Class Project Research Articles

Evaluating time-cost trade-off in a resource constraint GERT-type project scheduling problem considering rework

In practice, rework is a major threat to projects’ performance and increases the risk of not delivering the outcomes on time and budget. The classical project scheduling methods are incapable of considering the rework and stochastic structure for projects in the planning phase. The current study models the stochastic projects through a GERT network in which the occurrence of rework is allowed. The aim is to find the optimal execution mode for each activity so that the project is completed within the desired time and the resource constraint is satisfied. We develop a multi-mode time–cost trade-off resource constraint project scheduling problem under uncertainty to find a here-and-now solution to minimise project completion time. The problem is solved using a combination of flow-graph theory and a branch and bound method for the developed integer programming model. As the project structure is stochastic, a distinct set of all possible realised paths is considered. To the best of our knowledge, there is no similar test instance in the literature, hence, the solution methodology is implemented on a randomly generated numerical example. The reported computational results exhibit the sensitivity of objective function to the changes in available resource amount.

융합 프로젝트기반 팀티칭 수업에서의 학습 경험 분석: A대학 수업 사례를 중심으로

This study analyzes learners' experiences by developing a convergence project-based team-teaching class as a method to implement convergence education in university. To achieve this, the study conducted a literature review, developed a convergence project-based team-teaching class, and applied it in the field, followed by data collection and result analysis. The class was conducted with 39 students at A University during the second semester of 2023. Qualitative analysis of the data from the convergence project-based team-teaching class revealed that learners experienced convergent thinking in three aspects: 'intrapersonal convergence experiences,' 'convergence experiences among group members,' and 'convergence experiences with the real world.' The findings of this study provide foundational research for practical strategies that educators can use to design convergence project classes in alignment with the goals and direction of university education.

Vetting the Extrapolation Caution of Tamhane & Dunlop: A Time Series Forecasting Analysis

Context In forecasting there are only two classes of Projections: Extrapolations or Interpolations. Interestingly, Interpolations usually, all but guarantee, that the theoretical expectations that rationalize the veracity of the forecasting profiles are the likely State of Nature. Simply: The [1-a]% Forecasting Prediction Interval [FPI] provides the expected-intel with a frequency of [1-a]%. However, for Extrapolations, [T&D] [8 p. 363] offer the following “Forecasting Bump in the Road” T&D Conjecture: “- - -extrapolation beyond the range of the data is a risky business should be avoided.” If T&D are correct that: Forecasting Extrapolations somehow compromise the linkages of the Projection of the Past into a Relevant Future, Then, indeed, Extrapolations should be avoided. T&D’s theoretical and experientially based caution has garnered very little vetting interest—Voilà: The motivation for our research report. Research Elements Initially, we offer a detailed analysis of the mathematical nature of an Extrapolation as it affects the Precision of the 95% Time Series [TS] Forecasting Prediction Interval [95%TSFPIs]. This is critical as, interestingly, T&D offer no detailed support for their risky business musing. For the inferential testing stage, we will use as the Y-Response Variate: The Capture Rate of the 95%TSFPIs. As we are using a DOE-Inferential Model, we are opting for two-Category Covariates: Extrapolations—[As they are the focus of our inquiry.] & Panel-Variation—measured as the Coefficient of Determination [CoD]—[As variation is the bane of forecasting.]. For DOE: testing, we have selected a random sample of 202 Panels from the S&P500; for each Panel there are Three TS-Extrapolations and also Three [CoD-screens]. Results We found clear inferential evidence that as the Extrapolations move away from the mean of the TS time-index & The CoD increases that certain DOE-{Ext & CoD} Tukey-Kramer HSD-interaction-profiles suggest a failure to realizes the theoretical expectations of the Capture Rate of the 95%TSFPIs. We offer, for the first time, a deconstruction of these very interesting inferential DOE-results that rationalize T&D’s risky business musing.

Possibility of diffusion and challenges of a frailty prevention class hosted by older adults: Efforts by the Saitama Prefecture Silver Human Resources Center Federation Headquarters

