive to improving food security. The WEAI is used to provide evidence on the relationship between women’s empowerment in agriculture and household food security. A multinomial logistic regression is applied to the Women Empowerment in Agriculture Index (WEAI) components and the Household Hunger Scale. The overall results show that the WEAI can be used to determine household food insecurity; however it has to be contextually adapted. Assets ownership, credit, group membership and leisure time are positively associated with food security. Contrary to other literature, empowerment in having control and decisions on income indicate negative association with household food security. These results could potentially better inform public, private and civil society stakeholders’ dialogues in creating the most effective and sustainable interventions to help women attain long-term food security.

Keywords: food security, gender, empowerment, agriculture index, framework for African food security, household hunger scale

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Authors: Yihao Kuang, Bowen Ding

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With the increasing scale and complexity of knowledge graph, modern knowledge graph contains more and more types of entity, relationship, and attribute information. Therefore, in recent years, it has been a trend for knowledge graph inference to use reinforcement learning to deal with large-scale, incomplete, and noisy knowledge graph and improve the inference effect and interpretability. The Proximal Policy Optimization (PPO) algorithm utilizes a near-end strategy optimization approach. This allows for more extensive updates of policy parameters while constraining the update extent to maintain training stability. This characteristic enables PPOs to converge to improve strategies more rapidly, often demonstrating enhanced performance early in the training process. Furthermore, PPO has the advantage of offline learning, effectively utilizing historical experience data for training and enhancing sample utilization. This means that even with limited resources, PPOs can efficiently train for reinforcement learning tasks. Based on these characteristics, this paper aims to obtain better and more efficient inference effect by introducing PPO into knowledge inference technology.

Keywords: reinforcement learning, PPO, knowledge inference, supervised learning

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Authors: Anek Apipatkul, Paphakorn Pitayachaval

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Preventive maintenance is a standardized procedure to control and prevent risky problems affecting production in order to increase work efficiency. Machine monitoring also routinely works to collect data for a scheduling maintenance period. This paper is to present the application of machine monitoring by using the internet of things (IOTs) and a lean technique in order to manage with complex maintenance tasks of an automated plastic granule packing machine. To organize the preventive maintenance, there are several processes that the machine monitoring was applied, starting with defining a clear scope of the machine, establishing standards in maintenance work, applying a just-in-time (JIT) technique for timely delivery in the maintenance work, solving problems on the floor, and also improving the inspection process. The result has shown that wasted time was reduced, and machines have been operated as scheduled. Furthermore, the efficiency of the scheduled maintenance period was increased by 95%.

Keywords: internet of things, preventive maintenance, machine monitoring, lean technique

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Authors: Aneela Sheikh

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Private higher education institutes are challenged for their resilience and competitive edge in the globalized knowledge-based economy in the 21st century. Faculty retention plays an important role as a catalyst for addressing the current mega-developmental phenomenon in higher education institutes faced by developing countries. This study intends to explore the influence of servant leadership practice on faculty retention through the intervening role of job satisfaction towards minimizing the high faculty turnover in private higher education institutes, with the mediating role of job satisfaction. A sample of 341 faculty members from ten private higher education institutes in Lahore city of Pakistan, was selected through a stratified proportionate random sampling technique. A descriptive survey research approach was employed to collect data from 341 faculty members by administering a close-ended questionnaire based on a seven-point Likert scale as a self-administered research instrument. The study was conducted under the domain of the Leader-Member Exchange (LMX) theory. The mediating role of job satisfaction was measured by bootstrapping technique. The results revealed that servant leadership has a statistically significant influence on faculty retention, with a statistically significant mediating role of job satisfaction, in private higher education institutes in Pakistan. Further, up to the best of the authors’ knowledge, this is the first systematic and empirical study on faculty retention conducted against the backdrop of servant leadership in an Eastern context, particularly in Pakistan.

