bluuebunny/crossref_metadata_2025 huggingface dataset:
An Innovative Analysis of Predicting Melanoma Skin Cancer Using CNN and Random Forest Algorithm
Authors: Vikas Reddy Kakularam , Rama Parvathy L.
Published: November 2022

The study’s primary purpose is to propose an automatic melanoma cancer detection system using Random Forest Algorithm and Convolutional Neural Network algorithm (CNN) to detect melanoma cancer and compare their accuracy. Group 1 was Random Forest architecture with a sample size of 10, and Group 2 was a Convolutional Neural Network algorithm with a sample size of 10. They were iterated 20 times to predict the accuracy percentage of identifying melanoma cancer. Compared to Convolutional Neural Network accuracy, the Random Forest method is substantially more accurate (98%) (65%). The random forest technique has a statistical significance of p=0.0018 (p<0.05). The Independent Sample T-test has a high level of importance. In the context of this investigation, the random forest method outperforms the Convolutional Neural Network in melanoma skin cancer detection.
Classifications of E-MAIL SPAM Using Deep Learning Approaches
Authors: Anshumaanmishra  , VigneshwaranPandi
Published: November 2022

Spamming is an art used to deceive people and, in most cases, send unwanted messages that can be used by cybercriminals to trick victims and get confidential credentials from the victim. Spamming occurs via email, SMS, social networking websites calling the victim’s phone number, etc. Spamming can exist for various reasons, but it can be used for malicious purposes mainly like trying to forge the victim for gathering the personal information, bank details card details, passwords, and other confidential data about the intended user. To overcome the security breach, the spam messages are classified for the understanding of spam has been done using different methods like Machine Learning and Natural Language Processing. We propose a method to identify the email spam messages and also to classify the message using deep learning approaches such as Recurrent Neural Network (RNN), Long-Short Term Memory (LSTM), and Bilateral Long Short-Term Memory (BLSTM). We have used an email spam dataset with over 5000 spam text samples are used to train our deep learning models. The proposed method separated the sentences from the email into words followed by their root words, and each word is assigned an index number before training. We have used regularization and dropout layers in our models to reduce the chances of overfitting. The proposed method is evaluated and compared with other existing models based on the history of the loss curve, Precision-Recall, and accuracy. Based on the results, it is observed that our Bi-LSTM model produced higher accuracy than other existing systems.
Smart Stick Using Ultrasonic Sensors for Visually Impaired
Authors: Prema S. , Anand Jose , Vanitha P. , Nirmala Devi K.  , Mohamed Yaseen M. , Rajeswari C.
Published: November 2022

Tothe latest survey organized by the Times of India (ToI), currently, India is domestic to the globe’s biggest variety of sightless human beings. Among the forty million human beings throughout the world were blind, from this above 15 million blinds are from India. Technology aspires to make our lives better. Just like smartphones, smart TVs, and smart automobiles, this survey advocated us to recommend an intelligent stick that uses ultrasonic sensors for the visually impaired. An impaired individual typically faces positive problems in their everyday lifestyles however with the development in an era we can help them to guide a less difficult lifestyle. We have proposed a sophisticated intelligent blind useful resource stick that enables visually challenged human beings to navigate with ease. Though comparable merchandise is to be had within the market, they’re now no longer difficult and affordable. We have decreased the value without compromising with the elements of the smart cane as a substitute we’ve protected positive capabilities which can be mandatory.
Correlation Analysis of Voting Regression and Decision Tree Algorithm to Predict House Price with Improved Accuracy Rate
Authors: Hanuma Reddy G. , Sriramya P.
Published: November 2022

The primary goal of this study is to use efficient machine learning algorithms to anticipate better house prices, typically inflated. Materials and Methods: : This study will study the differences between near-accurate price prediction utilizing Novel Voting Regression (Group 2) and Decision Tree methods (Group 1). The sample size used to carry out this research was N=10 for each group studied. Clincle was used to calculate the sample size. The pre-test analysis was maintained at 80%. G-power is used to calculate the sample size. Statistical analysis yielded a significance value of 0.001. Results: : The accuracy of the Novel Voting Regression Algorithm for house price prediction is 82.94%, which is greater than the Decision Tree Algorithm’s 72.54%. The Independent Sample T-test has a statistical significance of 0.584. Conclusion: : As a result, it can be stated that the Novel Voting Regression technique can produce results that are almost as accurate as of the Decision Tree technique.
Damaged Licensed Number Plate Detection Based on Novel Object Oriented Classification with K-Means Algorithm
Authors: Swetha Y  , Kalaiarasi S
Published: November 2022

