Search results for: timetable planning

Authors: Kien Vu, Jien Min Soh, Mohamed Jahangir Abubacker, Piyawut Pattamanon, Soojin Lee, Suvro Banerjee

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Recent advances in Generative Artificial Intelligence (GenAI), in particular Large Language Models (LLMs) have shown promise to disrupt multiple industries at scale. However, LLMs also present unique challenges, notably, these so-called "hallucination" which is the generation of outputs that are not grounded in the input data that hinders its adoption into production. Common practice to mitigate hallucination problem is utilizing Retrieval Agmented Generation (RAG) system to ground LLMs'response to ground truth. RAG converts the grounding documents into embeddings, retrieve the relevant parts with vector similarity between user's query and documents, then generates a response that is not only based on its pre-trained knowledge but also on the specific information from the retrieved documents. However, the RAG system is not suitable for tabular data and subsequent data analysis tasks due to multiple reasons such as information loss, data format, and retrieval mechanism. In this study, we have explored a novel methodology that combines planning-and-execution and code generation agents to enhance LLMs' data analysis capabilities. The approach enables LLMs to autonomously dissect a complex analytical task into simpler sub-tasks and requirements, then convert them into executable segments of code. In the final step, it generates the complete response from output of the executed code. When deployed beta version on DataSense, the property insight tool of PropertyGuru, the approach yielded promising results, as it was able to provide market insights and data visualization needs with high accuracy and extensive coverage by abstracting the complexities for real-estate agents and developers from non-programming background. In essence, the methodology not only refines the analytical process but also serves as a strategic tool for real estate professionals, aiding in market understanding and enhancement without the need for programming skills. The implication extends beyond immediate analytics, paving the way for a new era in the real estate industry characterized by efficiency and advanced data utilization.

Keywords: large language model, reasoning, planning and execution, code generation, natural language processing, prompt engineering, data analysis, real estate, data sense, PropertyGuru

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Authors: Raha Bahreini

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This paper discusses the roll-back of women’s sexual and reproductive rights in the Islamic Republic of Iran, which has come in the wake of a striking shift in the country’s official population policies. Since the late 1980s, Iran has won worldwide praise for its sexual and reproductive health and services, which have contributed to a steady decline in the country’s fertility rate–from 7.0 births per women in 1980 to 5.5 in 1988, 2.8 in 1996 and 1.85 in 2014. This is owed to a significant increase in the voluntary use of modern contraception in both rural and urban areas. In 1976, only 37 per cent of women were using at least one method of contraception; by 2014 this figure had reportedly risen to a high of nearly 79 per cent for married girls and women living in urban areas and 73.78 per cent for those living in rural areas. Such progress may soon be halted. In July 2012, Iran’s Supreme Leader Ayatollah Sayed Ali Khamenei denounced Iran’s family planning policies as an imitation of Western lifestyle. He exhorted the authorities to increase Iran’s population to 150 to 200 million (from around 78.5 million), including by cutting subsidies for contraceptive methods and dismantling the state’s Family and Population Planning Programme. Shortly thereafter, Iran’s Minister of Health and Medical Education announced the scrapping of the budget for the state-funded Family and Population Planning Programme. Iran’s Parliament subsequently introduced two bills; the Comprehensive Population and Exaltation of Family Bill (Bill 315), and the Bill to Increase Fertility Rates and Prevent Population Decline (Bill 446). Bill 446 outlaws voluntary tubectomies, which are believed to be the second most common method of modern contraception in Iran, and blocks access to information about contraception, denying women the opportunity to make informed decisions about the number and spacing of their children. Coupled with the elimination of state funding for Iran’s Family and Population Programme, the move would undoubtedly result in greater numbers of unwanted pregnancies, forcing more women to seek illegal and unsafe abortions. Bill 315 proposes various discriminatory measures in the areas of employment, divorce, and protection from domestic violence in order to promote a culture wherein wifedom and child-bearing is seen as women’s primary duty. The Bill, for example, instructs private and public entities to prioritize, in sequence, men with children, married men without children and married women with children when hiring for certain jobs. It also bans the recruitment of single individuals as family law lawyers, public and private school teachers and members of the academic boards of universities and higher education institutes. The paper discusses the consequences of these initiatives which would, if continued, set the human rights of women and girls in Iran back by decades, leaving them with a future shaped by increased inequality, discrimination, poor health, limited choices and restricted freedoms, in breach of Iran’s international human rights obligations.

Keywords: family planning and reproductive health, gender equality and empowerment of women, human rights, population growth

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Authors: Ling Chen, Lanyan Peng

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In the new round of institutional reform of the State Council, Ministry of Culture and Ministry of Tourism were formed into a new department, Ministry of Culture and Tourism, which embodied the idea of the fusion development of cultural and tourism industries. At the same time, domestic tourists pay more attention to the tourism experience and tourism quality. The tourism patterns have been changed from the sightseeing mode of the individual scenic spot to the lifestyle mode of feeling the cultural atmosphere of the tourist destination. Therefore, this paper focuses on the tourism pattern based on lifestyle, studies the development status, content, and implementation measures of the tourism pattern. As the tourism pattern based on lifestyle integrating cultural and tourism industries in-depth, tourists can experience the living atmosphere, living conditions and living quality of the tourist destination, and deeply understand the urban cultural connotation during the trip. Suzhou has taken a series of measures to build up a tourism pattern based on lifestyle-'Suzhou life' tourism, including regional planning of tourism, integration of cultural resources, construction of urban atmosphere, and upgrading infrastructure. 'Suzhou life' tourism is based on the Suzhou food (cooked wheaten food, dim sum, specialty snacks), tourist attractions (Suzhou gardens, the ancient city) and characteristic recreational ways (appreciating Kun opera, enjoying Suzhou Pingtan, tea drinking). And the continuous integration of the three components above meet the spiritual, cultural needs of tourists and upgrade the tourism pattern based on lifestyle. Finally, the paper puts forward the tourism pattern planning suggestions.