Keywords: servant leadership, faculty retention, job satisfaction, higher education institutes

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Authors: Marjone Van Der Bank, C. M. Van Der Bank

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This paper presents an overview of the foundation and evolution of environmental related problems in local governments with specific reference on air pollution in South Africa. Local government has a direct mandate in terms of the Constitution of the Republic of South Africa, 1996 (hereafter, the Constitution). This mandate to protect, fulfil, respect and promote the Bill of Rights by local governments in respect of the powers and functions creates confusion around the role of where a local government fits in, in addressing the problem of climate change in South Africa. A reflection of the evolving legislations, developments, and processes regarding climate change that shaped local government dispensation in South Africa is addressed by the notion of developmental local governments. This paper seeks to examine the advances for mitigation and adaptation regulation of air pollution and application in South Africa. This study involves a qualitative approach that will involve South African national legislation as well as an interpretation of international strategies. A literature review study was conducted to undertake the various aspects of law in order to support the argument undertaken of mitigation and adaptation strategies. The paper presents a detailed discussion of the current legislation and the position as it currently stands, as well as the relevant protections as outlined in the National Environmental Management Act and the National Environmental Management: Air Quality Act. It then proceeds to outline the responsibilities of local governments in South Africa to mitigate and adapt to air pollution strategies.

Keywords: adaptation, climate change, disaster, local governments and mitigation

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Authors: D. Maneetham, L. Sivhour

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Robotic arm manipulators are widely used to accomplish many kinds of tasks. SCORBOT-ER 4u is a 5-degree of freedom (DOF) vertical articulated educational robotic arm, and all joints are revolute. It is specifically designed to perform pick and place task with its gripper. The pick and place task consists of consideration of the end effector coordinate of the robotic arm and the desired position coordinate in its workspace. This paper describes about forward kinematics modeling and analysis of the robotic end effector motion through joint space. The kinematics problems are defined by the transformation from the Cartesian space to the joint space. Denavit-Hartenberg (D-H) model is used in order to model the robotic links and joints with 4x4 homogeneous matrix. The forward kinematics model is also developed and simulated in MATLAB. The mathematical model is validated by using robotic toolbox in MATLAB. By using this method, it may be applicable to get the end effector coordinate of this robotic arm and other similar types to this arm. The software development of SCORBOT-ER 4u is also described here. PC-and EtherCAT based control technology from BECKHOFF is used to control the arm to express the pick and place task.

Keywords: forward kinematics, D-H model, robotic toolbox, PC- and EtherCAT-based control

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Authors: Franziska Köhler-Dauner, Inka Mayer, Lara Hart, Ute Ziegenhain, Jörg M. Fegert

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Preventive isolation and social distancing strategies during the SARS-CoV-2 pandemic have confronted families with a variety of different restrictions and stresses. Especially during this stressful time, children need a stable parental home to avoid developmental disorders. Additional risk factors such as maternal childhood abuse and neglect (CM) experiences may influence mothers' psychosomatic health (pG) and children's physical well-being (kW) during times of increased stress. Our aim was to analyse the interaction between maternal CM, maternal pG and children's kW during the pandemic. Mothers from a well-documented birth cohort to study transgenerational transmission of CM, were included in an online 'pandemic' survey assessing maternal pG and children's physical health during the pandemic. Our mediation analysis showed a significant positive association between the extent of maternal CM experiences, mothers' psychosomatic symptoms and their children's kW. Maternal psychosomatic symptoms significantly mediate the interaction between CM and children's kW; the direct effect remains non-significant when maternal psychosomatic symptoms are included as mediators. Maternal CM appears to be a relevant risk factor for maternal pG and children's kW during the pandemic. Maternal CM experiences seem to influence the way parents cope with stressful situations and increase the risk of suffering from depressive symptoms. The latter also affect their children's kW. Our findings underline the importance of carefully assessing the specific situation of families with children and offering individually adapted help to help families survive the pandemic.