The aim is to detect the quality of number plates using object oriented classification in comparison with K-Means clustering. Two groups such as novel Object Oriented Classification and K-Means algorithm are applied. Total number of samples that are evaluated on this proposed methodology are 265 images. Among this sample dataset, 185 images [70%] of the dataset was taken as a training dataset and 80 [30%] was taken as a testing dataset. Programming experiment was carried out for N=7 and N=9 iterations for novel Object Oriented Classification and K-Means algorithm respectively. Computation processes were executed and verified for exactness. SPSS was used for predicting significance value of the dataset considering G-Power value as 80%. Novel Object Oriented Classification algorithm shows a high accuracy and homogeneity for damaged number plate detection, and has recognition rate of 0.593 (p>0.05). This research article is intended to implement an innovative approach to Automatic License Plate Recognition for detection of damage in licensed number plates. Comparison results show that efficiency of Novel Object Oriented Classification is better than K-means Algorithm for detecting damaged number plates.
Improve Accuracy in Prediction of Credit Card Approval Using Novel XGboost Compared with Random Forest
Authors: Yasasvi Pathipati , Magesh Kumar S.
Published: November 2022

The aim of this work is to conclude the credit card approval using XGBoost algorithm and compare it with Random Forest (RF) to improve accuracy. Prediction of credit card approval using XGboost Classifier with sample size of N=10 and logistic regression with sample size of N=10, and dataset size of 48678. The dataset contains 19 attributes that help to determine whether a person gets approval for a credit card or not. The accuracy of the Xgboost Classifier is 87.97% and loss is 12.03%, which appears to be better than Random Forest (RF), which is 82.86% and loss is 17.14 %, with a significant value p = 0.001 (p<0.05, 2-tailed) in SPSS statistical analysis. The results show that the Novel Xgboost Classifier seems to perform significantly better than Random Forest (RF) for credit card approval prediction in terms of accuracy.
Predict Attacker Behaviour on IDS with High Accuracy Using K-Nearest Neighbor Algorithm
Authors: Bhavana M  , RajendranT
Published: November 2022

This work’s main objective is to predict the attacker’s behavior pattern with high accuracy by using machine learning methods. According to the experimental and statical analysis, the proposed model has improved accuracy. The study was performed with two machine learning algorithms, K-Nearest Neighbor (KNN) and Decision Tree (DTA). On a dataset of 19,864 items, the algorithms were implemented, trained, and assessed. Two iterations have extracted the trained and tested dataset on the sample size. Each algorithm has undergone ten iterations with different test sizes to get different result sets. This study’s G-Power test for machine learning algorithms is roughly 80%. The result sets of the programming experiment have been further analyzed with statistical tools and observed that the accuracy of KNN is 99.76, while DTA is 98.84, according to the testing data. By conducting the independent samples t-tests, the statistical difference is p<0.05. This research aims to create an innovative intruder behavior prediction that uses machine learning techniques to identify data as usual or invasive. While comparing the decision tree algorithm with the K-Nearest Neighbor algorithm, the final extracted results demonstrate that the KNN was outperformed.
Reducing the “Fog of Uncertainty” Surrounding Humanitarian Aid and Disaster Response Operations
Authors: Chen Winifred X. , Houghton Nicholas M. , Caldwell Barrett S.
Published: November 2022

Evaluating the initial impact of a large-scale disaster can be difficult and misdiagnosing the breadth and severity of an event may lead to a misallocation of response resources. During natural disaster response preparation, multiple classes of distributional and deep uncertainty affect decision making, increasing the range of effects influencing strategic and tactical resource allocation plans. Planning tools for humanitarian aid and disaster response (HADR) centers must address robustness of operations despite these “fog of uncertainty” factors, rather than calculate an efficient point estimate. This paper addresses needs to identify and improve issues affecting HADR response, including mechanisms to increase the robustness of HADR plans and response capabilities. It is not necessary nor viable to eliminate all uncertainty in response allocation decisions. Instead, an exogenous uncertainties, policy levers, relationships, and measures (XLRM) chart would serve as a useful decision-support tool to identify highly impactful variables which most significantly influence uncertainty while supporting risk management and decision-making when planning or executing a response. Furthermore, such considerations would mitigate some of the fog of uncertainty associated with coordinating an initial response to a disaster. The authors address changing tempo and decision/action cycles ranging from strategic planning to tactical response in HADR centers, focusing on XLRM examination and implementation.
Systems Engineering for Innovation Portfolio Management in the Energy Industry
Authors: Holmes R. Chadwick , Zhang Zhao , Saldaña Sandra , Mallison Brad , Francis Jason
Published: November 2022