Objectives Since 2018, the Saitama Prefecture Silver Human Resources Center (SHRC) Federation Headquarters and Tokyo Metropolitan Institute for Geriatrics and Gerontology has attempted to diffuse a business model in which SHRC members are compensated for operating a frailty prevention class. This activity report clarifies these efforts, examines the feasibility of diffusing this model based on each SHRC's project implementation status, and summarizes the relevant issues.Methods To promote the commercialization of classes, all 58 SHRCs in Saitama Prefecture were offered (1) class programs comprising a multifactorial program (exercise, nutrition, and social interactions) and teaching materials, (2) training courses for frailty prevention supporters who manage the classes (three days × four blocks/year), (3) project information exchange meetings (held once annually), and (4) consultation support for project implementation. A questionnaire survey on the project implementation status was conducted among SHRC employees to evaluate the possibility of project diffusion based on adoption, implementation, and continuation. Furthermore, project implementation issues were categorized using free descriptions as codes to create subcategories based on content and categories based on subcategory similarities.Results Regarding adoption, among the 58 SHRCs, 43 (74.1%) participated in training courses for frailty prevention supporters and 34 (58.6%) implemented the project from 2018 onwards. Regarding implementation, 23 (39.7%) SHRCs provided rewards to frailty prevention supporters (67.6% of the SHRC that implemented the project). Regarding continuation, 21 of the 28 SHRCs (75.0%) that began the project by 2021 continued it for two years or longer. Moreover, implementation challenges related to project initiation, supporters, new entrants, and class management were categorized.Conclusions More than half of the SHRCs implemented the project, 40% of SHRC provided rewards for frailty prevention supporters, and 75% of SHRCs that implemented the project continued working on it. Hence, the model may be extended to other regions. However, four issues have been identified. The model is likely to have a ripple effect, increasing the number of individuals involved in community frailty prevention and creating attractive employment opportunities for the elderly. We intend to address these challenges and disseminate our model further.

Low-dimensional projection of reactivity classes in chemical reaction dynamics using supervised dimensionality reduction.

Transition state theory (TST) provides a framework to estimate the rate of chemical reactions. Despite its great success with many reaction systems, the underlying assumptions such as local equilibrium and nonrecrossing do not necessarily hold in all cases. Although dynamical systems theory can provide the mathematical foundation of reaction tubes existing in phase space that enables us to predict the fate of reactions free from the assumptions of TST, numerical demonstrations for large systems have been yet one of the challenges. Here, we propose a dimensionality reduction algorithm to demonstrate structures in phase space (called reactive islands) that predict reactivity in systems with many degrees of freedom. The core of this method is the application of supervised principal component analysis, where a coordinate transformation is performed to preserve the dynamical information on reactivity (i.e., to which potential basin the system moves from a region of interest) as much as possible. The reactive island structures are expected to be reflected in the transformed, low-dimensional phase space. As an illustrative example, the algorithm is scrutinized using a modified Hénon-Heiles Hamiltonian system extended to many degrees of freedom, which has three channels leading to three different products from one stable potential basin. It is shown that our algorithm can predict the reactivity in the transformed, low-dimensional coordinate system better than a naïve coordinate system and that the reactivity distribution in the transformed low-dimensional space is considered to reflect the underlying reactive islands.

Students create prize‐winning app to keep everyone safer on campus

Four students from the University of Nevada, Reno, for their senior project in computer science class, created an app designed specifically to help women feel safer on campus. Kathleen Scafidi, Anna Desorcy, Michael Munakash, and Kurtis Bertauche were all computer science majors when they created the app Ur Next Route.

Cell class-specific long-range axonal projections of neurons in mouse whisker-related somatosensory cortices.

Long-range axonal projections of diverse classes of neocortical excitatory neurons likely contribute to brain-wide interactions processing sensory, cognitive and motor signals. Here, we performed light-sheet imaging of fluorescently labeled axons from genetically defined neurons located in posterior primary somatosensory barrel cortex and supplemental somatosensory cortex. We used convolutional networks to segment axon-containing voxels and quantified their distribution within the Allen Mouse Brain Atlas Common Coordinate Framework. Axonal density was analyzed for different classes of glutamatergic neurons using transgenic mouse lines selectively expressing Cre recombinase in layer 2/3 intratelencephalic projection neurons (Rasgrf2-dCre), layer 4 intratelencephalic projection neurons (Scnn1a-Cre), layer 5 intratelencephalic projection neurons (Tlx3-Cre), layer 5 pyramidal tract projection neurons (Sim1-Cre), layer 5 projection neurons (Rbp4-Cre), and layer 6 corticothalamic neurons (Ntsr1-Cre). We found distinct axonal projections from the different neuronal classes to many downstream brain areas, which were largely similar for primary and supplementary somatosensory cortices. Functional connectivity maps obtained from optogenetic activation of sensory cortex and wide-field imaging revealed topographically organized evoked activity in frontal cortex with neurons located more laterally in somatosensory cortex signaling to more anteriorly located regions in motor cortex, consistent with the anatomical projections. The current methodology therefore appears to quantify brain-wide axonal innervation patterns supporting brain-wide signaling.