Keywords: pandemic, maternal health, child health, abuse, neglect, maternal experiences

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Authors: James Donald Nyamahono, Kelvin Tinashe Pikirai

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Communal based natural resource management (CBNRM) is regarded as one of the most significant methods for sustainable natural resource conservation. This is due to the fact that it entails the engagement of local communities as well as the use of indigenous knowledge and customary conservation. The emergence of COVID-19 had a devastating impact on this sector since it has resulted in the disbandment of all collective activities, such as group gatherings, including those with a good cause. This is supported by research, which demonstrates that throughout the era of full lockdowns, the coordination of diverse activities and the sustainability of various working groups were severely harmed. This study was undertaken in the CBNRM niche to examine how COVID-19 affected this sector. Data were gathered through focus group discussions with youths, women, and the elderly active in CBNRM in Newtown, Bekezela Village, Eastern Cape. The study concluded that the sustainability of indigenous knowledge in natural resource management was endangered due to the restricted movements and community participation in developmental initiatives. The study also revealed a 'environment-community divide,' since COVID-19 hindered local communities from holding their regular conservation meetings. The research, on the other hand, discovered that there were 'secret' gatherings in which local communities attempted to adopt Afrocentric ways in which the available natural resources would provide a remedy for COVID-19.

Keywords: CBNRM, COVID-19, indigenous knowledge, South Africa

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Authors: Mohan Ramasundaram, Amutha Prabakar Muniyandi

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Remote user authentication is one of the important tasks for any kind of remote server applications. Several remote authentication schemes are proposed by the researcher for Telecare Medicine Information System (TMIS). Most of the existing techniques have limitations, vulnerable to various kind attacks, lack of functionalities, information leakage, no perfect forward security and ineffectiveness. Authentication is a process of user verification mechanism for allows him to access the resources of a server. Nowadays, most of the remote authentication protocols are using two-factor authentications. We have made a survey of several remote authentication schemes using three factors and this survey shows that the most of the schemes are inefficient and subject to several attacks. We observed from the experimental evaluation; the proposed scheme is very secure against various known attacks that include replay attack, man-in-the-middle attack. Furthermore, the analysis based on the communication cost and computational cost estimation of the proposed scheme with related schemes shows that our proposed scheme is efficient.

Keywords: Telecare Medicine Information System, elliptic curve cryptography, three-factor, biometric, random oracle

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Authors: Uswah Khairuddin, Rubiyah Yusof, Nenny Ruthfalydia Rosli

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This paper presents a comparative study between k-Nearest Neighbour (k-NN) and Multi-Layer Perceptron Neural Network (MLP-NN) classifier using Genetic Algorithm (GA) as feature selector for wood recognition system. The features have been extracted from the images using Grey Level Co-Occurrence Matrix (GLCM). The use of GA based feature selection is mainly to ensure that the database used for training the features for the wood species pattern classifier consists of only optimized features. The feature selection process is aimed at selecting only the most discriminating features of the wood species to reduce the confusion for the pattern classifier. This feature selection approach maintains the ‘good’ features that minimizes the inter-class distance and maximizes the intra-class distance. Wrapper GA is used with k-NN classifier as fitness evaluator (GA-kNN). The results shows that k-NN is the best choice of classifier because it uses a very simple distance calculation algorithm and classification tasks can be done in a short time with good classification accuracy.

Keywords: feature selection, genetic algorithm, optimization, wood recognition system

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Authors: Xinyuan Zou, Qihui Tang, Shujian Wang, Yulin Huang, Jie Gui, Xiangping Liu, Gang Liu, Yanqiang Tao

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Childhood trauma can have a long-lasting influence on individuals and contribute to mental disorders, including depression and anxiety. The current study aimed to explore the symptomatic and developmental patterns of depression, anxiety, and stress among adolescents who have suffered from childhood trauma. A total of 3,598 college students (female = 1,617 (44.94%), Mean Age = 19.68, SD Age = 1.35) in China completed the Childhood Trauma Questionnaire (CTQ) and the Depression, Anxiety, and Stress Scales (DASS-21), and 2,337 participants met the selection standard based on the cut-off scores of the CTQ. The symptomatic network and directed acyclic graph (DAG) network approaches were used. The results revealed that males reported experiencing significantly more physical abuse, physical neglect, emotional neglect, and sexual abuse compared to females. However, females scored significantly higher than males on all items of DASS-21, except for “Worthless”. No significant difference between the two genders was observed in the network structure and global strength. Meanwhile, among all participants, “Down-hearted” and “Agitated” appeared to be the most interconnected symptoms, the bridge symptoms in the symptom network, as well as the most vital symptoms in the DAG network. Apart from that, “No-relax” also served as the most prominent symptom in the DAG network. The results suggested that intervention targeted at assisting adolescents in developing more adaptive coping strategies with stress and regulating emotion could benefit the alleviation of comorbid depression, anxiety, and stress.

