Search results for: organizational identification

Authors: Noureddine Seddari, Mohamed Belaoued, Salah Bougueroua

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The modeling of complex systems is generally based on the decomposition of their components into sub-systems easier to handle. This division has to be made in a methodical way. In this paper, we introduce an industrial control system modeling and simulation based on the Multi-Agent System (MAS) methodology AALAADIN and more particularly the underlying conceptual model Agent/Group/Role (AGR). Indeed, in this division using AGR model, the overall system is decomposed into sub-systems in order to improve the understanding of regulation and control systems, and to simplify the implementation of the obtained agents and their groups, which are implemented using the Multi-Agents Development KIT (MAD-KIT) platform. This approach appears to us to be the most appropriate for modeling of this type of systems because, due to the use of MAS, it is possible to model real systems in which very complex behaviors emerge from relatively simple and local interactions between many different individuals, therefore a MAS is well adapted to describe a system from the standpoint of the activity of its components, that is to say when the behavior of the individuals is complex (difficult to describe with equations). The main aim of this approach is the take advantage of the performance, the scalability and the robustness that are intuitively provided by MAS.

Keywords: complex systems, modeling and simulation, industrial control system, MAS, AALAADIN, AGR, MAD-KIT

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Authors: Julio Lavarello-Salinas, Verónica Kramm-Vergara, Pedro Gil-La Orden

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During the COVID-19 pandemic, mental health became a relevant factor in people’s performance within organizations. The aim of this study was to analyze the effects of an organizational intervention program on the psychosocial factors of demands, resources, and the consequences of psychosocial risks in a technology services company during the COVID-19 pandemic. A quasi-experimental study was carried out with 105 employees who took part in an eight-week intervention program divided into two large stages. Pre- and post- measurements were collected using the UNIPSICO Questionnaire, considering its factors of demands, resources, and consequences of psychosocial risks. The Spanish Burnout Inventory (SBI) was also included. The results showed significant improvements in the perception of some psychosocial demand factors, all the resource factors, and all the consequences of psychosocial risks, except the guilt dimension of the SBI. Thus, we can conclude that the program was effective and that the study limitations should be improved in future studies.

Keywords: UNIPSICO questionnaire, occupational health, work stress, work psychosocial risk

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Authors: Alberto Jiménez-Vargas, Manuel de Jesús Palacios-Gallegos, Miguel Ángel Hernández-López, Rafael Campos-Amezcua, Julio Cesar Solís-Sanchez

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An optimal wind turbine blade design must be able of capturing as much energy as possible from the wind source available at the area of interest. Many times, an optimal design means the use of large quantities of material and complicated processes that make the wind turbine more expensive, and therefore, less cost-effective. For the construction and installation of a wind turbine, the blades may cost up to 20% of the outline pricing, and become more important due to they are part of the rotor system that is in charge of transmitting the energy from the wind to the power train, and where the static and dynamic design loads for the whole wind turbine are produced. The aim of this work is the develop of a blade fluid-structure interaction (FSI) simulation that allows the identification of the major damage zones during the normal production situation, and thus better decisions for design and optimization can be taken. The simulation is a dynamic case, since we have a time-history wind velocity as inlet condition instead of a constant wind velocity. The process begins with the free-use software NuMAD (NREL), to model the blade and assign material properties to the blade, then the 3D model is exported to ANSYS Workbench platform where before setting the FSI system, a modal analysis is made for identification of natural frequencies and modal shapes. FSI analysis is carried out with the two-way technic which begins with a CFD simulation to obtain the pressure distribution on the blade surface, then these results are used as boundary condition for the FEA simulation to obtain the deformation levels for the first time-step. For the second time-step, CFD simulation is reconfigured automatically with the next time-step inlet wind velocity and the deformation results from the previous time-step. The analysis continues the iterative cycle solving time-step by time-step until the entire load case is completed. This work is part of a set of projects that are managed by a national consortium called “CEMIE-Eólico” (Mexican Center in Wind Energy Research), created for strengthen technological and scientific capacities, the promotion of creation of specialized human resources, and to link the academic with private sector in national territory. The analysis belongs to the design of a rotor system for a 5 kW wind turbine design thought to be installed at the Isthmus of Tehuantepec, Oaxaca, Mexico.

Keywords: blade, dynamic, fsi, wind turbine

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Authors: V. L. M. F. Capellini, A. P. P. M. Maturana, N. C. M. Brondino, M. B. C. L. B. M. Peixoto, A. J. Broughton