Cell class-specific long-range axonal projections of neurons in mouse whisker-related somatosensory cortices

Long-range axonal projections of diverse classes of neocortical excitatory neurons likely contribute to brain-wide interactions processing sensory, cognitive and motor signals. Here, we performed light-sheet imaging of fluorescently labeled axons from genetically defined neurons located in posterior primary somatosensory barrel cortex and supplemental somatosensory cortex. We used convolutional networks to segment axon-containing voxels and quantified their distribution within the Allen Mouse Brain Atlas Common Coordinate Framework. Axonal density was analyzed for different classes of glutamatergic neurons using transgenic mouse lines selectively expressing Cre recombinase in layer 2/3 intratelencephalic projection neurons (Rasgrf2-dCre), layer 4 intratelencephalic projection neurons (Scnn1a-Cre), layer 5 intratelencephalic projection neurons (Tlx3-Cre), layer 5 pyramidal tract projection neurons (Sim1-Cre), layer 5 projection neurons (Rbp4-Cre), and layer 6 corticothalamic neurons (Ntsr1-Cre). We found distinct axonal projections from the different neuronal classes to many downstream brain areas, which were largely similar for primary and supplementary somatosensory cortices. Functional connectivity maps obtained from optogenetic activation of sensory cortex and wide-field imaging revealed topographically organized evoked activity in frontal cortex with neurons located more laterally in somatosensory cortex signaling to more anteriorly located regions in motor cortex, consistent with the anatomical projections. The current methodology therefore appears to quantify brain-wide axonal innervation patterns supporting brain-wide signaling.

Generalized Modular Method of Project Risk Management

The article discusses risk management models and frameworks implemented during the development of multi-user cross-platform distributed IT projects. For this class of pro-jects, the use of quantitative risk assessment methods, rules for absorbing and adding risks, which make it pos¬sible to systematically assess the likelihood of negative events and their impact on each stage of the project, are observed. Authors propose a method of modular risk management, present the main indicators for assessing the progress of the implementation of the i-th module and its operational ma¬nagement, and provide a formula for calculating project efficiency. These calculated indicators can be used to estimate the cost of resources at a certain point in time, estimate the timeframe for completing the module, and decide on the feasibility of further development.

Data-driven portfolio management for motion pictures industry: A new data-driven optimization methodology using a large language model as the expert

Portfolio management is one of the unresponded problems of the Motion Pictures Industry (MPI). To design an optimal portfolio for an MPI distributor, it is essential to predict the box office of each project. Moreover, for an accurate box office prediction, it is critical to consider the effect of the celebrities involved in each MPI project, which was impossible with any precedent expert-based method. Additionally, the asymmetric characteristic of MPI data decreases the performance of any predictive algorithm. In this paper, firstly, the fame score of the celebrities is determined using a large language model. Then, to tackle the asymmetric character of MPI’s data, projects are classified. Furthermore, the box office prediction takes place for each class of projects. Finally, using a hybrid multi-attribute decision-making technique, the preferability of each project for the distributor is calculated, and benefiting from a bi-objective optimization model, the optimal portfolio is designed. To validate our approach, we conducted experiments using a dataset of movies released in the United States from 1980 to 2020 and employed the proposed approach to predict box office performance. Our results demonstrate that the proposed methodology significantly improves prediction accuracy and provides a robust framework for effective portfolio management.

Students create prize‐winning app to keep everyone safer on campus

Four students from the University of Nevada, Reno, senior project in computer science class created an app designed specifically to help women feel safer on campus. Kathleen Scafidi, Anna Desorcy, Michael Munakash, and Kurtis Bertauche were all computer science majors when they created the app Ur Next Route.

Augmented Reality untuk Meningkatkan Keterampilan Menulis, Berbicara, Keterampilan Berpikir Kritis dalam Pembelajaran Bahasa Indonesia Kelas V SD Xyz Bintaro

Students need to learn thoroughly on the writing, speaking and critical thinking skills in order to adapt with the development of technology and information. This study aims to analyze the differences between 2 classes that implemented 2 different means in learning Bahasa Indonesia for grade 5 students, between control class that use lecturing method and the experiment class that use Augmented Reality. The research subject were the fifth graders of XYZ school in Bintaro area. There were 28 students from control group and 27 students from the experiment group with a total of 55 students in all. This research period was conducted in 4 months from late January in 23 January 2024 to 10 May 2024. This study used a weak experimental design method with a static-group pretest-posttest design model. The research data was collected from the observation of the students performance during class discussion and project presentation which used a rubric that has been validated and is a reliable instrument. The result of the statistical analysis showed differences in the control class pretest and control class posttest, in the experimental class pretest and experimental class posttest, also the nGain result for both classes in writing, speaking and critical thinking skills. The average nGain for control class in writing, speaking and critical thinking skills respectively are; 0,17; 0,21; 0,26 While the average nGain for the experiment class in writing, speaking and critical thinking skills is 0,41; 0,31; 0,27 respectively. Based on the result, the ngain result for critical thinking skills in experiment class showed low result using 0,3 as the significance value. This result means the use of Augmented Reality was less effective in critical thinking skills but effective in writing and speaking skills.