Keywords: tourism pattern, lifestyle, integration of cultural and tourism industries, Suzhou life

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Authors: John Hardy

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A range of future-oriented intelligence techniques is commonly used by states to assess their national security and develop strategies to detect and manage threats, to develop and sustain capabilities, and to recover from attacks and disasters. Although homeland security organizations use future's intelligence tools to generate scenarios and simulations which inform their planning, there have been relatively few studies of the methods available or their applications for homeland security purposes. This study presents an assessment of one category of strategic intelligence techniques, termed Multi-Path Futures Analyses (MPFA), and how it can be applied to three distinct tasks for the purpose of analyzing homeland security issues. Within this study, MPFA are categorized as a suite of analytic techniques which can include effects-based operations principles, general morphological analysis, multi-path mapping, and multi-criteria decision analysis techniques. These techniques generate multiple pathways to potential futures and thereby generate insight into the relative influence of individual drivers of change, the desirability of particular combinations of pathways, and the kinds of capabilities which may be required to influence or mitigate certain outcomes. The study assessed eighteen uses of MPFA for homeland security purposes and found that there are five key applications of MPFA which add significant value to analysis. The first application is generating measures of success and associated progress indicators for strategic planning. The second application is identifying homeland security vulnerabilities and relationships between individual drivers of vulnerability which may amplify or dampen their effects. The third application is selecting appropriate resources and methods of action to influence individual drivers. The fourth application is prioritizing and optimizing path selection preferences and decisions. The fifth application is informing capability development and procurement decisions to build and sustain homeland security organizations. Each of these applications provides a unique perspective of a homeland security issue by comparing a range of potential future outcomes at a set number of intervals and by contrasting the relative resource requirements, opportunity costs, and effectiveness measures of alternative courses of action. These findings indicate that MPFA enhances analysts’ ability to generate tangible measures of success, identify vulnerabilities, select effective courses of action, prioritize future pathway preferences, and contribute to ongoing capability development in homeland security assessments.

Keywords: homeland security, intelligence, national security, operational design, strategic intelligence, strategic planning

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Authors: Yingxiao Ye, Christopher Doehring, Angelos Georghiou, Hugh Robinson, Phebe Vayanos

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Human development is a threat to biodiversity, and conservation organizations (COs) are purchasing land to protect areas for biodiversity preservation. However, COs have limited budgets and thus face hard prioritization decisions that are confounded by uncertainty in future human land use. This research proposes a data-driven sequential planning model to help COs choose land parcels that minimize the uncertain human impact on biodiversity. The proposed model is robust to uncertain development, and the sequential decision-making process is adaptive, allowing land purchase decisions to adapt to human land use as it unfolds. The cellular automata model is leveraged to simulate land use development based on climate data, land characteristics, and development threat index from NASA Socioeconomic Data and Applications Center. This simulation is used to model uncertainty in the problem. This research leverages state-of-the-art techniques in the robust optimization literature to propose a computationally tractable reformulation of the model, which can be solved routinely by off-the-shelf solvers like Gurobi or CPLEX. Numerical results based on real data from the Jaguar in Central and South America show that the proposed method reduces conservation loss by 19.46% on average compared to standard approaches such as MARXAN used in practice for biodiversity conservation. Our method may better help guide the decision process in land acquisition and thereby allow conservation organizations to maximize the impact of limited resources.

Keywords: data-driven robust optimization, biodiversity conservation, uncertainty simulation, adaptive sequential planning

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Authors: Néstor Iván Rojas, Wilson Medina Sierra

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Managing spatial information is described through a Geographic Information System (GIS), for some neighborhoods in the city of Tunja, in relation to the structural typology of the buildings. The use of GIS provides tools that facilitate the capture, processing, analysis and dissemination of cartographic information, product quality evaluation of the classification of buildings. Allows the development of a method that unifies and standardizes processes information. The project aims to generate a geographic database that is useful to the entities responsible for planning and disaster prevention and care for vulnerable populations, also seeks to be a basis for seismic vulnerability studies that can contribute in a study of urban seismic microzonation. The methodology consists in capturing the plat including road naming, neighborhoods, blocks and buildings, to which were added as attributes, the product of the evaluation of each of the housing data such as the number of inhabitants and classification, year of construction, the predominant structural systems, the type of mezzanine board and state of favorability, the presence of geo-technical problems, the type of cover, the use of each building, damage to structural and non-structural elements . The above data are tabulated in a spreadsheet that includes cadastral number, through which are systematically included in the respective building that also has that attribute. Geo-referenced data base is obtained, from which graphical outputs are generated, producing thematic maps for each evaluated data, which clearly show the spatial distribution of the information obtained. Using GIS offers important advantages for spatial information management and facilitates consultation and update. Usefulness of the project is recognized as a basis for studies on issues of planning and prevention.

Keywords: microzonation, buildings, geo-processing, cadastral number

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Authors: Dipendra Kumar Yadav, Rajani Ghimire, Saroj Yadav

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Background: The concern about adolescent on reproductive health has grown due to unprecedented increasing rates of early pregnancies and sexually transmitted Infections and they do not have adequate awareness and knowledge about it. Access to these services as well as information about them is, therefore, crucial for adolescents to utilize and benefit from sexual and reproductive health services. The objective of the study was to assess the reproductive health knowledge, attitude and health services utilization among adolescents in rural and urban areas of Kaski district. Materials and Methods: A community-based descriptive cross-sectional study was conducted among adolescents (10-19 years of age) in rural and urban areas of Kaski district, Nepal. The period of data collection was October to November, 2014. Altogether 419 participants were taken for the study. Results: The mean age of the respondents was 15.86 and standard deviation was ±2.305. More than half (58.7 %) of the respondents were females and 41.3 % were males. Out of 419, majority (78.8%) of the respondents were known about family planning, among them only 70 % of respondents were aware about family planning methods. Fifty-one percentages of the respondents were aware about the sexually transmitted diseases. Before giving a birth there is need to consult with partner with this fact 68.7 % of the respondents were agree, 23.6 % of them were neutral and very few (7.6%) of them were disagree. Nearly twenty six percentage of the respondents were faced the reproductive health problems within one month. Out of 107 respondents, 57.9 % did not utilize reproductive health services because of different reasons. Conclusions: The overall level of knowledge towards reproductive health among adolescents was found low. However, levels of attitude towards different reproductive health components were found favorable. Only 42.1% of the respondents were utilized reproductive health services among those who was faced the reproductive health problems within one month which was low coverage of reproductive health services utilization.