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A paradigm shift is a process. The process of implementing inclusive education, a system constructed to support all learners, requires planning, identification, experimentation, and evaluation. In this vein, the purpose of the present study was to evaluate the capacity of one Brazilian state school systems to provide special education students with a quality inclusive education. This study originated at the behest of concerned families of students with special needs who filed complaints with the Municipality of Bauru, São Paulo. These families claimed, 1) children with learning differences and educational needs had not been identified for services, and 2) those who had been identified had not received sufficient specialized educational assistance (SEA) in schools across the City of Bauru. Hence, the Office of Civil Rights for the state of São Paulo (Ministério Público de São Paulo) summoned the local higher education institution, UNESP, to design a research study to investigate these allegations. In this exploratory study, descriptive data were gathered from all elementary and middle schools including 58 state schools and 17 city schools, for a total of 75 schools overall. Data collection consisted of each school's annual strategic action plan, surveys and interviews with all school stakeholders to determine their perceptions of the inclusive education available to students with Special Education Needs (SEN). The data were collected as one of four stages in a larger study which also included field observations of a focal students' experience and a continuing education course for all teachers and administrators in both state and city schools. For the purposes of this study, the researchers were interested in understanding the perceptions of school staff, parents, and students across all schools. Therefore, documents and surveys from 75 schools were analyzed for adherence to federal legislation guaranteeing students with SEN the right to special education assistance within the regular school setting. Results shows that while some schools recognized the legal rights of SEN students to receive special education, the plans to actually deliver services were absent. In conclusion, the results of this study revealed both school staff and families have insufficient planning and accessibility resources, and the schools have inadequate infrastructure for full-time support to SEN students, i.e., structures and systems to support the identification of SEN and delivery of services within schools of Bauru, SP. Having identified the areas of need, the city is now prepared to take next steps in the process toward preparing all schools to be inclusive.

Keywords: inclusion, school, special education, special needs

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Authors: Bilel Chalghaf, Mathieu Varin

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Forest characterization in Quebec, Canada, is usually assessed based on photo-interpretation at the stand level. For species identification, this often results in a lack of precision. Very high spatial resolution imagery, such as DigitalGlobe, and Light Detection and Ranging (LiDAR), have the potential to overcome the limitations of aerial imagery. To date, few studies have used that data to map a large number of species at the tree level using machine learning techniques. The main objective of this study is to map 11 individual high tree species ( > 17m) at the tree level using an object-based approach in the broadleaf forest of Kenauk Nature, Quebec. For the individual tree crown segmentation, three canopy-height models (CHMs) from LiDAR data were assessed: 1) the original, 2) a filtered, and 3) a corrected model. The corrected CHM gave the best accuracy and was then coupled with imagery to refine tree species crown identification. When compared with photo-interpretation, 90% of the objects represented a single species. For modeling, 313 variables were derived from 16-band WorldView-3 imagery and LiDAR data, using radiance, reflectance, pixel, and object-based calculation techniques. Variable selection procedures were employed to reduce their number from 313 to 16, using only 11 bands to aid reproducibility. For classification, a global approach using all 11 species was compared to a semi-hierarchical hybrid classification approach at two levels: (1) tree type (broadleaf/conifer) and (2) individual broadleaf (five) and conifer (six) species. Five different model techniques were used: (1) support vector machine (SVM), (2) classification and regression tree (CART), (3) random forest (RF), (4) k-nearest neighbors (k-NN), and (5) linear discriminant analysis (LDA). Each model was tuned separately for all approaches and levels. For the global approach, the best model was the SVM using eight variables (overall accuracy (OA): 80%, Kappa: 0.77). With the semi-hierarchical hybrid approach, at the tree type level, the best model was the k-NN using six variables (OA: 100% and Kappa: 1.00). At the level of identifying broadleaf and conifer species, the best model was the SVM, with OA of 80% and 97% and Kappa values of 0.74 and 0.97, respectively, using seven variables for both models. This paper demonstrates that a hybrid classification approach gives better results and that using 16-band WorldView-3 with LiDAR data leads to more precise predictions for tree segmentation and classification, especially when the number of tree species is large.

Keywords: tree species, object-based, classification, multispectral, machine learning, WorldView-3, LiDAR

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Authors: M. Khouil, N. Saber, M. Mestari

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In this paper, a different architecture of a collision detection neural network (DCNN) is developed. This network, which has been particularly reviewed, has enabled us to solve with a new approach the problem of collision detection between two convex polyhedra in a fixed time (O (1) time). We used two types of neurons, linear and threshold logic, which simplified the actual implementation of all the networks proposed. The study of the collision detection is divided into two sections, the collision between a point and a polyhedron and then the collision between two convex polyhedra. The aim of this research is to determine through the AMAXNET network a mini maximum point in a fixed time, which allows us to detect the presence of a potential collision.

Keywords: collision identification, fixed time, convex polyhedra, neural network, AMAXNET

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Authors: Paul Flynn, Luke O’Donnell