The establishment of development pipelines for innovative technologies is a familiar aspect of digital transformation within the energy industry. One variant relies on innovation teams to rapidly prototype ideas as Proofs-of-Concept (POC) that, when successful, are matured and commercialized as new technical solutions within product lines. However, as the number of ideas grows, diversity of in-scope energy systems broadens, and resources remain constrained, identifying the highest-value ideas aligned with innovation goals and enterprise strategy has become paramount. We outline a prioritization and selection (PAS) approach founded on systems engineering (SE) to manage the work progressed within an innovation team. Specifically, we adapt the tradespace methodology for design selection when stakeholder needs and project constraints create a multi-objective optimization problem. The assessment combines a rigorous stakeholder analysis and surveys to characterize a multi-attribute utility function measuring POC benefit. POC resources are estimated from anticipated duration, development needs, validation requirements, and process change required by the technical solutions. These metrics characterize cost-benefit trade-offs, complemented by innovation measures associated with each POC. The final end-to-end workflow enables innovation idea comparisons with a dashboard to guide POC selection, portfolio shaping, and work prioritization across multiple energy disciplines and industry asset classes.
International Regulation Design for Reduction of GHG Emission in Maritime Shipping by Agent-Based Simulation
Authors: Nonomura Kazuho , Hiekata Kazuo , Yoshida Junki
Published: November 2022

In order to reduce carbon dioxide emissions from international shipping, the International Maritime Organization (IMO) is discussing the future strengthening of EEDI/EEXI and the introduction of subsidies and carbon taxes. However, the stakes in international shipping are so complex that it is difficult for the IMO to predict how regulations will affect shipping companies’ decisions and markets in the future, making it difficult to determine effective regulations.In this study, we develop an agent simulator that simulates the decision-making process of actual shipping companies, and propose a method to quantitatively evaluate the response of international shipping to various regulations, thereby supporting the decision-making process of policy makers. The developed simulator outputs simulation results from 2023 to 2050 when the EEDI/EEXI reduction rate, subsidy rate, and carbon tax rate are input.In this study, we conducted simulations for 100 different regulatory proposals and plotted the results of all the proposals on a scatter plot of total carbon dioxide emissions and total benefits to support the decision making of regulatory decision makers. Furthermore, we were able to support effective regulatory decisions even when the assumptions were that the carbon emission reduction targets set by the IMO would be met and that carbon tax revenues would exceed subsidy expenditures.
A Co-Creative Approach for the Commercialization of Offshore Methane Hydrate Resources
Authors: Suzuki Kenya , Wada Ryota , Konno Yoshihiro , Hiekata Kazuo , Nagakubo Sadao
Published: November 2022

The MH21-S R&D consortium (MH21-S) established in 2019 advances technological development toward the commercialization of Japan’s offshore methane hydrate resources. This research is conducted as a part of MH21-S, funded by the Ministry of Economy, Trade, and Industry. Under the global trend toward decarbonization, there is a strong demand to combine methane hydrate production with CCS (carbon dioxide capture & storage) technology. Among the various possible combinations, we need to define the target architecture and develop strategic plans for it. However, the uncertainty and complexity of the socio-technical system make it challenging to derive a consensual decision. In this paper, we propose a co-creative approach engaging various stakeholders through workshops and model-based discussion. The workshop was designed to gather ideas from stakeholders from various backgrounds. The ideas raised in the workshops were analyzed to construct a morphological matrix to generate a comprehensive solution space. A simulation model was developed to quantitatively evaluate the wide variety of concepts, by integrating several element models, such as economic evaluations models, gas production models, and production system models. The model interface was designed to support the understanding of the complex system. Through the demonstration of this approach, we have developed a model that can provide quantified evaluations of concepts that support the consensual decision-making of the target architecture.
A Team Performance Measurement by Pulse Survey Results of Corporate Planning Members
Authors: Kimura Tomiya , Sugihara Midori , Takaramoto Mayu , Toriya Masako , Toma Tetsuya
Published: November 2022

A typical company’s corporate planning department in Japan, is under the direct control of management, and the majority of its work is to deploy management’s instructions within the company rather than to think and act on its own. As a result, members of the corporate planning department, which is supposed to function as the core of the company, have a strong sense of being told to do what they are told, resulting in a sense of stagnation. As a result, the motivation of the members of the Corporate Planning Department declines, and there are concerns about the health hazards associated with this. To solve these problems, we introduced on-on-one meeting, education and training, and behavior change initiatives to increase the motivation of the members of the Corporate Planning Department. We measured members’ motivation by conducting a pulse survey after each initiative, calculated the effectiveness of each initiative, and used a Monte Carlo simulation to determine the most effective way to order the initiatives. According to the results of the pulse survey, when corporate planning team members are forced by their supervisors to follow a one-on-one meeting policy, their performance generally worsens; however, they may be easily influenced by their management philosophy, and other indicators may increase. And from the results of the simulation, a one-on-one meeting does not appear to have an effect if started early in the organization’s formation. By contrast, conducting a one-on-one meeting after an ice breaker, such as behavior change or education, in which members collaborate with each other, is considered effective. However, it was found that the effect gradually became the same as the number of simulations increased.
Data-Driven and Real-Time Prediction Models for Highly Iterative Product Development Processes
Authors: Arjomandi Rad Mohammad , Raudberget Dag , Stolt Roland
Published: November 2022