Keywords: symptom network, childhood trauma, depression, anxiety, stress

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Authors: Anantdeep Kaur, Sharanjeet Singh

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Early childhood education and assessment of children is a very essential tool that helps them in their growth and development. Techniques should be developed, and tools should be created in this field as it is a very important learning phase of life. Some information and sources are included for student assessment to provide a record of growth in all developmental areas cognitive, physical, Language, social-emotional, and approaches to learning. As an early childhood educator, it is very important to identify children who need special support and counseling to improve them because they are not mentally mature to discuss with the teacher their problems and needs. It is the duty and responsibility of the educator to assess children from their body language, behavior, and their routine actions about their skills that can be improved and which can take them forward in their future life. And also, children should be assessed with their weaker points because this is the right time to correct them, and they be improved with certain methods and tools by working on them constantly. Observing children regularly with all their facets of development, including intellectual, linguistic, social-emotional, and physical development. Every day, a physical education class should be regulated to check their physical growth activities, which can help to assess their physical activeness and motor abilities. When they are outside on the playgrounds, it is very important to instill environmental understanding among them so that they should know that they are very part of this nature, and it will help them to be one with the universe rather than feeling themselves individually. This technique assists them in living their childhood full of energy all the time. All types of assessments have unique purposes. It is important first to determine what should be measured, then find the program that best assesses those.

Keywords: special needs, motor ability, environmental understanding, physical development

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Authors: Oluwagbemiga Paul Agboola, Cornelius Olatunji Omojola, Dayo Martins Oyeshomo

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The role of a recreational park in human and environmental development has attracted much interest in the recent time. Recreation parks' development could act as an effective planning strategy to enhance environmental sustainability, social cohesiveness, and users' quality of life. Similarly, parks enhance neighbourhood's aesthetics, refresh the air and enhance humans' contact with nature. In this connection, recreation parks create natural surroundings of rural areas for leisure, relaxation, recreation, psychological and physical comfort of the people. The purpose of this paper is to investigate the effectiveness of the two recreational parks' development as a strategy for neighbourhood's environmental improvement, sustainability and the recreationists' cohesiveness. A total number of 158 survey questionnaires were distributed to the tourists at Ikogosi cold and warm spring in Ekiti state as well as Olumirin waterfalls, Erin-Ijesa, Osun State, in South-West, Nigeria. The quantitative results of the analyzed data with Relative Importance Index (RII) revealed that recreation parks provide optimum opportunities for users' social cohesiveness and well-being while parks' sustainable environment could be enhanced base on the provision of essential facilities, services, and future developmental plans. It is recommended that for recreation parks to realize their full potential in environmental sustainability, adequate maintenance and provision of essential facilities becomes imperative.

Keywords: environmental sustainability, neighbourhood development, recreational park, Nigeria

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Authors: Hiroshi Kinoshita, Yasuto Nakanishi, Ryuhei Okuno, Toshio Higashi