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There is a pressing societal need for educators in formal and non-formal settings to develop pedagogical frameworks, programmes, and interventions that support the development of transversal skills for life beyond the classroom. These skills include communication, collaboration, interpersonal relationship building, problem-solving, and planning, and organizational skills; or lifeworld literacies encountered first hand. This is particularly true for young people aged between 15-18. This demographic represents both the future of society and those best positioned to take advantage of well-designed, structured educational supports within and across formal and non-formal settings. Secondary school history has been identified as an appropriate area of study which deftly develops many of those transversal skills so crucial to positive societal engagement. However, in the formal context, students often challenge history’s relevance to their own lived experience and dismiss it as a study option. In response to such challenges, teachers will often design stimulating lessons which are often well-received. That said, some students continue to question modern-day connections, presenting a persistent and pervasive classroom distraction. The continuing decline in numbers opting to study second-level history indicates an erosion of what should be a critical opportunity to develop all-important lifeworld literacies within formal education. In contrast, students readily acknowledge relevance in non-formal settings where many participants meaningfully engage with history by way of student-focused activities. Furthermore, many do so without predesigned pedagogical aids which support transversal skills development as embodied learning outcomes. As this paper will present, there is a dearth of work pertaining to the circular subject of history and its embodied learning outcomes, including lifeworld literacies, in formal and non-formal settings. While frequently challenging to reconcile formal (often defined by strict curricula and examination processes), and non-formal engagement with history, opportunities do exist. In the Irish context, this is exemplified by a popular university outreach programme: breaking the SEAL. This programme supports second-level history students as they fulfill curriculum requirements in completing a research study report. This report is a student-led research project pulling on communication skills, collaboration with peers and teachers, interpersonal relationships, problem-solving, and planning and organizational skills. Completion of this process has been widely recognized as excellent preparation not only for higher education (third level) but work-life demands as well. Within a formal education setting, the RSR harnesses non-formal learning virtues and exposes students to limited aspects of independent learning that relate to a professional work setting –a lifeworld literacy. Breaking the SEAL provides opportunities for students to enhance their lifeworld literacy by engaging in an independent research and learning process within the protective security of the classroom and its teacher. This paper will highlight the critical role this programme plays in preparing participating students (n=315) for life after compulsory education and presents examples of how lifeworld literacies may be developed through a scaffolded process of historical research and reporting anchored in non-formal contexts.

Keywords: history, education, literacy, transversal skills

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Authors: Melanie Grier, Adam Murry

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Objective: Worldwide, Indigenous Peoples experience underemployment and poverty at disproportionately higher rates than non-Indigenous people, despite similar rates of employment seeking. Euro-colonial conquest and genocidal assimilation policies are implicated as perpetuating poverty, which research consistently links to health and wellbeing disparities. Many of the contributors to poverty, such as inadequate income and lack of access to medical care, can be directly or indirectly linked to underemployment. Calls have been made to prioritize Indigenous perspectives in Industrial-Organizational (I/O) psychology research, yet the literature on Indigenous employment remains scarce. What does exist is disciplinarily diverse, topically scattered, and lacking evidence of community-based participatory research (CBPR) practices, a research project approach which prioritizes community leadership, partnership, and betterment and reduces the potential for harm. Due to the harmful colonial legacy of extractive scientific inquiry "on" rather than "with" Indigenous groups, Indigenous leaders and research funding agencies advocate for academic researchers to adopt reparative research methodologies such as CBPR to be used when studying issues pertaining to Indigenous Peoples or individuals. However, the frequency and consistency of CBPR implementation within scholarly discourse are unknown. Therefore, this project’s goal is two-fold: (1) to understand what comprises CBPR in Indigenous research and (2) to determine if CBPR has been historically used in Indigenous employment research. Method: Using a systematic literature review process, sixteen articles about CBPR use with Indigenous groups were selected, and content was analyzed to identify key components comprising CBPR usage. An Indigenous CBPR components framework was constructed and subsequently utilized to analyze the Indigenous employment empirical literature. A similar systematic literature review process was followed to search for relevant empirical articles on Indigenous employment. A total of 120 articles were identified in six global regions: Australia, New Zealand, Canada, America, the Pacific Islands, and Greenland/Norway. Each empirical study was procedurally examined and coded for criteria inclusion using content analysis directives. Results: Analysis revealed that, in total, CBPR elements were used 14% of the time in Indigenous employment research. Most studies (n=69; 58%) neglected to mention using any CBPR components, while just two studies discussed implementing all sixteen (2%). The most significant determinant of overall CBPR use was community member partnership (CP) in the research process. Studies from New Zealand were most likely to use CBPR components, followed by Canada, Australia, and America. While CBPR use did increase slowly over time, meaningful temporal trends were not found. Further, CBPR use did not directly correspond with the total number of topical articles published that year. Conclusions: Community-initiated and engaged research approaches must be better utilized in employment studies involving Indigenous Peoples. Future research efforts must be particularly attentive to community-driven objectives and research protocols, emphasizing specific areas of concern relevant to the field of I/O psychology, such as organizational support, recruitment, and selection.

Keywords: community-based participatory research, content analysis, employment, indigenous research, international, reconciliation, recruitment, reparative research, selection, systematic literature review