Some high-level technical products are associated with transdisciplinary simulation-driven design processes. Therefore, their design process involves many stakeholders and is prone to frequent changes, leading to a highly iterative process with a long lead time. Despite the decades of statistical approximations and metamodeling techniques on prediction models, companies are still striving to achieve fully automated real-time predictions in early design phases. The literature study shows a gap in existing methods such as not being fully real-time or suffering from high dimensionality. This paper presents a generic model for the development process of such described products and motivation for such modeling through a series of semi-structured interviews with an automotive sub-supplier company. The proposed process model points to the digital verification in every design loop as the bottleneck which is then confirmed by interviewees. As alternative solutions to overcome the problems, a method for data-driven and real-time prediction models is presented to enable the designer to foresee the consequence of their decision in the design phase. To evaluate the method, two examples of such real-time meta-modeling techniques, developed in an ongoing research project are discussed. The proposed examples confirm that the framework can reduce lead time spent on digital verification and therefore accelerate the design process in such products.
An Investigation into Additively Manufacturable Latticed Packaging for Fresh Produce
Authors: Seng Wen Qi , Song Xue Ting , Kuo Jo-Yu , Chen Chun-Hsien
Published: November 2022

Fresh produce is most commonly stored in corrugated fibreboard containers (CFCs) post-harvest. However, CFCs and packaging fillers like foams that serve as a cushion for fresh produce are a single-use product that is costly and not environmentally friendly. Reusable plastic containers (RPCs) are an alternative to CFCs, but due to its high transmissibility of forces that lead to damage of the content as well as its high upfront cost to manufacture and implement, the adoption of RPCs is low. With the advancement in additive manufacturing, this study aims to structurally innovate RPCs by incorporating lattice configurations in them. The proposed lattice structures will translate the characteristics of cushioning materials into the container’s feature. Via direct frequency response simulation, the preliminary results demonstrated that proposed designs can sufficiently protect the fresh produce by reducing the maximum displacement experienced when subjected to loads within a common frequency range. This study hopes to inspire more efforts in reducing the consumption of CFCs and developing a more sustainable practice in the food packaging industry by adopting reusable packaging.
Adequate Method Selection for Quantifying Verbal Knowledge in Context of Composite Manufacturing
Authors: Schatz Markus Edwin
Published: November 2022

With this contribution, the quantification of verbal knowledge is being discussed. This quantification is particularly necessary in composite structural design, as mechanical, economical and technical aspects are strongly intertwined. Hence, modelling technical and economical aspects becomes relevant in context of structural design optimization of composites. With this paper, the decision on whether to utilize machine learning or fuzzy inference systems is clarified in case complex composite manufacturing techniques such as braiding are in light.
Transdisciplinary Credit Allocation Policy to Foster Regional Economic Development Through Financial Institutions
Authors: Trigos Federico , Aldana Carlos Mario
Published: November 2022

Corporate philosophies of multiple financial institutions, including development banks, address regional economic development as their corporate driver. Regardless the latter, regional development financial institutions usual priority focuses primarily on individual application credit risk assessment, without a designed long term policy to impact strategic industries and its regional key economic objectives. With a transdisciplinary approach that involves a number of engineering (engineering economics, mathematical programming) and non engineering disciplines (finance, accounting, banking, policy making) that takes into account the full set of stakeholders (credit applicants, financial institutions, society at large, governments, among others), the contribution of this work impact the future of engineering practice by providing a framework (a method that includes a ready to use decision support tool) to design a transdisciplinary credit allocation policy that financial institutions could rely on to have a targeted aim significant impact in the strategic economic transformation of focused regions. A numerical illustration is provided to highlight the specifics of this transdisciplinary policy for the benefit of practitioners and society.
Managing and Governing Integrated Research Programmes: Lessons from Organizational Studies
Authors: Wever Mark , Romera Alvaro , Wognum Nel , Shah Munir
Published: November 2022

To solve complex problems, researchers are increasingly working in large, integrated research programmes. Integration of projects within a single programme rather than supporting a range of individual, more autonomous projects, is supposed to lead to several benefits, including: creating and enhancing synergies amongst projects, improving collaboration and knowledge exchanges amongst researchers from different disciplines, realizing efficiency gains, and generating a higher return on investments in R&D. However, often these advantages are insufficiently realized in practice and large-scale integrated programs instead incur high overhead costs, frustrate researchers, and realize insufficient integration and collaboration. Why do integrated programmes sometimes fail to realize their lofty ambitions? In the present paper, we use the literature on governance, management studies, and organizational economics to analyse several key problems plaguing integrated programmes. We argue that these problems can be linked to the implementation of programme management systems and coordination mechanisms that are poorly aligned with the unique characteristics of integrated programmes. We develop guidelines for funding agencies and programme managers to implement systems and mechanisms that are a better fit for purpose and that enhance collaboration.
Utilizing Transdisciplinary Project-Based Learning in Undergraduate Engineering Education
Authors: Davis Lacey M. , Caldwell Barrett S.
Published: November 2022