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Various kinds of pegboards have been developed and used widely in research and clinics of rehabilitation for evaluation and training of patient’s hand function. A common measure in these peg boards is a total time of performance execution assessed by a tester’s stopwatch. Introduction of electrical and automatic measurement technology to the apparatus, on the other hand, has been delayed. The present work introduces the development of a pegboard with an electric sensor to detect moments of individual peg’s insertion and removal. The work also gives fundamental data obtained from a group of healthy young individuals who performed peg transfer tasks using the pegboard developed. Through trails and errors in pilot tests, two 10-hole peg-board boxes installed with a small photo-reflector and a DC amplifier at the bottom of each hole were designed and built by the present authors. The amplified electric analogue signals from the 20 reflectors were automatically digitized at 500 Hz per channel, and stored in a PC. The boxes were set on a test table at different distances (25, 50, 75, and 125 mm) in parallel to examine the effect of hole-to-hole distance. Fifty healthy young volunteers (25 in each gender) as subjects of the study performed successive fast 80 time peg transfers at each distance using their dominant and non-dominant hands. The data gathered showed a clear-cut light interruption/continuation moment by the pegs, allowing accurately (no tester’s error involved) and precisely (an order of milliseconds) to determine the pull out and insertion times of each peg. This further permitted computation of individual peg movement duration (PMD: from peg-lift-off to insertion) apart from hand reaching duration (HRD: from peg insertion to lift-off). An accidental drop of a peg led to an exceptionally long ( < mean + 3 SD) PMD, which was readily detected from an examination of data distribution. The PMD data were commonly right-skewed, suggesting that the median can be a better estimate of individual PMD than the mean. Repeated measures ANOVA using the median values revealed significant hole-to-hole distance, and hand dominance effects, suggesting that these need to be fixed in the accurate evaluation of PMD. The gender effect was non-significant. Performance consistency was also evaluated by the use of quartile variation coefficient values, which revealed no gender, hole-to-hole, and hand dominance effects. The measurement reliability was further examined using interclass correlation obtained from 14 subjects who performed the 25 and 125 mm hole distance tasks at two 7-10 days separate test sessions. Inter-class correlation values between the two tests showed fair reliability for PMD (0.65-0.75), and for HRD (0.77-0.94). We concluded that a sensor peg board developed in the present study could provide accurate (excluding tester’s errors), and precise (at a millisecond rate) time information of peg movement separated from that used for hand movement. It could also easily detect and automatically exclude erroneous execution data from his/her standard data. These would lead to a better evaluation of hand dexterity function compared to the widely used conventional used peg boards.

Keywords: hand, dexterity test, peg movement time, performance consistency

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Authors: Sina Saadati

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Multiprocessors Systems-On-Chips (MPSOCs) are used widely on modern computers to execute sophisticated software and applications. These systems include different processors for distinct aims. Most of the proposed task schedulers attempt to improve energy consumption. In some schedulers, the processor's temperature is considered to increase the system's reliability and performance. In this research, we have proposed a new method for thermal-aware task scheduling which is based on an artificial neural network (ANN). This method enables us to consider a variety of factors in the scheduling process. Some factors like ambient temperature, season (which is important for some embedded systems), speed of the processor, computing type of tasks and have a complex relationship with the final temperature of the system. This Issue can be solved using a machine learning algorithm. Another point is that our solution makes the system intelligent So that It can be adaptive. We have also shown that the computational complexity of the proposed method is cheap. As a consequence, It is also suitable for battery-powered systems.

Keywords: task scheduling, MOSOC, artificial neural network, machine learning, architecture of computers, artificial intelligence

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Authors: Nidhi S. Bisht

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The study examines the role of work-home interference, on enhancing emotional exhaustion in the branch officers of private MFIs in India. Additionally, the moderating role of recovery experiences and technology-assisted supplemental work (TASW) were studied. With the increasing expectations to perform job related tasks at home, technology-assisted supplemental work (TASW) was hypothesized to positively moderate the relationship between work-home interference and emotional exhaustion. Further, it was expected that recovery experiences-psychological detachment, relaxation will help to recover and unwind from work and negatively moderate the relationship between work-home interference and emotional exhaustion. Results of SEM-analyses largely offered support for the hypotheses. These findings increase our insight in the processes leading to increased emotional exhaustion and suggest that employees can protect themselves from emotional exhaustion by keeping a tab on technology-assisted supplemental work and facilitating recovery experiences.

Keywords: emotional exhaustion, India, microfinance institutions (MFIs), work-home interference

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Authors: Dimitar Karastoyanov, Todor Penchev

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The paper presents the research of a kind of autonomous mobile robots, intended for work and adaptive perception in unknown and unstructured environment. The objective are robots, dedicated for multi-sensory environment perception and exploration, like measurements and samples taking, discovering and putting a mark on the objects as well as environment interactions–transportation, carrying in and out of equipment and objects. At that ground classification of the different types mobile robots in accordance with the way of locomotion (wheel- or chain-driven, walking, etc.), used drive mechanisms, kind of sensors, end effectors, area of application, etc. is made. Modular system for the mechanical construction of the mobile robots is proposed. Special PLC on the base of AtMega128 processor for robot control is developed. Electronic modules for the wireless communication on the base of Jennic processor as well as the specific software are developed. The methods, means and algorithms for adaptive environment behaviour and tasks realization are examined. The methods of group control of mobile robots and for suspicious objects detecting and handling are discussed too.