Keywords: reproductive health knowledge, reproductive health attitudes, adolescent, service utilization

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Authors: Vilar, Katila

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Rapid urbanization have made of spontaneous settlements one of the dominant´s social subjects of the XXIst century. Currently, it´s recognized that these territories cannot easily be eradicated and are a way of life to many populations of emergent countries. Since late 90s, there is an urgent concern in finding planning and efficient urban design strategies to poverty reduction, spatial integration and social inclusion of low-income communities. The article aims to identify, understand and evaluate the social inclusion´s processes through the urban transformation that has been undertaken in Moravia and how they affected the community´s social capital. To achieve this objective, we start to analyse the PPMIM´s planning discourse in which prevails the sustainability´s concept, to further identify, through the analysis of the project carried out, the urban design strategies implemented and their impact on the perception and on the community´s experience, and, finally, how these focused on the social capital. It relies on concepts such as urban design, social capital, local development and sustainability. At the urban design level it starts on the current principles of “making places”, on the new urbanism concepts and on the practices on the ground carried out by a new generation of architects/planners whose have the main ethical approach in order to create more opportunities and greater social impact to these territories. At the social capital´s level and on the development´s theory, relies on authors such as Coleman, Putman Kliksberg and Amartya Sen. Finally, it aims to address a general discussion about the positive and negative implications of slum upgrading programmes and some necessary recommendations for urban design and social capital can really be translated into real resources for the self sustainable development of low-income communities and their future generations.

Keywords: local and sustainable development, social capital, spontaneous settlements, urban design

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Authors: Zeynep Guler

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Argumentation and the production of scientific arguments are essential components that are necessary for helping students become scientifically literate through engaging them in constructing and critiquing ideas. Incorporating argumentation into science classrooms is challenging and can be a long-term process for both students and teachers. Students have difficulty in engaging tasks that require them to craft arguments, evaluate them to seek weaknesses, and revise them. Teachers also struggle with facilitating argumentation when they have underdeveloped science practices, underdeveloped pedagogical knowledge for argumentation science teaching, or underdeveloped teaching practice with argumentation (or a combination of all three). Thus, there is a need to support teachers in developing pedagogy for science teaching as argumentation, planning and implementing teaching practice for facilitating argumentation and also in becoming more agentic in this regards. Looking specifically at the experience of agency within education, it is arguable that agency is necessary for teachers’ renegotiation of professional purposes and practices in the light of changing educational practices. This study investigated how science teachers develop pedagogy for argumentation both individually and with their colleagues and also how teachers become more agentic (or not) through the active engagement of their contexts-for-action that refer to this as an ecological understanding of agency in order to positively influence or change their practice and their students' engagement with argumentation over two academic years. Through educational design study, this study conducted with three secondary science teachers (key stage 3-year 7 students aged 11-12) in the UK to find out if similar or different patterns of developing pedagogy for argumentation and of becoming more agentic emerge as they engage in planning and implementing a cycle of activities during the practice of teaching science with argumentation. Data from video and audio-recording of classroom practice and open-ended interviews with the science teachers were analysed using content analysis. The findings indicated that all the science teachers perceived strong agency in their opportunities to develop and apply pedagogical practices within the classroom. The teachers were pro-actively shaping their practices and classroom contexts in ways that were over and above the amendments to their pedagogy. They demonstrated some outcomes in developing pedagogy for argumentation and becoming more agentic in their teaching in this regards as a result of the collaboration with their colleagues and researcher; some appeared more agentic than others. The role of the collaboration between their colleagues was seen crucial for the teachers’ practice in the schools: close collaboration and support from other teachers in planning and implementing new educational innovations were seen as crucial for the development of pedagogy and becoming more agentic in practice. They needed to understand the importance of scientific argumentation but also understand how it can be planned and integrated into classroom practice. They also perceived constraint emerged from their lack of competence and knowledge in posing appropriate questions to help the students engage in argumentation, providing support for the students' construction of oral and written arguments.

Keywords: argumentation, teacher professional development, teacher agency, students' construction of argument

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Authors: Rui Serôdio, Alexandra Serra, José Albino Lima, Luísa Catita, Paula Lopes

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We will present the outline of the Project SIA (Social Inclusion through Accessibility) focusing in one of its core components: how our applied research model contributes to define community participation as a pillar for strategic and political agenda amongst local authorities. Project ISA, supported by EU regional funding, was design as part of a broader model developed by SIMLab–Social Inclusion Monitoring Laboratory, in which the relation University-Community is a core element. The project illustrates how University of Porto developed a large scale project of applied psychology research in a close partnership with 18 municipalities that cover almost all regions of Portugal, and with a private architecture enterprise, specialized in inclusive accessibility and “design for all”. Three fundamental goals were defined: (1) creation of a model that would promote the effective civic participation of local citizens; (2) the “voice” of such participation should be both individual and collective; (3) the scientific and technical framework should serve as one of the bases for political decision on inclusive accessibility local planning. The two main studies were run in a standardized model across all municipalities and the samples of the three modalities of community participation were the following: individual participation based on 543 semi-structured interviews and 6373 inquiries; collective participation based on group session with 302 local citizens. We present some of the broader findings of Project SIA and discuss how they relate to our applied research model.

Keywords: applied psychology, collective identity, community participation, inclusive accessibility

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Authors: Agada N. Ihuoma, Nagata Yasunori

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Artificial intelligence (AI) techniques play a crucial role in predicting the expected energy outcome and its performance, analysis, modeling, and control of renewable energy. Renewable energy is becoming more popular for economic and environmental reasons. In the face of global energy consumption and increased depletion of most fossil fuels, the world is faced with the challenges of meeting the ever-increasing energy demands. Therefore, incorporating artificial intelligence to predict solar radiation outcomes from the intermittent sunlight is crucial to enable a balance between supply and demand of energy on loads, predict the performance and outcome of solar energy, enhance production planning and energy management, and ensure proper sizing of parameters when generating clean energy. However, one of the major problems of forecasting is the algorithms used to control, model, and predict performances of the energy systems, which are complicated and involves large computer power, differential equations, and time series. Also, having unreliable data (poor quality) for solar radiation over a geographical location as well as insufficient long series can be a bottleneck to actualization. To overcome these problems, this study employs the anaconda Navigator (Jupyter Notebook) for machine learning which can combine larger amounts of data with fast, iterative processing and intelligent algorithms allowing the software to learn automatically from patterns or features to predict the performance and outcome of Solar Energy which in turns enables the balance of supply and demand on loads as well as enhance production planning and energy management.