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Authors: Kornelia Kordiak

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The research is based on a biographical approach and serves as a foundation for understanding individual human destinies through the analysis of the context of life experiences. It focuses on the significance of childhood in shaping family micro-worlds from the perspective of biographical learning. In this case, the family micro-world is interpreted as a complex of beliefs and judgments about elements of the ‘total universe’ based on the individual's experiences. The main aim of the research is to understand the importance of childhood in shaping family micro-worlds from the perspective of reflection on biographical learning. Additionally, it contributes to a deeper understanding of the familial experiences of the studied individuals who form these family micro-worlds and the course of the biographical learning process in the subjects. Biographical research aligns with an interpretative paradigm, where individuals are treated as active interpreters of the world, giving meaning to their experiences and actions based on their own values and beliefs. The research methods used in the project—narrative interview method and analysis of personal documents—enable obtaining a multidimensional perspective on the phenomenon under study. Narrative interviews serve as the main data collection method, allowing researchers to delve into various life contexts of individuals. Analysis of these narratives identifies key moments and life patterns, as well as discovers the significance of childhood in shaping family micro-worlds. Moreover, analysis of personal documents such as diaries or photographs enriches the understanding of the studied phenomena by providing additional contexts and perspectives. The research will be conducted in three phases: preparatory, main, and final. The anticipated schedule includes preparation of research tools, selection of research sample, conducting narrative interviews and analysis of personal documents, as well as analysis and interpretation of collected research material. The narrative interview method and document analysis will be utilized to capture various contexts and interpretations of childhood experiences and family relations. The research will contribute to a better understanding of family dynamics and individual developmental processes. It will allow for the identification and understanding of mechanisms of biographical learning and their significance in shaping identity and family relations. Analysis of adult narratives will enable the identification of factors determining patterns of behavior and attitudes in adult life, which may have significant implications for pedagogical practice.

Keywords: childhood, adulthood, biographical learning, narrative interview, analysis of personal documents, family micro-worlds

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Authors: Rafael Martins Manzano Silva, Jean-Francois Tremong

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Electrification of railway lines allows to increase speed, power, capacity and energetic efficiency of rolling stocks. However, this process of electrification is complex and costly. An electrification project is not just about design of catenary. It also includes installation of structures around electrification, as substation installation, electrical isolation, signalling, telecommunication and civil engineering structures. France has more than 30,000 km of railways, whose only 53% are electrified. The others 47% of railways use diesel locomotive and represent only 10% of the circulation (tons.km). For this reason, a new type of electrification, less expensive than the usual, is requested to enable the modernization of these railways. One solution could be the use of hybrids trains. This technology opens up new opportunities for less expensive infrastructure development such as the partial electrification of railway lines. In a partially electrified railway, the power supply of theses hybrid trains could be made either by the catenary or by the on-board energy storage system (ESS). Thus, the on-board ESS would feed the energetic needs of the train along the non-electrified zones while in electrified zones, the catenary would feed the train and recharge the on-board ESS. This paper’s objective deals with the technical and economic potential identification of partial electrification of railway lines. This study provides different scenarios of electrification by replacing the most expensive places to electrify using on-board ESS. The target is to reduce the cost of new electrification projects, i.e. reduce the cost of electrification infrastructures while not increasing the cost of rolling stocks. In this study, scenarios are constructed in function of the electrification’s cost of each structure. The electrification’s cost varies considerably because of the installation of catenary support in tunnels, bridges and viaducts is much more expensive than in others zones of the railway. These scenarios will be used to describe the power supply system and to choose between the catenary and the on-board energy storage depending on the position of the train on the railway. To identify the influence of each partial electrification scenario in the sizing of the on-board ESS, a model of the railway line and of the rolling stock is developed for a real case. This real case concerns a railway line located in the south of France. The energy consumption and the power demanded at each point of the line for each power supply (catenary or on-board ESS) are provided at the end of the simulation. Finally, the cost of a partial electrification is obtained by adding the civil engineering costs of the zones to be electrified plus the cost of the on-board ESS. The study of the technical and economic potential ends with the identification of the most economically interesting scenario of electrification.

Keywords: electrification, hybrid, railway, storage

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Authors: Jonathan M. Watt, Regina L. Sturiale

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The linguistic idiosyncrasies of prison populations have been studied with great interest by scholarly and popular writers alike, whose interests range from curiosity to a disciplined understanding of its function. This paper offers a formalized nomenclature for the four relevant terms (slang, jargon, argot, and cant) and brings together key sociolinguistic concepts such as domain and register with research on institutional dynamics as well as culture and identity. It presents a fresh body of data drawn from interviews with prison staff in the American NE and with awareness of selected publications. The paper then draws a correlation between a person’s competence in prison antilanguage and their status as part of the in-group. This is a distinctive marker of identification that is essential to inmate survival and staff effectiveness.

Keywords: slang, jargon, argot, sociolinguistics, antilanguage, identity

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Authors: Basheer Ahmad Al-Alwan, Ali Ratib Al-Awamreh, Badar Saif Alhatmi

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The success of organizations in today's rapidly changing business landscape greatly hinges on the effectiveness of management creativity. This research aimed to uncover the elements influencing the effectiveness of management creativity by employing the Theory of Planned Behavior. The study's findings indicate that two significant predictors of management creativity effectiveness are one's attitude towards it and the subjective norms within the organization. Such results are rather important for the organizations and their leaders who would want to increase management creativity. The attitudes of subordinates towards management creativity should be positive if managers wish to cultivate management creativity among their employees, and the organizational culture must also be one that enhances and supports creative thinking. They should also make available all the requisite resources and support required for the implementation of their creative ideas and let employees participate in the decision-making processes in order to increase their sense of control over their creative activities. This research contributes to the literature on managerial creativity by presenting evidence about the effectiveness of managerial creativity and the strategies aimed at increasing the level of creativity in organizations through empirical insights.