Keywords: mobile robots, wireless communications, environment investigations, group control, suspicious objects

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Authors: Darynne Madison Dela Gente, Panayiota Courelli

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Similarities in behavior between perpetrators of school violence and those with a parent in prison raise concern when considering the root causes of a student’s violent behavior. Dealing with parental incarceration is highly consequential on a student’s emotional well-being and may cause aggressive behavior that can lead to them becoming a perpetrator of school violence. These students are more likely to have interpersonal issues, antisocial tendencies, and a hostile demeanor, which are factors that closely align with indicators of an offender of violence. Developmental risk factors of parental incarceration are heavily understudied and often overlooked. This literature review aims to analyze the correlation between having a parent in prison and exhibiting physical or verbal aggression in a school environment. Furthermore, it strives to bring awareness to the inconsistencies in existing research and encourage a greater depth of study of the behavioral impacts, specifically in an academic setting. Furthermore, it will elaborate on the effectiveness of current intervention programs, such as Project Avary, Hope House, Kids Mates Inc., and Girl Scouts Beyond Bars, which provide immense support, as well as proposed methods of implementation in a school environment. Creating a space for these students to cope ultimately aids in the prevention of violent behaviors and intergenerational incarceration. Access to intervention programs, especially in schools located in areas with high rates of incarceration, would greatly reduce the risk of these students becoming perpetrators of school violence.

Keywords: adolescent behavior, adolescent mental health, parental incarceration, school violence prevention

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Authors: Rimac Smiljanic Ana, Pepur Sandra, Bulog Ivana

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Financial decision-making in the household is not simple, and it demands that the decision-maker has proper knowledge and skills. Usually, high uncertainty, risk, and stress surround household financial decision-making since it is extremely important and critical for household wealth accumulation and for the well-being of all household members. Generally, skilful people tend to have higher confidence in certain tasks they perform, and they achieve better results. Therefore, in the household context, the possession of certain skills by the ones who make financial decisions for the household is of particular importance. This paper addresses financial literacy as an important skill for household decision-making. Apart from financial literacy, the paper also considers other factors, such as employment, education, and age, as significant for household financial decision-making. The analysis is based on quantitative individual-level survey data. The data collection was conducted during January and February 2021 in Croatia through an online survey. To reach a wide variety of participants, the snowball sampling method was used. The result revealed interesting and somewhat puzzling results. Our results point to the importance of financial literacy skills for household decision-making.

Keywords: skill, financial literacy, decision-making, household financijal decision making

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Authors: Gladys Maame Akua Setordzie

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Decision on one’s future career is said to have both beneficial and detrimental effects on one’s mental health, social and economic standing later in life, making it an important developmental problem for young people. In this light, the study’s overarching goal was to assess how different personality traits serve as a determinant of career decision-making difficulties experienced by university students in Ghana. Specifically, for the purpose of shaping the future of individualized career counselling support, the study investigated whether the “Big Five” personality traits influenced the difficulties students at the University of Ghana encounter while making career decisions. Cross-sectional survey design using a stratified random sampling technique, sampled 494 undergraduate students from the University of Ghana, who completed the Big Five Questionnaire and the Career Decision-making Difficulties Questionnaire. Hierarchical multiple regression analyses indicated that neuroticism, consciousness, and openness, accounted for a significant proportion of the variance in career decision-making difficulties. This study provides empirical evidence to support the idea that neuroticism is not necessarily a negative emotion when it comes to career decisionmaking, as has been suggested in previous studies, but rather it allows students to perform better in career decision-making. These results suggests that personality traits play a significant role in the career decision-making process of students of the University of Ghana. Therefore, a better understanding of how different personal and interpersonal factors impact career indecision in students could help career counsellors develop more focused vocational and career guidance interventions.