Transdisciplinary project-based learning is an opportunity for undergraduate engineering students to acquire valuable skills in translating individual knowledge to other disciplines and interacting with non-academic stakeholders. In the authors’ project-based education experience, these skills have been developed in both course-based and co-curricular learning contexts. The necessary foundation to implement transdisciplinary projects in education is introducing students to collaboration across disciplines as well as with stakeholders, consummers, and users. Furthermore, students practice holistic problem-solving techniques that account for emergent behaviors during project development. Emergent behaviors are inherent to complex real-world problems. Engineering students would benefit from the opportunity to practice adapting to evolving project requirements and goals in low-risk, academic settings prior to enduring these challenges at the career level. This active learning approach can increase student agency and diversity as students work in multi-disciplinary teams on relevant problems, drawing from previous experiences. Additionally, students learn the value of qualitative data for characterizing exigencies of stakeholders, consummers, and users that are often unavailable from quantitative data, though generally more emphasized for use in engineering design decisions. Students participating in transdisciplinary project-based learning gain agency and develop a skillset for investigating the cross disciplinary implications and sociotechnical contexts of real world problems.
Student Learning Journey Map: A Design Toolkit for Enriching Learning Experience
Authors: Hussadintorn Na Ayutthaya Duangthida , Koomsap Pisut
Published: November 2022

Engineering education has gradually moved away from knowledge-focused teacher-centered learning to competence-focused student-centered learning to exposing students to different learning activities as experience gained is critical to their knowledge internalization for competence development. Several teaching and learning methods have been introduced to the discipline as an effective alternative accelerator for student learning to intensive lectures and laboratory sessions and contributors supporting the outcome-based learning. However, some instructors may find it challenging to utilize the methods for enriching student learning journeys because specific implications are required for individual methods and the alignment to the content and other course design components. Consequently, this would lead to malfunctioned and unengaged journeys that impede achieving course learning outcomes. Therefore, this paper presents a course planning and preparation toolkit under the view of students to enrich their learning experience. The toolkit is developed based on the LOVE learning experience model and Kolb’s learning cycle. It navigates the instructors through the process of transforming a course into an engaging and constructive learning journey, with a step-by-step visual representation of how to choose and arrange the methods and prepare other course components. An intensive graduate course on Product Design and Development is employed to exemplify the toolkit.
Doing Transdisciplinary Studies Through the Lens of Intervention Based Research
Authors: Mathiasen John Bang , Clausen Pernille
Published: November 2022

Transdisciplinary research commences with exploratory research to understand and solve complex real-world problems followed by explanatory research to generate academic knowledge. This paper conceptualises transdisciplinary engineering through the lens of intervention-based research, which seems useful to solve societal problems when practical knowledge to handle the problematic situation contradicts solution proposals emerging from prevalent theories. The proposed model combines academic knowledge, practical knowledge, and artefact portraying the problematic situation into means to achieve the end, which when implemented transforms the problematic situation into the desired situation. To explicate the proposed model, the study draws on a longitudinal research conducted by the two authors of this paper. In this study, which focuses on designing digitalised solutions for data-driven decision-making at shop floor level, we faced serve research-related challenges. The academic knowledge revealed a clear picture of how to design the solution, but the practical knowledge exposed that the digital solution was merely an illusion; i.e. a gap between theories and practical understanding. The proposed model to handle this gap forwards the role of artefacts and suggests that artefacts, academic knowledge and practical knowledge rank alongside.
A Socio-Technical Regime Transitions Model for Gerontechnology Service Design: Privacy, Information Security and Cyber Security in Focus
Authors: Kowalski Stewart James , Østby Grethe
Published: November 2022

In this paper, we present on ongoing research to use a socio-technical privacy, information security and cybersecurity model to support the design, development and delivery processes of health care services for aging in place. The current research in gerontechnological services development is reviewed, and experiences from the use of serious games to evaluate the model are outlined.
Study of the User Behaviour Caused by Automatic Recommendation Systems Call to Action
Authors: Kopanitsa Georgy , Kovalchuk Sergey
Published: November 2022