Keywords: management creativity, attitudes, subjective norms, perceived behavioral control

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Authors: Valentin Nickolai, Florian Pfeffel, Christian Louis Kühner

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In many industrialized nations, the demand for skilled workers rises, causing the current market for employees to be more candidate-driven than employer-driven. Therefore, losing highly skilled and experienced employees due to early or partial retirement negatively impacts firms. Therefore, finding new ways to incentivize older employees (Silver Workers) to stay longer with the company and in their job can be crucial for the success of a firm. This study analyzes how working remotely can be a valid incentive for experienced Silver Workers to stay in their job and instead work from home with more flexible working hours. An online survey with n = 684 respondents, who are employed in the service sector, has been conducted based on 13 constructs that influence job satisfaction. These have been further categorized into three groups “classic influencing factors,” “influencing factors changed by remote working,” and new remote working influencing factors,” and were analyzed using structural equation modeling (SEM). Here, Cronbach’s alpha of the individual constructs was shown to be suitable. Furthermore, the construct validity of the constructs was confirmed by face validity, content validity, convergent validity (AVE > 0.5: CR > 0.7), and discriminant validity. Additionally, confirmatory factor analysis (CFA) confirmed the model fit for the investigated sample (CMIN/DF: 2.567; CFI: 0.927; RMSEA: 0.048). It was shown in the SEM-analysis that the influencing factor on job satisfaction, “identification with the work,” is the most significant with β = 0.540, followed by “Appreciation” (β = 0.151), “Compensation” (β = 0.124), “Work-Life-Balance” (β = 0.116), and “Communication and Exchange of Information” (β = 0.105). While the significance of each factor can vary depending on the work model, the SEM-analysis also shows that the identification with the work is the most significant factor in all three work models mentioned above and, in the case of the traditional office work model, it is the only significant influencing factor. The study shows that employees between the ages of 56 and 65 years have the highest job satisfaction when working entirely from home or remotely. Furthermore, their job satisfaction score of 5.4 on a scale from 1 (very dissatisfied) to 7 (very satisfied) is the highest amongst all age groups in any of the three work models. Due to the significantly higher job satisfaction, it can be argued that giving Silver Workers the offer to work from home or remotely can incentivize them not to opt for early retirement or partial retirement but to stay in their job full-time Furthermore, these findings can indicate that employees in the Silver Worker age are much more inclined to leave their job for early retirement if they have to entirely work in the office.

Keywords: home office, remote work instead of early or partial retirement, silver worker, structural equation modeling

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Authors: Zongyan Li, Matt Best

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This paper presents an optimization method for reducing the number of input channels and the complexity of the feed-forward NARX neural network (NN) without compromising the accuracy of the NN model. By utilizing the correlation analysis method, the most significant regressors are selected to form the input layer of the NN structure. An application of vehicle dynamic model identification is also presented in this paper to demonstrate the optimization technique and the optimal input layer structure and the optimal number of neurons for the neural network is investigated.

Keywords: correlation analysis, F-ratio, levenberg-marquardt, MSE, NARX, neural network, optimisation

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Authors: Lagnajeet Mohanty, Mohnish Mishra, Pratham Tapdiya, Himanshu Sekhar Nayak, Swetapadma Singh

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In the era of global interconnectedness, effective risk assessment and management are critical for organizational resilience. This review explores the integration of machine learning (ML) into risk processes, examining its transformative potential and the challenges it presents. The literature reveals ML's success in sectors like consumer credit, demonstrating enhanced predictive accuracy, adaptability, and potential cost savings. However, ethical considerations, interpretability issues, and the demand for skilled practitioners pose limitations. Looking forward, the study identifies future research scopes, including refining ethical frameworks, advancing interpretability techniques, and fostering interdisciplinary collaborations. The synthesis of limitations and future directions highlights the dynamic landscape of ML in risk management, urging stakeholders to navigate challenges innovatively. This abstract encapsulates the evolving discourse on ML's role in shaping proactive and effective risk management strategies in our interconnected and unpredictable global landscape.

Keywords: machine learning, risk assessment, ethical considerations, financial inclusion

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Authors: Olalekan Bamidele Aruleba

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This research assessed the impact of manpower training and development in the construction industry. The aim is to determine the effect of training and development on employees for effective organizational growth in the construction industry to identify the training method for each category of employee in the construction industry, challenges to training and development of workers in the construction industry and impact of manpower training and development on employees and employers. Data for the study were obtained through a well-structured questionnaire administered to building professionals in Nigeria construction firm. Eighty (80) questionnaires were distributed among building professionals in three selected local governments within Ondo State and sixty-four (64) were returned. Data collected were analysed using descriptive statistics and ranking. Findings of the study revealed that in house training and in-service training methods were preferred by most construction industry. It concluded that the attitude of top management and lack of fund was seen as the significant challenges militating against training of employees. The study recommended that manpower training and development must be sustained by all stakeholders in the industry in order to improve workers' productivity; the organization should adopt the right method in training each category of employees and carry out the need assessment for training to avoid training wrong employees.