The Influence of Implementing the Project Based Learning Model on Students’ Geography Learning Motivation at SMA N 1 Tanjung Mutiara Agam Regency

This research is motivated by the problem of low motivation to study geography, no concentration and low activity during learning, there is no student feedback when learning takes place. The purpose of this study was to find out and analyze data that had the effect of applying the Project Based Learning learning model on increasing students' motivation to learn Geography at SMA N 1 Tanjung Mutiara, Agam Regency. The type of research used was a quasi-experimental research, the research design used was a non-equivalent Control Group Design. The population of all class X students of SMA N 1 Tanjung Mutiara, Agam Regency who were registered in the 2022/2023 school year consisted of 6 classes and the sampling in this study was conducted by random sampling, the instruments in this study were warm and the data analysis techniques were descriptive and inferential statistical analysis. Research results: Is there an effect of applying the Project Based Learning learning model to increasing students' motivation to learn Geography at SMA N 1 Tanjung Mutiara, Agam Regency, research. Based on the descriptive analysis of the experimental class (Project based learning) which obtained a percentage value of 84% in the High category while students in the control class (Conventional) obtained a percentage value of 78% with High. Based on the independent sample t-test regarding student questionnaire answers, it can be concluded that the sig value is 0.002 < 0.05 which states that the coefficient value is significant because tcount > ttable = 3.298 > ttable 1.670, thus it can be interpreted that H0 is rejected and Ha is accepted. so, there is an influence of the project based learning learning model on student learning motivation in the subject of Geography at SMA N 1 Tanjung Mutiara, Agam Regency.

From local bacterial communities to energy: application of microbial fuel cells in laboratory experimentation.

It is well known that bacterial communities are an essential component to maintain the balance of terrestrial ecosystems due to the functions and services performed by microorganisms in the environment. The research seeking on alternative energy sources has shown that bacterial communities can bioconvert the chemical energy of an organic substrate into electrical energy, within devices known as microbial fuel cells. For this reason, this class project allows students of Biotechnology, Environmental Science, and Microbiology to apply the appropriate methodology to develop a class project throughout an environmental bacterial community capable of generating electrical energy.

Linear sections of determinantal varieties

Denote Mmn(k) to be the set of all m n matrices over k, and PMmn(k) to be its affine space. Let Dm,n,r PMmn(k) be the subvariety consisting of the projective classes of all m n matrices with rank less than or equal to r. We study the minimal integer k > 0 such that for any linear subspace L of dimension k in PMmn(k), Dm,n,r L = . We get some partial results about this problem. Specially, when m = n = r + 1, we solve this problem for k = R, C and Q.

Teacher Capability in Developing Independent Curriculum Learning Tools

The Merdeka Curriculum is the latest innovation that takes time for teachers to adjust their teaching methods. This study aims to analyze teachers' ability to develop learning tools in accordance with the Merdeka Curriculum at SD Negeri 32 Cakranegara. The focus of this research is on grade 4A and 4B teachers, using observation, documentation, and interview methods to collect data regarding teachers' competencies and their learning designs. The results showed that SDN 32 Cakranegara has implemented various concepts from Merdeka Belajar. Teachers demonstrate skills in designing learning tools such as teaching modules, Learner Worksheets (LKPD), media, teaching materials, and evaluations, in accordance with the required stages and components. However, in its implementation, there are challenges such as arranging the Flow of Learning Objectives (ATP) to be more organized and systematic. In addition, teachers also have difficulties in preparing the Learning Implementation Plan (RPP) and choosing appropriate assessments to evaluate learning. The limitations of student books, teachers' lack of ability and readiness to use varied learning methods and media, as well as limited technology skills, are also obstacles. The wide range of teaching materials and the difficulty in determining appropriate class projects in grade IV are also challenges. To overcome this, it is recommended that teachers seek additional references on learning assessment and attend training regularly to improve their competence.