Diagnostics accuracy and usability of symptom checkers have been researched in several studies. Their ability to set a correct diagnosis especially in the urgent cases is questionable. There is one aspect of symptom checkers that has not been deeply studied yet. It is their ability to motivate patients to follow up after receiving a direct recommendation and to decrease a load on the health care professionals. The goal of this research is to study how patients behave after receiving a recommendation from a symptom checker and motivation of this behavior. We studied how patients react on the symptom checker recommendations and the motivation behind this behavior. In total we invited 3615 patients to have a symptom checker screening; 2374 of them agreed to run a symptom checker screening; 867 of them agreed to participate in the study. The proportion of the patients who agreed to have a symptom checker screening. So, we can clearly see that symptom checker screening doesn’t result in a significant decrease of the load on healthcare professionals. This is supported by the quantitative study results. The patients emphasized the ease of use of the tool and clearness of the recommendations it gives. However, they perceived it as rather a second opinion tool or a tool that helps to prepare to the doctor’s visit.
Development and Implementation of the Data Science Learning Platform for Research Physician
Authors: Begic Fazlic Lejla , Schacht Marvin , Morgen Marlies , Schmeink Anke , Lipp Robert , Martin Lukas , Vollmer Thomas , Winter Stefan , Dartmann Guido
Published: November 2022

Data analysis and their application are the unavoidable factors in the activities analyses in health care. Unfortunately, the acquisition of data from large available medical databases is a complex process and requires deep knowledge of computer science and especially knowledge of tools for data management. According to the European General Data Protection Regulation, the problem becomes much more complex. Recognizing these problems and difficulties, we have developed a Data Science Learning Platform (DSLP) that primarily targets practitioners and researchers but also the computer science students. Using our proposed tool chain together with the developed graphical user interface, data scientists and research physicians will be able to use available medical databases, apply and analyze different anonymization methods, analyze data according to the patient’s risk and quickly formulate new studies to target a disease in a complex data model. This article presents a clinical research discovery toolbox that implements and demonstrates tools for data anonymization, patient data visualization, NLP-tools for guideline search and data science learning tools.
Reporte de Mercados Financieros - segundo trimestre de 2014
Authors: Vargas Hernando , Cardozo Pamela , Benítez Sandra , Rojas Juan Sebastián , Cardozo Nathali , Martínez Diego Alejandro , Moreno José Fernando , Patiño Lina , Rassa Juan Sebastián , Venegas Tatiana , Paz Juan Camilo , Medina Juan Pablo
Published: November 2022

El segundo trimestre de 2014 estuvo caracterizado por una menor incertidumbre en los mercados financieros internacionales como resultado de varios factores, entre ellos las mejores perspectivas de la economía China luego que el Gobierno y el Banco Central de ese país anunciaran medidas de estímulo y se publicaran algunos datos mejores a los esperados; y la continuidad de las políticas monetarias expansivas por parte de bancos centrales de países desarrollados las cuales fueron recibidas positivamente por el mercado.
Reporte de Mercados Financieros - tercer trimestre de 2013
Authors: Vargas Hernando , Cardozo Pamela , Benítez Sandra , Rojas Juan Sebastián , Cardozo Nathali , Martínez Diego Alejandro , Moreno José Fernando , Patiño Lina , Rassa Juan Sebastián , Venegas Tatiana
Published: November 2022

El Banco de la República (BR) genera información para la toma de decisiones, la rendición de cuentas y la difusión al público. En particular, el Reporte de Mercados Financieros está enmarcado dentro del principio de difusión al público y contribuye a cumplir con el servicio que presta el Banco de ofrecer información e investigación económica de calidad.
Reporte de Mercados Financieros - tercer trimestre de 2014
Authors: Vargas Hernando , Cardozo Pamela , Benítez Sandra , Rojas Juan Sebastián , Cardozo Nathali , Martínez Diego Alejandro , Moreno José Fernando , Patiño Lina , Rassa Juan Sebastián , Venegas Tatiana , Rincón Cristiam Leonardo , Medina Juan Pablo
Published: November 2022

El tercer trimestre de 2014 estuvo caracterizado por una mayor incertidumbre en los mercados financieros internacionales con respecto al trimestre anterior, principalmente ante la incertidumbre sobre el inicio de la normalización monetaria por parte de la Reserva Federal. Algunos factores como las tensiones geopolíticas en Europa y Medio Oriente, y la publicación de datos económicos desfavorables en la Zona Euro, aumentaron la percepción de riesgo en este periodo.
Reporte de Mercados Financieros - cuarto trimestre de 2014
Authors: Vargas Hernando , Cardozo Pamela , Benítez Sandra , Rojas Juan Sebastián , Cardozo Nathali , Martínez Diego Alejandro , Moreno José Fernando , Patiño Lina , Rassa Juan Sebastián , Venegas Tatiana , Rincón Cristiam Leonardo , Medina Juan Pablo
Published: November 2022