Keywords: artificial Intelligence, backward elimination, linear regression, solar energy

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Authors: C. Salis, D. Zedda, M. F. Wilson

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The IDEA project was conceived for teachers who are interested in enhancing their capacity to effectively implement the use of specific technologies in their teaching practice. Participating teachers are coached and supported as they explore technologies applied to the educational context. They access tools such as the technological platform developed by our team. Among the platform functionalities, teachers access an instructional systems design (ISD) tool (learning designer) that was adapted to the needs of our project. The tool is accessible from computers or mobile devices and used in association with other technologies to create new, meaningful learning environments. The objective of an instructional systems design is to guarantee the quality and effectiveness of education and to enhance learning. This goal involves both teachers who want to become more efficient in transferring knowledge or skills and students as the final recipient of their teaching. The use of Blooms’s taxonomy enables teachers to classify the learning objectives into levels of complexity and specificity, thus making it possible to highlight the kind of knowledge teachers would like their students to reach. The fact that the instructional design features can be visualized through the IDEA platform is a guarantee for those who are looking for specific educational materials to be used in their lessons. Despite the benefits offered, a number of teachers are reluctant to use ISD because the preparatory work of having to thoroughly analyze the teaching/learning objectives, the planning of learning material, assessment activities, etc., is long and felt to be time-consuming. This drawback is minimized using a learning designer, as the tool facilitates to reuse of the didactic contents having a clear view of the processes of analysis, planning, and production of educational or testing materials uploaded on our platform. In this paper, we shall present the feedback of the teachers who used our tool in their didactic.

Keywords: educational benefits, educational quality, educational technology, ISD tool

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Authors: Asghar Zamani, Mostafa Falahmorad

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Virtualization is established to combine and use the unique capabilities of employees to increase productivity and agility to provide services regardless of location. Adapting to fast and continuous change and getting maximum access to human resources are reasons why virtualization is happening. The distance problem is solved by information. Flexibility is the most important feature of virtualization, and information will be the main focus of virtualized companies. In this research, we used the Covid-19 opportunity window to assess the productivity of the companies that had been going through more virtualized management before the Covid-19 in comparison with those that just started planning on developing infrastructures on virtual management after the crises of pandemic occurred. The research process includes financial (profitability and customer satisfaction) and behavioral (organizational culture and reluctance to change) metrics assessment. In addition to financial and CRM KPIs, a questionnaire is devised to assess how manager and employees’ attitude has been changing towards the migration to virtualization. The sample companies and questions are selected by asking from experts in the IT industry of Iran. In this article, the conclusion is that companies open to virtualization based on accurate strategic planning or willing to pay to train their employees for virtualization before the pandemic are more agile in adapting to change and moving forward in recession. The prospective companies in this research, not only could compensate for the short period loss from the first shock of the Covid-19, but they could also foresee new needs of their customer sooner than other competitors, resulting in the need to employ new staff for executing the emerging demands. Findings were aligned with the literature review. Results can be a wake-up call for business owners especially in developing countries to be more resilient toward modern management styles instead of continuing with traditional ones.

Keywords: virtual management, virtual organization, competitive advantage, KPI, profit

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Authors: Saori Fujimoto, Hiromi Kawasaki, Mari Murakami, Yoko Ueno

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Background: Coronavirus disease (COVID-19) has been spreading throughout the world. In Japan, many nursing universities have conducted online clinical practices to secure students’ learning opportunities. In the field of women’s health nursing, even after the pandemic ended, it will be worthwhile to utilize online practice in declining birthrate and reducing the burden of mothers. This study examined the learning effects of conducting online visits for mothers with infants during the COVID-19 pandemic by nursing students to enhance the students’ ability to carry out the online practice even in ordinary times effectively. Methods: Students were divided into groups of three, and information on the mothers was assessed, and the visits were planned. After role-play was conducted by the students and teachers, an online visit was conducted. The analysis target was the self-evaluation score of nine students who conducted online visits in June 2020 and had consented to participate. The evaluation contents included three items for assessment, two items for planning, one item for ethical consideration, five items for nursing practice, and two items for evaluation. The self-evaluation score ranged from 4 (‘Can do with a little advice’) to 1 (‘Can’t do with a little advice’). A univariate statistical analysis was performed. This study was approved by the Ethical Committee for Epidemiology of Hiroshima University. Results: The items with the highest mean (standard deviation) scores were ‘advocates for the dignity and the rights of mothers’ (3.89 (0.31)) and ‘communication behavior needed to create a trusting relationship’ (3.89 (0.31)).’ Next were the ‘individual nursing practice tailored to mothers (3.78 (0.42))’ and ‘review own practice and work on own task (3.78 (0.42)).’ The mean (standard deviation) of the items by type were as follows: three assessment items, 3.26 (0.70), two planning items, 3.11 (0.49), one ethical consideration item, 3.89 (0.31), five nursing practice items, 3.56 (0.54), and two evaluation items, 3.67 (0.47). Conclusion: The highest self-evaluations were for ‘advocates for the dignity and the rights of mothers’ and ‘communication behavior needed to create a trusting relationship.’ These findings suggest that the students were able to form good relationships with the mothers by improving their ability to effectively communicate and by presenting a positive attitude, even when conducting health visits online. However, the self-evaluation scores for assessment and planning were lower than those of ethical consideration, nursing practice, and evaluation. This was most likely due to a lack of opportunities and time to gather information and the need to modify and add plans in a short amount of time during one online visit. It is necessary to further consider the methods used in conducting online visits from the following viewpoints: methods of gathering information and the ability to make changes through multiple visits.

Keywords: infants, learning effects, mothers, online visit practice

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Authors: Jerzy Banski

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Small towns represent a key element of settlement structure and serve a number of important functions associated with the servicing of rural areas that surround them. It is in light of this that scientific studies have paid considerable attention to the functional structure of centers of this kind, as well as the relationships with both surrounding rural areas and other urban centers. But a preliminary to such research has typically involved attempts at classifying the urban centers themselves, with this also assisting with the planning and shaping of development policy on different spatial scales. The purpose of the work is to test out the methods underpinning three different classifications of small urban centers, as well as to offer a preliminary interpretation of the outcomes obtained. Research took in 722 settlement units in Poland, granted town rights and populated by fewer than 20,000 inhabitants. A morphologically-based classification making reference to the database of topographic objects as regards land cover within the administrative boundaries of towns and cities was carried out, and it proved possible to distinguish the categories of “housing-estate”, industrial and R&R towns, as well as towns characterized by dichotomy. Equally, a functional/morphological approach taken with the same database allowed for the identification – via an alternative method – of three main categories of small towns (i.e., the monofunctional, multifunctional or oligo functional), which could then be described in far greater detail. A third, multi-criterion classification made simultaneous reference to the conditioning of a structural, a location-related, and an administrative hierarchy-related nature, allowing for distinctions to be drawn between small towns in 9 different categories. The results obtained allow for multifaceted analysis and interpretation of the geographical differentiation characterizing the distribution of Poland’s urban centers across space in the country.