Keywords: career decision-making difficulties, dysfunctional career beliefs, personality traits, young people

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Authors: Pablo Javier Ortega-Rodriguez, Francisco Jose Pozuelos-Estrada

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Recently, there has been a renewed interest in school autonomy in the United Kingdom and its impact on students' outcomes. English principals have a pivotal role in decision-making. The aim of this paper is to explore the correlation between the type of school (public or private) and the considerable responsibilities of English principals which participated in PISA 2015. The final sample consisted of 419 principals. Descriptive data (percentages and means) were generated for the variables related to professional autonomy. Pearson's chi-square test was used to determine if there is an association between the type of school and principals' responsibilities for relevant tasks. Statistical analysis was performed using SPSS software, version 22. Findings suggest a significant correlation between the type of school and principals' responsibility for firing teachers and formulating the school budget. This study confirms that the type of school is not associated with principals' responsibility for choosing which textbooks are used at school. The present study establishes a quantitative framework for defining four models of professional autonomy and some proposals to improve school autonomy in the United Kingdom.

Keywords: decision making, principals, professional autonomy, school autonomy

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Authors: Siti Aisyah

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This article discusses character education which is a very basic education for early childhood with the aim of instilling moral values to prevent unacceptable behaviours. Children can absorb good character when they are in a supportive environment, for that schools should understand and implement character education in the learning process. In the school environment, good character education and habituation can be developed. All parties in the school should be involved, especially the teachers. This research discusses how teachers apply characters on the values of responsibility, honesty, discipline, love and compassion, caring, courage, independence, hard work, mutual cooperation, courtesy, justice, self-control and tolerance. The respondents of this study were teachers involving 200 children from all over Indonesia. The methodology used was a survey method with the result that more than 80% of teachers have been able to exhibit the expected behaviours. The survey was conducted based on observations, types of tasks and assessed performance. The character values can be optimally taught in the school environment based on the teacher's ability to implement them. Through the character education in schools, children can also instil a positive outlook on life.

Keywords: teachers, character strengthening, early childhood, behavior

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Authors: Shu-Min Tsao, Chung-Ming Lo, Shao-Chun Chen

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Most diabetes patients tend to suffer from its complication of retina diseases. Therefore, early detection and early treatment are important. In clinical examinations, using color fundus image was the most convenient and available examination method. According to the exudates appeared in the retinal image, the status of retina can be confirmed. However, the routine screening of diabetic retinopathy by color fundus images would bring time-consuming tasks to physicians. This study thus proposed a computer-aided exudate diagnosis for the screening of diabetic retinopathy. After removing vessels and optic disc in the retinal image, six quantitative features including region number, region area, and gray-scale values etc… were extracted from the remaining regions for classification. As results, all six features were evaluated to be statistically significant (p-value < 0.001). The accuracy of classifying the retinal images into normal and diabetic retinopathy achieved 82%. Based on this system, the clinical workload could be reduced. The examination procedure may also be improved to be more efficient.

Keywords: computer-aided diagnosis, diabetic retinopathy, exudate, image processing

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Authors: Mariem Kchaou, Wiem Khlif, Faiez Gargouri

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Modeling business processes is an essential task when evaluating, improving, or documenting existing business processes. To be efficient in such tasks, a business process model (BPM) must have high structural quality and high performance. Evidently, evaluating the performance of a business process model is a necessary step to reduce time, cost, while assessing the structural quality aims to improve the understandability and the modifiability of the BPMN model. To achieve these objectives, a set of structural and performance measures have been proposed. Since the diversity of measures, we propose a framework that integrates both structural and performance aspects for classifying them. Our measure classification is based on business process model perspectives (e.g., informational, functional, organizational, behavioral, and temporal), and the elements (activity, event, actor, etc.) involved in computing the measures. Then, we implement this framework in a tool assisting the structural quality and the performance of a business process. The tool helps the designers to select an appropriate subset of measures associated with the corresponding perspective and to calculate and interpret their values in order to improve the structural quality and the performance of the model.