El Banco de la República (BR) genera información para la toma de decisiones, la rendición de cuentas y la difusión al público. En particular, el Reporte de Mercados Financieros está enmarcado dentro del principio de difusión al público y contribuye a cumplir con el servicio que presta el Banco de ofrecer información e investigación económica de calidad.
Orangutan Phryne, apes and humans
Authors:   Moscow Zoo, Science Department, B. Gruzinskaya St, 1, Moscow, 123242, Russia, Khlyupin Sergey Alekseevich , Vorontsova Elena Leonidovna ,   Lomonosov Moscow State University, Anuchin Research Institute and Museum of Anthropology, Mokhovaya st., 11, Moscow, 125009, Russia
Published: November 2022

Introduction. In the article the life of a female orangutan named "Phryne" is described. Phryne lived in the Moscow Zoo in 1927–1937. Now her body, preserved by taxidermy, is kept in the Museum of Anthropology of the Lomonosov Moscow State University. The experience of keeping monkeys and apes in captivity can explain the influence of nutrition, restriction of mobility, deprivation on the physical and mental health of human. Materials and methods. Materials from scientific and popular publications, as well as archival materials are used in this work. Analytical and chronological research methods were used. Results. Data on Phryne's physical development and blood counts are given in the article. Phryne had such traits of character as curiosity and attachment to the keeper, among others. The article contains information of her skills and abilities, favorite games and relationships with other apes and with people. In December 1933 a fire occurred in the monkey house. The female chimpanzee Mimosa and the male orangutan Moritz died from carbon monoxide. Phryne was the only one left. She died in 1937 of dysentery at the age of ten. Conclusion. Phryne was a true legend of the Moscow Zoo, she was often written about in newspapers, photos were published. The experience in keeping her made an invaluable contribution to the development of Russian primatology. Phryne was stuffed by the famous taxidermist N.K. Nazimov.
Potential international crimes in Ukraine: should atrocities in Bucha be classified as genocide, war crimes, or crimes against humanity?
Authors: Tchobo D. L. R.
Published: November 2022

The dilemma between the root of the word Genocide and its legal meaning is affecting the international criminal justice system. The proof is that Presidents Volodymyr Zelenskyy of Ukraine and Joe Biden of the USA called the atrocity crimes observed in Ukraine “Genocide”. The purpose of this study is to examine whether the atrocities that recently occurred in Bucha could be qualified as a crime of genocide. This article substantially analyzed the meaning of the terms composing the word genocide in the context of the nature of those atrocity crimes. In this regard, it was found that there is etymologically a gap between the legal meaning of genocide and the nature of the crime in question which shields its alleged perpetrators from impunity. Thus, this paper attempted to demonstrate that the alleged atrocity crimes observed in Bucha could not be classified as genocide and then, exposed the potential international crimes committed in Ukraine.
Service in the State Bureau of Investigation of Ukraine bodies as a type of public service
Authors: Didenko O. M. , Salmanova O. Yu.
Published: November 2022

Public service in the bodies of the State Bureau of Investigation of Ukraine has been defined as the main mechanism of these bodies functioning, which is manifested in the multifaceted activities of the staff and employees of the Bureau. The application of the laws of Ukraine “On the State Bureau of Investigations” and “On the State Service” regarding service in the bodies of the State Bureau of Investigations of Ukraine has been analyzed. It has been concluded that the service in the bodies of the State Bureau of Investigation of Ukraine is a derived concept from the civil service in Ukraine.

A number of cases of using the Law of Ukraine “On State Service” rather than the specific Law of Ukraine “On the State Bureau of Investigation” have been given when it comes to service in the bodies of the State Bureau of Investigation of Ukraine. The following signs of service in the bodies of the State Bureau of Investigation of Ukraine have been identified: service focus on satisfying public interests; occupying a public position; the act of appointment to a position or the result of a competition is the basis for the emergence of legal relations (service); the professional basis of prevention, detection, termination, disclosure and investigation of criminal offenses.

It has been established that regulatory, organizational, personnel and other principles of service in the bodies of the State Bureau of Investigation of Ukraine have their own specifics compared to public service, although they are covered by this concept. Similar signs of service in the bodies of the State Bureau of Investigation of Ukraine and the public service have been given. Service in the bodies of the State Bureau of Investigation of Ukraine has been defined as a public, professional, politically impartial activity for the prevention, detection, termination, disclosure and investigation of criminal offenses within their competence, which is carried out by employees appointed to positions in the bodies of the State Bureau of Investigation of Ukraine.
The phenomenon of dormant inheritance in inheritance law
Authors: Kukhariev O. Ye.
Published: November 2022

The article is devoted to clarifying the essence of the phenomenon of dormant inheritance in inheritance law. It has been concluded that the right of ownership of the inherited property is acquired by the heir retrospectively from the time the inheritance was opened, regardless of the legal regime of the inherited property. However, until the moment of state registration of the right of ownership, the heir is limited in his/her ability to dispose of the inherited real estate, in particular by alienating it. However, this limitation does not at all indicate that the heir has not acquired the right of ownership of the inherited property. The heir can transfer the inherited property to management, enter into an agreement on changing the size of shares in the inheritance.