Keywords: small towns, classification, local planning, Poland

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Authors: Beatriz González-rodrigo, Diego Hidalgo-leiva, Omar Flores, Claudia Germoso, Maribel Jiménez-martínez, Laura Navas-sánchez, Belén Orta, Nicola Tarque, Orlando Hernández- Rubio, Miguel Marchamalo, Juan Gregorio Rejas, Belén Benito-oterino

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Cities facing seismic hazard necessitate detailed risk assessments for effective urban planning and vulnerability identification, ensuring the safety and sustainability of urban infrastructure. Comprehensive studies involving seismic hazard, vulnerability, and exposure evaluations are pivotal for estimating potential losses and guiding proactive measures against seismic events. However, broad-scale traditional risk studies limit consideration of specific local threats and identify vulnerable housing within a structural typology. Achieving precise results at neighbourhood levels demands higher resolution seismic hazard exposure, and vulnerability studies. This research aims to bolster sustainability and safety against seismic disasters in three Central American and Caribbean capitals. It integrates geospatial techniques and artificial intelligence into seismic risk studies, proposing cost-effective methods for exposure data collection and damage prediction. The methodology relies on prior seismic threat studies in pilot zones, utilizing existing exposure and vulnerability data in the region. Emphasizing detailed building attributes enables the consideration of behaviour modifiers affecting seismic response. The approach aims to generate detailed risk scenarios, facilitating prioritization of preventive actions pre-, during, and post-seismic events, enhancing decision-making certainty. Detailed risk scenarios necessitate substantial investment in fieldwork, training, research, and methodology development. Regional cooperation becomes crucial given similar seismic threats, urban planning, and construction systems among involved countries. The outcomes hold significance for emergency planning and national and regional construction regulations. The success of this methodology depends on cooperation, investment, and innovative approaches, offering insights and lessons applicable to regions facing moderate seismic threats with vulnerable constructions. Thus, this framework aims to fortify resilience in seismic-prone areas and serves as a reference for global urban planning and disaster management strategies. In conclusion, this research proposes a comprehensive framework for seismic risk assessment in high-risk urban areas, emphasizing detailed studies at finer resolutions for precise vulnerability evaluations. The approach integrates regional cooperation, geospatial technologies, and adaptive fragility curve adjustments to enhance risk assessment accuracy, guiding effective mitigation strategies and emergency management plans.

Keywords: assessment, behaviour modifiers, emergency management, mitigation strategies, resilience, vulnerability

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Authors: Srinivas Peri, Siva Abhishek Sirivella, Tejaswini Kallakuri, Uzair Ahmad

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Effective traffic management and infrastructure planning are crucial for the development of smart cities and intelligent transportation systems. This study addresses the challenge of data scarcity by generating realistic synthetic traffic data using the PeMS-Bay dataset, improving the accuracy and reliability of predictive modeling. Advanced synthetic data generation techniques, including TimeGAN, GaussianCopula, and PAR Synthesizer, are employed to produce synthetic data that replicates the statistical and structural characteristics of real-world traffic. Future integration of Spatial-Temporal Generative Adversarial Networks (ST-GAN) is planned to capture both spatial and temporal correlations, further improving data quality and realism. The performance of each synthetic data generation model is evaluated against real-world data to identify the best models for accurately replicating traffic patterns. Long Short-Term Memory (LSTM) networks are utilized to model and predict complex temporal dependencies within traffic patterns. This comprehensive approach aims to pinpoint areas with low vehicle counts, uncover underlying traffic issues, and inform targeted infrastructure interventions. By combining GAN-based synthetic data generation with LSTM-based traffic modeling, this study supports data-driven decision-making that enhances urban mobility, safety, and the overall efficiency of city planning initiatives.

Keywords: GAN, long short-term memory, synthetic data generation, traffic management

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Authors: Sadaf Saeed

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The consideration of walkability as an urban design parameter in conjunction with transit-oriented development is an established trend in the developed countries but an upcoming trend in developing countries. In Pakistan, the first Bus Rapid Transit (locally called as Metro Bus) has been introduced in the city of Lahore in 2013 where around 40 percent of the riders access to transit stations by walking. To what extent the aspect of walkability has been considered in the local scenario? To address this question, this paper presents an account of urban design parameters regarding pedestrian provisions and quality of walking environment between Metro Bus stations and users’ destination in the transit neighbourhoods (areas up to 500-meter radius). The primary and secondary data for objective and subjective walkability measurements has been used for neighbourhoods of five selected transit stations ranked against the predefined critical assessed factors (CAF). The multi-criteria approach including visual and geospatially-based parameters at street level, along with walkability index score at selected sites linked with CAF evaluation were the selected methods for this study. The acceptability of walkability as an urban design parameter for transit planning in terms of connectivity and social implications of the concept has also been analysed in the local context. The paper highlights that the aspect of walkability in Lahore is being derelict owing to the focus of government on other initiatives such as park and ride and feeder bus services for mobility of passengers. However, the pedestrian-friendly design parameters as a part of future transit planning can enhance social, liveable and interactive walking environment within transit neighbourhoods.

Keywords: walkability, sustainability, transit neighborhoods, social communities

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Authors: Loyd R. Hook, Maryam Moharek

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With the envisioned future growth of low altitude urban aircraft operations for airborne delivery service and advanced air mobility, strategies to coordinate and deconflict aircraft flight paths must be prioritized. Autonomous coordination and planning of flight trajectories is the preferred approach to the future vision in order to increase safety, density, and efficiency over manual methods employed today. Difficulties arise because any conflict resolution must be constrained by all other aircraft, all airspace restrictions, and all ground-based obstacles in the vicinity. These considerations make pair-wise tactical deconfliction difficult at best and unlikely to find a suitable solution for the entire system of vehicles. In addition, more traditional methods which rely on long time scales and large protected zones will artificially limit vehicle density and drastically decrease efficiency. Instead, strategic planning, which is able to respond to highly dynamic conditions and still account for high density operations, will be required to coordinate multiple vehicles in the highly constrained low altitude urban environment. This paper develops and evaluates such a planning algorithm which can be implemented autonomously across multiple aircraft and situations. Data from this evaluation provide promising results with simulations showing up to 10 aircraft deconflicted through a relatively narrow low-altitude urban canyon without any vehicle to vehicle or obstacle conflict. The algorithm achieves this level of coordination beginning with the assumption that each vehicle is controlled to follow an independently constructed flight path, which is itself free of obstacle conflict and restricted airspace. Then, by preferencing speed change deconfliction maneuvers constrained by the vehicles flight envelope, vehicles can remain as close to the original planned path and prevent cascading vehicle to vehicle conflicts. Performing the search for a set of commands which can simultaneously ensure separation for each pair-wise aircraft interaction and optimize the total velocities of all the aircraft is further complicated by the fact that each aircraft's flight plan could contain multiple segments. This means that relative velocities will change when any aircraft achieves a waypoint and changes course. Additionally, the timing of when that aircraft will achieve a waypoint (or, more directly, the order upon which all of the aircraft will achieve their respective waypoints) will change with the commanded speed. Put all together, the continuous relative velocity of each vehicle pair and the discretized change in relative velocity at waypoints resembles a hybrid reachability problem - a form of control reachability. This paper proposes two methods for finding solutions to these multi-body problems. First, an analytical formulation of the continuous problem is developed with an exhaustive search of the combined state space. However, because of computational complexity, this technique is only computable for pairwise interactions. For more complicated scenarios, including the proposed 10 vehicle example, a discretized search space is used, and a depth-first search with early stopping is employed to find the first solution that solves the constraints.