Keywords: construction, development, manpower, training

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Authors: Manzurul Alam, John Griffiths, David Holloway, Megan Paull, Anne Clear

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Background: This paper investigates the nature of risk management practices in non-profit organizations. It is argued here that the risk exposure of these organizations has increased as a result of their entrepreneurial activities. This study explores how a particular non-profit organization formulates its risk strategies in the face funding restrictions. Design/Method/Approach: The study adopts a case study approach to report the results on how a non-profit organization diversifies its activities, tackles risks arising from such activities and improves performance. Results: The findings show that the organization made structural adjustments and leadership changes which helped to adjust their risk strategies. It also reports the organizational processes to deal with risks arising from both related and unrelated diversification strategies. Implications: Any generalization from this case example needs to be taken with caution as there are significant differences between non-profit organizations operating in different sectors. Originality: The paper makes a significant contribution to the non-profit literature by highlighting the diversification strategies along with risk performance.

Keywords: risk management, performance management, non-profit organizations, financial management

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Authors: Joseph M. Rich, Vinay A. Duddalwar, Assad A. Oberai

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Prostate adenocarcinoma is the most common cancer in males, with osseous metastases as the commonest site of metastatic prostate carcinoma (mPC). Treatment monitoring is based on the evaluation and characterization of lesions on multiple imaging studies, including Computed Tomography (CT). Monitoring of the osseous disease burden, including follow-up of lesions and identification and characterization of new lesions, is a laborious task for radiologists. Deep learning algorithms are increasingly used to perform tasks such as identification and segmentation for osseous metastatic disease and provide accurate information regarding metastatic burden. Here, nnUNet was used to produce a model which can segment CT scan images of prostate adenocarcinoma vertebral bone metastatic lesions. nnUNet is an open-source Python package that adds optimizations to deep learning-based UNet architecture but has not been extensively combined with transfer learning techniques due to the absence of a readily available functionality of this method. The IRB-approved study data set includes imaging studies from patients with mPC who were enrolled in clinical trials at the University of Southern California (USC) Health Science Campus and Los Angeles County (LAC)/USC medical center. Manual segmentation of metastatic lesions was completed by an expert radiologist Dr. Vinay Duddalwar (20+ years in radiology and oncologic imaging), to serve as ground truths for the automated segmentation. Despite nnUNet’s success on some medical segmentation tasks, it only produced an average Dice Similarity Coefficient (DSC) of 0.31 on the USC dataset. DSC results fell in a bimodal distribution, with most scores falling either over 0.66 (reasonably accurate) or at 0 (no lesion detected). Applying more aggressive data augmentation techniques dropped the DSC to 0.15, and reducing the number of epochs reduced the DSC to below 0.1. Datasets have been identified for transfer learning, which involve balancing between size and similarity of the dataset. Identified datasets include the Pancreas data from the Medical Segmentation Decathlon, Pelvic Reference Data, and CT volumes with multiple organ segmentations (CT-ORG). Some of the challenges of producing an accurate model from the USC dataset include small dataset size (115 images), 2D data (as nnUNet generally performs better on 3D data), and the limited amount of public data capturing annotated CT images of bone lesions. Optimizations and improvements will be made by applying transfer learning and generative methods, including incorporating generative adversarial networks and diffusion models in order to augment the dataset. Performance with different libraries, including MONAI and custom architectures with Pytorch, will be compared. In the future, molecular correlations will be tracked with radiologic features for the purpose of multimodal composite biomarker identification. Once validated, these models will be incorporated into evaluation workflows to optimize radiologist evaluation. Our work demonstrates the challenges of applying automated image segmentation to small medical datasets and lays a foundation for techniques to improve performance. As machine learning models become increasingly incorporated into the workflow of radiologists, these findings will help improve the speed and accuracy of vertebral metastatic lesions detection.

Keywords: deep learning, image segmentation, medicine, nnUNet, prostate carcinoma, radiomics

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Authors: Ulrich Wake, Eniman Syamsuddin

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The model for camera model identificaiton is trained using pretrained model ResNet43 and ResNet50. The dataset consists of 500 photos of each phone. Dataset is divided into 1280 photos for training, 320 photos for validation and 400 photos for testing. The model is trained using One Cycle Policy Method and tested using Test-Time Augmentation. Furthermore, the model is trained for 50 epoch using regularization such as drop out and early stopping. The result is 90% accuracy for validation set and above 85% for Test-Time Augmentation using ResNet50. Every model is also trained by slightly updating the pretrained model’s weights

Keywords: ​ One Cycle Policy, ResNet34, ResNet50, Test-Time Agumentation

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Authors: Y. Tiamaz, N. Souissi

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The purpose of this paper is to present a classification of Lean models which aims to capture all the concepts related to this approach and thus facilitate its implementation. This classification allows the identification of the most relevant models according to several dimensions. From this perspective, we present a review and an analysis of Lean models literature and we propose dimensions for the classification of the current proposals while respecting among others the axes of the Lean approach, the maturity of the models as well as their application domains. This classification allowed us to conclude that researchers essentially consider the Lean approach as a toolbox also they design their models to solve problems related to a specific environment. Since Lean approach is no longer intended only for the automotive sector where it was invented, but to all fields (IT, Hospital, ...), we consider that this approach requires a generic model that is capable of being implemented in all areas.