It is emphasized that a necessary condition for the emergence of the right of ownership of the inheritance is its acceptance by the heir in the manner and terms determined by civil legislation.

The theory of splitting the ownership of inherited property is analyzed, according to which the emergence of the right of ownership of hereditary movable property is associated with the time of the opening of the inheritance, and for immovable property – with the date of state registration of rights to it. The contentiousness of the theory of splitting the ownership of inherited property is substantiated due to its inconsistency with the construction of universal legal succession.

The phenomenon of dormant inheritance characterizes the actual state of the objects of inheritance from the time of the opening of the inheritance to the moment of its acceptance by the heir. Legally, such an interval of the state of statelessness of property does not exist, taking into account the rule of retroactive acceptance of inheritance established in the law. Thus, according to part 5 of article 1268 of the Civil Code of Ukraine, regardless of the time of acceptance of the inheritance, it belongs to the heir from the time of opening the inheritance, that is, from the moment of the death of the testator or his/her declaration as deceased. It is emphasized that the provision on retroactive acceptance of inheritance is a legal fiction.
Criminal law characteristics of mass destruction weapons as a criminal offense constructive objective feature (Articles 439, 440 of the Criminal Code of Ukraine)
Authors: Shamsutdinov О. V.
Published: November 2022

The norms of international and national legislation, which determine the definition and meaning of the concept of mass destruction weapons, as well as each of its components – chemical, biological (in particular, toxin) and nuclear weapons – have been studied. It has been established that a constructive objective feature of the crimes provided for in Articles 439 and 440 of the Criminal Code of Ukraine is not any weapon of mass destruction, but only those prohibited by international treaties, the consent of which is binding on the Verkhovna Rada of Ukraine. Considering that the highest body of the legislative power of Ukraine has not ratified the international treaty on the prohibition of nuclear weapons, approved by the General Assembly of the United Nations on July 7, 2017, the position of the scientists who believe that as part of the crime of “use of mass destruction weapons” (Article 439 of the Criminal Code of Ukraine), nuclear weapons are not part of the concept of “weapons of mass destruction” has been supported.

Doctrinal approaches to distinguishing the object, means and instrument of committing a criminal offense have been considered, on the basis of which it has been concluded that the object of the crime is a “passive” feature of the composition of the criminal offense, it is characterized by a criminal influence on it in the form of action or inaction, its properties are provided by the subject of the crime use in the more or less distant future. Weapons of mass destruction as part of the criminal offense provided for in Art. 440 of the Criminal Code of Ukraine, is the subject of this crime.

The means of committing the crime is an “active” feature of the composition of the criminal offense, its properties are used by the criminal to create favorable conditions and facilitate the implementation of the illegal act. The instrument of the crime is also an “active” feature of its composition. Its properties are always used by the criminal directly when committing the crime to cause or threaten to cause significant damage to the object of criminal law protection. As part of the criminal offense provided for in Art. 439 of the Criminal Code of Ukraine, weapons of mass destruction are the means of committing this crime.
Finances of the Nation: The Impact of COVID-19 on Provincial and Local Government Finances
Authors: Behro Ayaka , Smart Michael
Published: November 2022

In this article, Ayaka Behro and Michael Smart explore the impact of COVID-19 on provincial government finances. While spending rose in all provinces in the 2020-21 fiscal year, so did revenues in many provinces, cushioning the impact on deficits. While grants and income tax revenues rose in many provinces, largely owing to federal policies, consumption tax and natural resource revenues fell sharply. Comparing provinces, higher COVID-19 caseloads were associated with higher health spending and lower consumption tax revenues. These findings suggest that COVID-19 has had a more damaging impact on provincial finances than initial forecasts had suggested.
Duha Printers Revisited: Issues Regarding Corporate Control
Authors:   EY Law LLP, Toronto, Taylor Roger , Marcil Marie-Claude ,   EY Law LLP, Montreal
Published: November 2022

In 1998, the Supreme Court of Canada issued its decision in Duha Printers. This was the first case dealing with the concept of de jure control of a corporation that the court had considered since its decision in Imperial General Properties in 1985. In Duha Printers, the court effectively restored the Buckerfield's test of control and set out a schematic basis for determining the person (if any) that controls a corporation at a particular time, and the evidentiary basis on which that person could be legally deprived of such control. The court's reasons for judgment raise a number of issues in respect of the concept of de jure control, including the scope of application of the decision, the continuing authority of the Supreme Court's two decisions previous to Duha Printers that appeared to have strayed from the Buckerfield's test of control, the limitation of the category of agreements that may be relevant to the control question, and the scope of and rationale for exceptions to that limitation. This article explores a number of de jure control issues decided or commented on by the court, and raised by the reasons for judgment, in Duha Printers.