Keywords: strategic planning, autonomous, aircraft, deconfliction

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Authors: Antonella Falanga, Armando Cartenì

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Today, an unprecedented amount of data coming from several sources, including mobile devices, sensors, tracking systems, and online platforms, characterizes our lives. The term “big data” not only refers to the quantity of data but also to the variety and speed of data generation. These data hold valuable insights that, when extracted and analyzed, facilitate informed decision-making. The 4Vs of big data - velocity, volume, variety, and value - highlight essential aspects, showcasing the rapid generation, vast quantities, diverse sources, and potential value addition of these kinds of data. This surge of information has revolutionized many sectors, such as business for improving decision-making processes, healthcare for clinical record analysis and medical research, education for enhancing teaching methodologies, agriculture for optimizing crop management, finance for risk assessment and fraud detection, media and entertainment for personalized content recommendations, emergency for a real-time response during crisis/events, and also mobility for the urban planning and for the design/management of public and private transport services. Big data's pervasive impact enhances societal aspects, elevating the quality of life, service efficiency, and problem-solving capacities. However, during this transformative era, new challenges arise, including data quality, privacy, data security, cybersecurity, interoperability, the need for advanced infrastructures, and staff training. Within the transportation sector (the one investigated in this research), applications span planning, designing, and managing systems and mobility services. Among the most common big data applications within the transport sector are, for example, real-time traffic monitoring, bus/freight vehicle route optimization, vehicle maintenance, road safety and all the autonomous and connected vehicles applications. Benefits include a reduction in travel times, road accidents and pollutant emissions. Within these issues, the proper transport demand estimation is crucial for sustainable transportation planning. Evaluating the impact of sustainable mobility policies starts with a quantitative analysis of travel demand. Achieving transportation decarbonization goals hinges on precise estimations of demand for individual transport modes. Emerging technologies, offering substantial big data at lower costs than traditional methods, play a pivotal role in this context. Starting from these considerations, this study explores the usefulness impact of big data within transport demand estimation. This research focuses on leveraging (big) data collected during the COVID-19 pandemic to estimate the evolution of the mobility demand in Italy. Estimation results reveal in the post-COVID-19 era, more than 96 million national daily trips, about 2.6 trips per capita, with a mobile population of more than 37.6 million Italian travelers per day. Overall, this research allows us to conclude that big data better enhances rational decision-making for mobility demand estimation, which is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, cloud computing, decision-making, mobility demand, transportation

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Authors: Verd Shomrom, Gilat Trabelsi

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The goal of the study was to examine the effects of Computerized Cognitive Training (CCT) with and without cognitive mediation on Executive Function (EF) (planning and self- regulation) and on psychological resiliency among adolescents with Attention Deficits Hyperactive Disorder (ADHD) with or without Learning Disabilities (LD). Adolescents diagnosed with Attention Deficit Disorder and / or Learning Disabilities have multidimensional impairments that result from neurological damage. This work explored the possibility of influencing cognitive aspects in the field of Executive Functions (specifically: patterns of planning and self-regulation) among adolescents with a diagnosis of Attention Deficit Disorder and / or Learning Disabilities who study for a 10-12 grades. 46 adolescents with ADHD and/or with LD were randomly applied to experimental and control groups. All the participants were tested (BRC- research version, Resiliency quaternaries) before and after the intervention: mediated/ non-mediated Computerized Cognitive Training (MINDRI). The results indicated significant effects of cognitive modification in the experimental group, between pre and post Phases, in comparison to control group, especially in self- regulation (BRC- research version, Resiliency quaternaries), and on process analysis of Computerized Cognitive Training (MINDRI). The main conclusion was that even short- term mediation synchronized with CCT could greatly enhance the performance of executive functions demands. Theoretical implications for the positive effects of MLE in combination with CCT indicate the ability for cognitive change. The practical implication is the awareness and understanding of efficient intervention processes to enhance EF, learning awareness, resiliency and self-esteem of adolescents in their academic and daily routine.

Keywords: attention deficits hyperactive disorder, computerized cognitive training, executive function, mediated learning experience, learning disabilities

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Authors: Bruna C. Brasileiro, José Alberto S. Sá, Brigida R. P. Rocha

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The Amazon region development was related to large-scale projects associated with economic cycles. Economic cycles were originated from policies implemented by successive governments that exploited the resources and have not yet been able to improve the local population's quality of life. These implanted development strategies were based on vertical planning centered on State that didn’t know and showed no interest in know the local needs and potentialities. The future of this region is a challenge that depends on a model of development based on human progress associated to intelligent, selective and environmentally safe exploitation of natural resources settled in renewable and no-polluting energy generation sources – a differential factor of attraction of new investments in a context of global energy and environmental crisis. In this process the planning and support of Brazilian State, local government, and selective international partnership are essential. Residual biomass utilization allows the sustainable development by the integration of production chain and energy generation process which could improve employment condition and income of riversides. Therefore, this research discourses how the use of local residual biomass (açaí lumps) could be an important instrument of sustainable development for isolated communities located at Alcobaça Sustainable Development Reserve (SDR), Tucuruí, Pará State, since in this region the energy source more accessible for who can pay are the fossil fuels that reaches about 54% of final energy consumption by the integration between the açaí productive chain and the use of renewable energy source besides it can promote less environmental impact and decrease the use of fossil fuels and carbon dioxide emissions.