Identification of Sources of Complexity in Various Types of Building Projects in India Based on Design and Performance Attributes

Building projects as sub-sect of construction projects are complex and different in design and performance attributes. The prominent classes of building projects are high-rise residential buildings, hospitals, hotels, general offices, retail buildings/malls, educational institutions, and warehouses. In this study, building projects have been classified based on their end use. Complexities vary between construction projects and within various types of building projects, as well as across regions and countries. Understanding the sources of complexity is imperative to strategize their successful development. This research paper attempts to identify the sources of complexities using the design and performance attributes of seven prominent building types. A survey was conducted through experienced architects and construction professionals (the mean years of experience being approximately 13.88 years) over 34 different attributes or parameters under six categories. These attributes have been shortlisted from past research work by various authors, and the pilot study for this project. The Kruskal-Wallis Test was used to calculate the mean ranking and to confirm that the medians of each building type were not the same when compared against each attribute, irrespective of the level of complexity. Using data analysis and the mean ranking scores as a representation of relative complexity, primary sources of complexity in each class of buildings have been identified and listed. The results indicate that hospitals (as a building typology) are relatively the most complex building facilities in terms of design and performance attributes, showing the highest mean ranking towards 16 attributes (with only one shared ranking). Hospitals are followed by retail/malls (10 with one shared ranking), hotels (3), high-rise residential buildings (4), educational institutions (2), general offices (0), and warehouses (0). Strategies to manage these attributes have been proposed for each building typology so that the risks emanating from the complexities of these building projects can be mitigated and effectively managed at the design stage.

Shaping Future Leaders: Exploring Challenges and Strategies in Character Education at Madrasah Tsanawiyah

This research aims to gain a deep understanding of character education management and the supporting and inhibiting factors in the implementation of Character Education Management at Madrasah Tsanawiyah Pesantren Mizanul Ulum. This research employs a qualitative approach with a case study design. Data collection is conducted through in-depth interviews with various stakeholders, including the school principal, teachers, and parents. Participatory observation is also carried out to understand the daily dynamics in the madrasah. Thematic analysis is applied to identify supporting and inhibiting factors in character education implementation. The results reveal that full involvement of the pesantren community such as regular meetings with parents and open classes for parents, integrated curriculum such as material development and collaborative projects in class, and active character guidance are the main supporting factors. Conversely, challenges from external environments, resource limitations, and technological impacts emerge as inhibiting factors. Wise and creative management steps in overcoming resource limitations, coupled with a prudent technological approach, have proven effective in maintaining focus on shaping students' characters.

Artificial Intelligence (AI) is Not A Writing Gods, So Why Do Post-Graduate Students Believe It?

This study was aimed at understanding graduate students' preferences in applying AI when dealing with their class papers and projects in Indonesia. It also sought to understand how students who have used AI in previous writing feel about such experience. This study adopted a phenomenological research method in order to elicit in-depth insights into the concerns of the students. The participants included graduate students from four universities in Indonesia. These data were gathered using semi-structured interviews of 30 students who had experience using AI for their academic writing. Guided by understanding the decision-making process, perceived benefits, and drawbacks of AI, and overall experiences, interview questions were prepared. One-way thematic analysis was conducted with the interview data. Students seemed to view AI applications as only helping with formatting and editing tasks, as most of them would like to have the opportunity to do the major work by themselves for better learning. Another underlying strong theme emerging here is related to AI overdependency and unequal access to it. The results offer insights into the respective areas that can be used by educators and institutions to provide a balance between the rising AI in use and support for independent learning within academics.

Exploring student perspectives on generative artificial intelligence in higher education learning

This study examined the perspectives of Ghanaian higher education students on the use of ChatGPT. The Students’ ChatGPT Experiences Scale (SCES) was developed and validated to evaluate students’ perspectives of ChatGPT as a learning tool. A total of 277 students from universities and colleges participated in the study. Through exploratory factor analysis, a three-factor structure of students' perspectives (ChatGPT academic benefits, ChatGPT academic concerns, and accessibility and attitude towards ChatGPT) was identified. A confirmatory factor analysis was carried out to confirm the identified factors. The majority of students are aware of and recognize the potential of Gen AI tools like ChatGPT in supporting their learning. However, a significant number of students reported using ChatGPT mainly for non-academic purposes, citing concerns such as academic policy violations, excessive reliance on technology, lack of originality in assignments, and potential security risks. Students mainly use ChatGPT for assignments rather than for class or group projects. Students noted that they have not received any training on how to use ChatGPT safely and effectively. The implications for policy and practice are discussed in terms of how well-informed policy guidelines and strategies on the use of Gen AI tools like ChatGPT can support teaching and improve student learning.