Keywords: lean approach, lean models, classification, dimensions, holistic view

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Authors: Naritphol Boonyakiat

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This research attempts to investigate the relationship between corporate social responsibility and students’ job performance of the Silpakorn University’s internship program within various organizations. The goal of this study is to fill the literature gap by gaining an understanding of corporate social responsibility that fundamentally relate to students’ job performance within the organizations. Thus, this study will focus on the outcomes that derive from selected employers’ qualitative assessment and evaluation forms from various companies. The results represent the perceptions of students towards the corporate social responsibility aspects and their job performance evaluation from the employers in various organizations. The findings indicate that corporate social responsibility has significant effects on students’ job performance. This study may assist us in gaining a better understanding of the integrated aspects of university and workplace environments to discover how to allocate optimally university’s resources and management approaches to gain benefits from corporate social responsibility practices toward students’ job performance within an organizational setting. Therefore, there is good reason to believe that the findings can contribute to research in the area of CSR and students’ job performance as an essential aspect of long-term success sustainability.

Keywords: corporate social responsibility, job performance, university students, internship program

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Authors: Kalyan S. Ghosh, B. L. Dhananjaya

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Snake bite causes fatal injuries in multi-organs and even many deaths due to several adverse physiological effects of various phospholipases (PLA2s) present in snake venom. Though these PLA2s bear highly homologues sequences and also structure but exhibit a different extent of those pharmacological effects. In this study, we have explored the difference in the neurotoxicity of two PLA2 namely PLA2-V, PLA2-VIIIa present in the venom from Vipera russellii. Bioinformatics studies on sequences of these two proteins along with detailed structural comparison enable us to explore the differences unambiguously. The identification of the residues involved in neurotoxicity will further lead towards proper designing of inhibitors against such killing effects of the venom.

Keywords: electrostatic potential, homology modeling, hydrophobicity, neurotoxicity, Phospholipase A2

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Authors: M. Doudi, M. H. Pazandeh, L. Rahimzadeh Torabi

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Bedsores are pressure ulcers that occur on the skin or tissue due to being immobile and lying in bed for extended periods. Bedsores have the potential to progress into open ulcers, increasing the possibility of variety of bacterial infection. Acinetobacter baumannii, a pathogen of considerable clinical importance, exhibited a significant correlation with Bedsores (pressure ulcers) infections, thereby manifesting a wide spectrum of antibiotic resistance. The emergence of drug resistance has led researchers to focus on alternative methods, particularly phage therapy, for tackling bacterial infections. Phage therapy has emerged as a novel therapeutic approach to regulate the activity of these agents. The management of bacterial infections greatly benefits from the clinical utilization of bacteriophages as a valuable antimicrobial intervention. The primary objective of this investigation consisted of isolating and discerning potent bacteriophage capable of targeting multi drug-resistant (MDR) and extensively drug-resistant (XDR) bacteria obtained from pressure ulcers. In present study, analyzed and isolated A. baumannii strains obtained from a cohort of patients suffering from pressure ulcers at Taleghani Hospital in Ahvaz, Iran. An approach that included biochemical and molecular identification techniques was used to determine the taxonomic classification of bacterial isolates at the genus and species levels. The molecular identification process was facilitated by using the 16S rRNA gene in combination with universal primers 27 F, and 1492 R. Bacteriophage was obtained through the isolation process conducted on treatment plant sewage located in Isfahan, Iran. The main goal of this study was to evaluate different characteristics of phage, such as their appearance, range of hosts they can infect, how quickly they can enter a host, their stability at varying temperatures and pH levels, their effectiveness in killing bacteria, the growth pattern of a single phage stage, mapping of enzymatic digestion, and identification of proteomics patterns. The findings demonstrated that an examination was conducted on a sample of 50 specimens, wherein 15 instances of A. baumannii were identified. These microorganisms are the predominant Gram-negative agents known to cause wound infections in individuals suffering from bedsores. The study's findings indicated a high prevalence of antibiotic resistance in the strains isolated from pressure ulcers, excluding the clinical strains that exhibited responsiveness to colistin.According to the findings obtained from assessments of host range and morphological characteristics of bacteriophage VbɸAB-1, it can be concluded that this phage possesses specificity towards A. Baumannii BAH_Glau1001 was classified as a member of the Plasmaviridae family. The bacteriophage mentioned earlier showed the strongest antibacterial effect at a temperature of 18 °C and a pH of 6.5. Through the utilization of sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis on protein fragments, it was established that the bacteriophage VbɸAB-1 exhibited a size range between 50 and 75 kilodaltons (KDa). The numerous research findings on the effectiveness of phages and the safety studies conducted suggest that the phages studied in this research can be considered as a practical solution and recommended approach for controlling and treating stubborn pathogens in burn wounds among hospitalized patients.