Keywords: Amazon, biomass, renewable energy, sustainability

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Authors: Mohamed Abdalla Elamein Boshara, Peter Charles Woods, Nour Eldin Mohamed Elshaiekh

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Knowledge Management has become very important for Disaster Management response and planning. This paper proposes the implementation of a Knowledge Management System with a sustainable data collection mechanism for reliable and timely information management to support decision makers in making the right decisions in the timely manner.

Keywords: knowledge management, disaster management, incident tracking, web application

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Authors: Migael van Zyl, Stefanie Visser, Awelani Phaswana

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The electricity landscape in South Africa is characterized by frequent occurrences of loadshedding, a measure implemented by Eskom to manage electricity generation shortages by curtailing demand. Loadshedding, classified into stages ranging from 1 to 8 based on severity, involves the systematic rotation of power cuts across municipalities according to predefined schedules. However, this practice introduces distortions in recorded electricity demand, posing challenges to accurate forecasting essential for budgeting, network planning, and generation scheduling. Addressing this challenge requires the development of a methodology to quantify the impact of loadshedding and integrate it back into metered electricity demand data. Fortunately, comprehensive records of loadshedding impacts are maintained in a database, enabling the alignment of Loadshedding effects with hourly demand data. This adjustment ensures that forecasts accurately reflect true demand patterns, independent of loadshedding's influence, thereby enhancing the reliability of electricity supply management in South Africa. This paper presents a methodology for determining the hourly impact of load scheduling and subsequently adjusting historical demand data to account for it. Furthermore, two forecasting models are developed: one utilizing the original dataset and the other using the adjusted data. A comparative analysis is conducted to evaluate forecast accuracy improvements resulting from the adjustment process. By implementing this methodology, stakeholders can make more informed decisions regarding electricity infrastructure investments, resource allocation, and operational planning, contributing to the overall stability and efficiency of South Africa's electricity supply system.

Keywords: electricity demand forecasting, load shedding, demand side management, data science

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Authors: Neha Pranav Kolhe, Harithapriya Vijaye, Arushi Kamle

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The economic growth engines are urban regions. As the economy expands, so does the need for peace and quiet, and noise pollution is one of the important social and environmental issue. Health and wellbeing are at risk from environmental noise pollution. Because of urbanisation, population growth, and the consequent rise in the usage of increasingly potent, diverse, and highly mobile sources of noise, it is now more severe and pervasive than ever before, and it will only become worse. Additionally, it will expand as long as there is an increase in air, train, and highway traffic, which continue to be the main contributors of noise pollution. The current study will be conducted in two zones of class I city of central India (population range: 1 million–4 million). Total 56 measuring points were chosen to assess noise pollution. The first objective evaluates the noise pollution in various urban habitats determined as formal and informal settlement. It identifies the comparison of noise pollution within the settlements using T- Test analysis. The second objective assess the noise pollution in silent zones (as stated in Central Pollution Control Board) in a hierarchical way. It also assesses the noise pollution in the settlements and compares with prescribed permissible limits using class I sound level equipment. As appropriate indices, equivalent noise level on the (A) frequency weighting network, minimum sound pressure level and maximum sound pressure level were computed. The survey is conducted for a period of 1 week. Arc GIS is used to plot and map the temporal and spatial variability in urban settings. It is discovered that noise levels at most stations, particularly at heavily trafficked crossroads and subway stations, were significantly different and higher than acceptable limits and squares. The study highlights the vulnerable areas that should be considered while city planning. The study demands area level planning while preparing a development plan. It also demands attention to noise pollution from the perspective of residential and silent zones. The city planning in urban areas neglects the noise pollution assessment at city level. This contributes to that, irrespective of noise pollution guidelines, the ground reality is far away from its applicability. The result produces incompatible land use on a neighbourhood scale with respect to noise pollution. The study's final results will be useful to policymakers, architects and administrators in developing countries. This will be useful for noise pollution in urban habitat governance by efficient decision making and policy formulation to increase the profitability of these systems.

Keywords: noise pollution, formal settlements, informal settlements, built environment, silent zone, residential area

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Authors: Naci Büyükkaracığan

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Hydroclimatic observation values ​​are used in the planning of the project of water resources. Climate variables are the first of the values ​​used in planning projects. At the same time, the climate system is a complex and interactive system involving the atmosphere, land surfaces, snow and bubbles, the oceans and other water structures. The amount and distribution of precipitation, which is an important climate parameter, is a limiting environmental factor for dispersed living things. Trend analysis is applied to the detection of the presence of a pattern or trend in the data set. Many trends work in different parts of the world are usually made for the determination of climate change. The detection and attribution of past trends and variability in climatic variables is essential for explaining potential future alteration resulting from anthropogenic activities. Parametric and non-parametric tests are used for determining the trends in climatic variables. In this study, trend tests were applied to annual total precipitation data obtained in period of 1972 and 2012, in the Konya Basin. Non-parametric trend tests, (Sen’s T, Spearman’s Rho, Mann-Kendal, Sen’s T trend, Wald-Wolfowitz) and parametric test (mean square) were applied to annual total precipitations of 15 stations for trend analysis. The linear slopes (change per unit time) of trends are calculated by using a non-parametric estimator developed by Sen. The beginning of trends is determined by using the Mann-Kendall rank correlation test. In addition, homogeneities in precipitation trends are tested by using a method developed by Van Belle and Hughes. As a result of tests, negative linear slopes were found in annual total precipitations in Konya.

Keywords: trend analysis, precipitation, hydroclimatology, Konya

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Authors: Vinay Kumar, M. Kishor, Sathyanarayana Rao Ts

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Background: Growth of elderly people in the general population in recent years is termed as ‘greying of the world’ where there is a shift from high mortality & fertility to low mortality and fertility, resulting in an increased proportion of older people as seen in India. Improved health care promises longevity but socio-economic factors like poverty, joint families and poor services pose a psychological threat. Epidemiological data regarding the prevalence of mental disorders in geriatric population with physical illness is required for proper health planning. Methods: Sixty consecutive elderly patients aged 60 years or above of both sexes, reporting with physical illness to general outpatient registration counter of JSS Medical College and Hospital, Mysore, India, were considered for the Study. With informed consent, they were screened with General Health Questionnaire (GHQ-12) and were further evaluated for diagnosing mental disorders according to WHO International Classification of Diseases (ICD-10) criteria. Results: Mental disorders were detected in 48.3%, predominantly depressive disorders, nicotine dependence, generalized anxiety disorder, alcohol dependence and least was dementia. Most common physical illness was cardiovascular disease followed by metabolic, respiratory and other diseases. Depressive disorders, substance dependence and dementia were more associated with cardiovascular disease compared to metabolic disease and respiratory diseases were more associated with nicotine dependence. Conclusions: Depression and Substance use disorders among elderly population is of concern, which needs to be further studied with larger population. Psychiatric morbidity will adversely have an impact on physical illness which needs proper assessment and management. This will enhance our understanding and prioritize our planning for future.