Keywords: performance, structural quality, perspectives, tool, classification framework, measures

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Authors: Seungwon Baek, Haeseok Jeong, Haehyun Lee, Woojin Park

Abstract:

The main purpose of this study was to compare obese people to the non-obese in terms of joint kinematics in lower-limb body. The height of chairs was also considered as a design factor. Obese people had a difficulty in sit-to-stand (STS) tasks compared to the non-obese people. High chair heights can make STS task easy and it helps the obese to be more comfortable with STS task in particular. Subjects were instructed to wear inertial measurement unit (IMU) sensors. They perform STS task using chairs of different heights. Joint kinematics and subjective ratings of discomfort were measured. Knee angles of the obese group were greater than that of the non-obese group in normal type. No significant difference in joint kinematics was found in high chair. Interaction effect was found between obesity and height of chair. The results verified the previous research that had suggested a biomechanical model of STS movement. The results can be applied to occupational design for the obese.

Keywords: biomechanics, electromyography, joint kinematics, obesity, sitting, sit-to-stand

Procedia PDF Downloads 299

Authors: Yared Assefa Demessie

Abstract:

This study may help to establish the appropriateness of ceramic waste aggregate for concrete production since it is obviously understood that the rising from continuous urbanization and industrialization development leads depletion of natural construction resource and the disposal of waste material. It can be used as base to conduct a study on the alternative readily available materials like ceramic industrial waste aggregates can lead to environmental concrete. The study assessed the fresh and hardened properties of the concrete produced by replacing part of the natural fine aggregate with an aggregate produced from ceramic industrial waste. In the study, experimental investigation was employed which involved two major tasks: material specifications and experimental evaluation of concrete were done in the laboratory. Experimental investigations such that workability, unit weight, compressive strength test, tensile strength test and flexural strength test for C-25 concrete mixes with different percentages of ceramic industrial waste aggregate after a curing period of 7 and 28 days has done and interpreted the result statically using mean, standard deviation and coefficient of variance.

Keywords: ceramic industrial waste, fresh concrete, hardened concrete, fine aggregate

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Authors: Linxin Liu

Abstract:

As system complexity increases, log parsing and anomaly detection become more and more important in ensuring system stability. However, traditional methods often face the problems of insufficient adaptability and decreasing accuracy when dealing with rapidly changing log contents and unknown domains. To this end, this paper proposes a distinct approach, LogRAG, which combines RAG (Retrieval Augmented Generation) technology with Prompt Engineering for Large Language Models, applied to log analysis tasks to achieve dynamic parsing of logs and intelligent anomaly detection. By combining real-time information retrieval and prompt optimization, this study significantly improves the adaptive capability of log analysis and the interpretability of results. Experimental results show that the method performs well on several public datasets, especially in the absence of training data, and significantly outperforms traditional methods. This paper provides a different technical path for log parsing and anomaly detection, demonstrating significant theoretical value and application potential.

Keywords: log parsing, anomaly detection, retrieval-augmented generation, prompt engineering, LLMs

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Authors: Yunyong Guo, Sudhakar Ganti, Bryan Guo

Abstract:

The swift proliferation of telehealth Internet of Things (IoT) devices has sparked concerns regarding energy consumption and the need for streamlined data processing. This paper presents an energy-efficient model that integrates telehealth IoT devices into a platform based on fog and cloud computing. This integrated system provides a sustainable and robust solution to address the challenges. Our model strategically utilizes fog computing as a localized data processing layer and leverages cloud computing for resource-intensive tasks, resulting in a significant reduction in overall energy consumption. The incorporation of adaptive energy-saving strategies further enhances the efficiency of our approach. Simulation analysis validates the effectiveness of our model in improving energy efficiency for telehealth IoT systems, particularly when integrated with localized fog nodes and both private and public cloud infrastructures. Subsequent research endeavors will concentrate on refining the energy-saving model, exploring additional functional enhancements, and assessing its broader applicability across various healthcare and industry sectors.

Keywords: energy-efficient, fog computing, IoT, telehealth

Procedia PDF Downloads 72