Keywords: acinetobacter baumannii, extremely drug- resistant, phage therapy, surgery wound

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Authors: Dawei Cai

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In this paper, we present a new wearable device that provide an automatic guidance servie for visitors. By combining the position information from NFC and the orientation information from a 6 axis acceleration and terrestrial magnetism sensor, the head's direction can be calculated. We developed an algorithm to calculate the device orientation based on the data from acceleration and terrestrial magnetism sensor. If visitors want to know some explanation about an exhibit in front of him, what he has to do is just lift up his mobile device. The identification program will automatically identify the status based on the information from NFC and MEMS, and start playing explanation content for him. This service may be convenient for old people or disables or children.

Keywords: wearable device, ubiquitous computing, guide sysem, MEMS sensor, NFC

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Authors: Sunitha Thappa

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Business environment is a set of complex interdependent dimensions that corporates have to always be vigil in identifying the influential waves. Over the year business environment has evolved into a basket of uncertainties. Every organization strives to counter this dynamic nature of business environment by recurrently evaluating the primary and support activities of its value chain. This has led to companies redesigning their business models, reinvent business processes and operating procedure on unremitting basis. A few specific issues that are placed before the present day managers are breaking down the functional interpretation of any challenge that organizations confronts, reduction in organizational hierarchy and tackling the components of the value chain to retain their competitive advantage. It is how effectively managers detect the changes and swiftly reorient themselves to these changes that define their success or failure. Given the complexity of decision making in this dynamic environment, two important question placed before the B-schools of today. Firstly, are they grooming and nurturing managerial talent proficient enough to thrive in this multifaceted business environment? Secondly, are the management graduates walking through their portals, able to view challenges from a cross-functional perspective with emphasis to customer and process rather than hierarchy and functions. This paper focuses on the need for a process oriented approach to management education.

Keywords: management education, pedagogy, functional, process

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Authors: Grzegorz Sierpiński, Ireneusz Celiński, Marcin Staniek

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The article discusses multi modal mobility in contemporary societies as a main planning and organization issue in the functioning of administrative bodies, a problem which really exists in the space of contemporary cities in terms of shaping modern transport systems. The article presents classification of available resources and initiatives undertaken for developing multi modal mobility. Solutions can be divided into three groups of measures–physical measures in the form of changes of the transport network infrastructure, organizational ones (including transport policy) and information measures. The latter ones include in particular direct support for people travelling in the transport network by providing information about ways of using available means of transport. A special measure contributing to this end is a trip planner. The article compares several selected planners. It includes a short description of the Green Travelling Project, which aims at developing a planner supporting environmentally friendly solutions in terms of transport network operation. The article summarizes preliminary findings of the project.

Keywords: mobility, modal split, multimodal trip, multimodal platforms, sustainable transport

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Authors: Asem M. Othman

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The expansion of the hospitality industry is unmistakable. Services, by nature, are intangible. Hence, service quality, in general, is a complicated process to be measured and evaluated. Hotels, as a service sector and part of the hospitality industry, are growing rapidly. This research paper was carried out to identify the quality determinants that may affect hotel guests’ service quality perception. In this research paper, each quality determinant will be discussed, illustrated, and justified thoroughly via a systematic literature review. The purpose of this paper is to set the stage to measure the significant influence of the service quality determinants on guest satisfaction. The knowledge produced from this study will assist practitioners and/or hotel service providers to imply into their policies.

Keywords: service quality, hotel service, quality management, quality determinants

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Authors: Marc Diesse, Hochschule Heilbronn

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We address the question of identifying the configuration space singularities of linkages, i.e., points where the configuration space is not locally a submanifold of Euclidean space. Because the configuration space cannot be smoothly parameterized at such points, these singularity types have a significantly negative impact on the kinematics of the linkage. It is known that Jacobian methods do not provide sufficient conditions for the existence of CS-singularities. Herein, we present several additional algebraic criteria that provide the sufficient conditions. Further, we use those criteria to analyze certain classes of planar linkages. These examples will also show how the presented criteria can be checked using algorithmic methods.

Keywords: linkages, configuration space-singularities, real algebraic geometry, analytic geometry

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Authors: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

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Authors: Najah Kalifah Almazmomi

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In the time of artificial intelligence (AI), there is a need to know the determinants of success in business management, which are taking on a new dimension. This research purports to scrutinize the Critical Success Factors (CSFs) that drive and ignite the fire of success to help uncover the subtle and profound dynamics that might be operative in organizations. By means of a systematic literature review and a number of empirical methods, the paper is aimed at determining and assessing the key aspects of CSFs, putting emphasis on their role and meaning in the context of AI technology adoption. Some central features such as leadership ways, innovation models, strategic thinking methodologies, organizational culture transformations, and human resource management approaches are compared and contrasted with the AI-driven revolution. Additionally, this research will explore the interactive effects of these factors and their joint impact on the success, survival, and flexibility of a business in the current environment, which is changing due to AI development. Through the use of different qualitative and quantitative methodologies, the research concludes that the findings are significant in understanding the relative roles of individual CSFs and in studying the interactions between them in such an AI-enabled business environment.

Keywords: critical success factors, business and management, artificial intelligence, leadership strategies

Procedia PDF Downloads 37