Keywords: Geriatric, mental disorders, physical illness, psychiatry

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Authors: Ejaz Ali M. Phil

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Enterprise Resource Planning (ERP) systems are playing a vital role in effective management of business functions in large and complex organizations. Human Resource Information System (HRIS) is a core module of ERP, providing concrete solutions to implement Human Resource Management (HRM) Practices in an innovative and efficient manner. Over the last decade, there has been considerable increase in the studies on HRIS. Nevertheless, previous studies relatively lacked to examine the moderating role of HRIS in performing HRM practices that may affect the firms’ performance. The current study was carried out to examine the impact of HRM practices (training, performance appraisal) on perceived organizational performance, with moderating role of HRIS, where the system is in place. The study based on Resource Based View (RBV) and Ability Motivation Opportunity (AMO) Theories, advocating that strengthening of human capital enables an organization to achieve and sustain competitive advantage which leads to improved organizational performance. Data were collected through structured questionnaire based upon adopted instruments after establishing reliability and validity. The structural equation modeling (SEM) were used to assess the model fitness, hypotheses testing and to establish validity of the instruments through Confirmatory Factor Analysis (CFA). A total 220 employees of 25 firms in corporate sector were sampled through non-probability sampling technique. Path analysis revealing that HRM practices and HRIS have significant positive impact on organizational performance. The results further showed that the HRIS moderated the relationships between training, performance appraisal and organizational performance. The interpretation of the findings and limitations, theoretical and managerial implications are discussed.

Keywords: enterprise resource planning, human resource, information system, human capital

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Authors: S. I. Mwasha, Z. Robinson, M. Musgrave

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Communities, especially in the global south, have been reported to have low adaptive capacity to cope with climate change impacts. As an attempt to improve adaptive capacity, most studies have focused on understanding the access of the household resources which can contribute to resilience against changes. However, little attention has been shown in uncovering how the household resources could be used and their implications to resilience against weather related shocks. By using a case study qualitative study, this project analyzed the trends in livelihoods practices and their implication to social equity. The study was done in three different villages within Kilimanjaro region. Each in different agro ecological zone. Two focus group discussions in two agro-ecological zones were done, one for women and another one for men except in the third zone where focus group participant were combined together (due to unforeseen circumstances). In the focus group discussion, several participatory rural appraisal tools were used to understand trend in crops and animal production and the use in which it is made: climate trends, soil fertility, trees and other livelihoods resources. Data were analyzed using thematic network analysis. Using an amalgam of magnitude (to note weather comments made were positive or negative) and descriptive coding (to note the topic), six basic themes were identified under social equity: individual ownership, family ownership, love and respect, women no education, women access to education as well as women access to loans. The results implied that despite mum and dad in the family providing labor in the agro pastoral activities, there were separations on who own what, as well as individual obligations in the family. Dad owned mostly income creating crops and mum, food crops. therefore, men controlled the economy which made some of them become arrogant and spend money to meet their interests sometimes not taking care of the family. Separation in ownership was reported to contribute to conflicts in the household as well as causing controversy on the use income is spent. Men were reported to use income to promote matriarchy system. However, as women were capacitated through access to education and loans they become closer to their husband and get access to own and plan the income together for the interest of the family. Joint ownership and planning on the household resources were reported to be important if families have to better adapt to climate change. The aim of this study is not to show women empowerment and joint ownership and planning as only remedy for low adaptive capacity. There is the need to understand other practices that either directly or indirectly impacts environmental integrity, food security and economic development for household resilience against changing climate.

Keywords: adaptive capacity, climate change, resilience, women empowerment

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Authors: Antonella Falanga, Armando Cartenì

Abstract:

"Big data" refers to extremely vast and complex sets of data, encompassing extraordinarily large and intricate datasets that require specific tools for meaningful analysis and processing. These datasets can stem from diverse origins like sensors, mobile devices, online transactions, social media platforms, and more. The utilization of big data is pivotal, offering the chance to leverage vast information for substantial advantages across diverse fields, thereby enhancing comprehension, decision-making, efficiency, and fostering innovation in various domains. Big data, distinguished by its remarkable attributes of enormous volume, high velocity, diverse variety, and significant value, represent a transformative force reshaping the industry worldwide. Their pervasive impact continues to unlock new possibilities, driving innovation and advancements in technology, decision-making processes, and societal progress in an increasingly data-centric world. The use of these technologies is becoming more widespread, facilitating and accelerating operations that were once much more complicated. In particular, big data impacts across multiple sectors such as business and commerce, healthcare and science, finance, education, geography, agriculture, media and entertainment and also mobility and logistics. Within the transportation sector, which is the focus of this study, big data applications encompass a wide variety, spanning across optimization in vehicle routing, real-time traffic management and monitoring, logistics efficiency, reduction of travel times and congestion, enhancement of the overall transportation systems, but also mitigation of pollutant emissions contributing to environmental sustainability. Meanwhile, in public administration and the development of smart cities, big data aids in improving public services, urban planning, and decision-making processes, leading to more efficient and sustainable urban environments. Access to vast data reservoirs enables deeper insights, revealing hidden patterns and facilitating more precise and timely decision-making. Additionally, advancements in cloud computing and artificial intelligence (AI) have further amplified the potential of big data, enabling more sophisticated and comprehensive analyses. Certainly, utilizing big data presents various advantages but also entails several challenges regarding data privacy and security, ensuring data quality, managing and storing large volumes of data effectively, integrating data from diverse sources, the need for specialized skills to interpret analysis results, ethical considerations in data use, and evaluating costs against benefits. Addressing these difficulties requires well-structured strategies and policies to balance the benefits of big data with privacy, security, and efficient data management concerns. Building upon these premises, the current research investigates the efficacy and influence of big data by conducting an overview of the primary and recent implementations of big data in transportation systems. Overall, this research allows us to conclude that big data better provide to enhance rational decision-making for mobility choices and is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, public transport, sustainable mobility, transport demand, transportation planning

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