Work Of Analysts Research Articles

Police analysts on the job in Canada: work experiences, data work, and the move towards evidence-based policing

ABSTRACT Analysts working within police services play a key role in translating data into usable and understandable forms of knowledge for police personnel. Despite the increased focus on data and research in policing, we know little about the everyday data work of police analysts. In this article, we review the literature on analysts’ experiences and draw on survey data from analysts working in police services across Canada to examine the types of data work they routinely engage in and the value placed on their work by police personnel. Our findings suggest that analysts are underutilized and spend much of their time reporting descriptive statistics rather than performing more sophisticated analyses. While analysts perceived their work as being valued by police personnel, they did not think it was understood or used to its full extent. We conclude the paper by discussing the implications of these findings on the move towards evidence-based policing.

Artificial Neural Network Based Approach for Food Recognition Using Various Filters

Food image recognition system has various applications now a day. In this paper, we have used a machine learning supervised approach and Support Vector Machine to classify different food images. SVM has been classified to detect and recognize food images with the least modification. By applying various filters like a texture filter, a segmentation method, clustering, and a SVM approach we have achieved more accuracy than other machine learning approaches with manually extracting features. Sustenance is an indivisible piece of people groups lives. we tend to apply a convolution neural network (CNN) to the undertakings of analyst work and perceiving sustenance pictures. Clarification for the wide decent variety of styles of nourishment, and picture acknowledgment of sustenance things are typically unpleasant difficulties. Nevertheless, profound learning has been demonstrated starting late to be a genuinely extreme picture acknowledgment framework, and CNN could be a dynamic approach to managing profound learning. CNN showed on a very basic level higher precision than did old-fashioned help vector-machine-based courses with carefully assembled decisions. For sustenance picture disclosure, CNN likewise demonstrated fundamentally count higher precision than a standard technique. Generally higher precision than standard techniques.

БІЗНЕС-АНАЛІТИКА ТА ЗАСОБИ ВІЗУАЛІЗАЦІЇ ДАНИХ

The article considers topical issues of business intelligence and data visualization, their impact on effective management decisions in modern companies. The aim of the article is to study the theoretical and methodological foundations of the use of visual content for making the most effective management decisions, systematization of the most popular business intelligence tools for visualization of marketing data. The main tasks of the business analyst and the most popular analytical resources on the Internet are defined in the work. It is noted that the use of business intelligence tools helps marketers to access relevant information, visualize statistics, conduct marketing research, model risks and take timely measures to prevent them. It is determined that data visualization has become one of the most important tools of business analytics, and the use of visual content allows you to convey the essence of the message concisely and conduct a quick analysis of data with the right emphasis. The classification of visualization according to the type of result (statistical, dynamic and interactive) is given. The main stages of business analyst work are analyzed in the work, the connection between information technologies and business analytics is investigated. The most popular analytical resources on the Internet are listed, the Google Analytics web analytics tool is analyzed, and its advantages and disadvantages are identified. It is noted that the data obtained from the use of only one tool analyst can be erroneous, so you need to compare indicators using information from different sources. The factors influencing the effectiveness of visual content in social networks are indicated. The modern market of data visualization tools is analyzed. The scientific novelty of the work is reflected in the definition of the most common tools for visualizing business intelligence data. It is concluded that with the constant growth of information in all spheres of life, there is a need to use automated systems to support management and innovation decisions, especially the growing demand for software for business analysis and visualization of data.

Developing an Analytical Pipeline to Classify Patient Safety Event Reports Using Optimized Predictive Algorithms.

Patient safety event reports provide valuable insight into systemic safety issues but deriving insights from these reports requires computational tools to efficiently parse through large volumes of qualitative data. Natural language processing (NLP) combined with predictive learning provides an automated approach to evaluating these data and supporting the work of patient safety analysts. The objective of this study was to use NLP and machine learning techniques to develop a generalizable, scalable, and reliable approach to classifying event reports for the purpose of driving improvements in the safety and quality of patient care. Datasets for 14 different labels (themes) were vectorized using a bag-of-words, tf-idf, or document embeddings approach and then applied to a series of classification algorithms via a hyperparameter grid search to derive an optimized model. Reports were also analyzed for terms strongly associated with each theme using an adjusted F-score calculation. F1 score for each optimized model ranged from 0.951 ("Fall") to 0.544 ("Environment"). The bag-of-words approach proved optimal for 12 of 14 labels, and the naïve Bayes algorithm performed best for nine labels. Linear support vector machine was demonstrated as optimal for three labels and XGBoost for four of the 14 labels. Labels with more distinctly associated terms performed better than less distinct themes, as shown by a Pearson's correlation coefficient of 0.634. We were able to demonstrate an analytical pipeline that broadly applies NLP and predictive modeling to categorize patient safety reports from multiple facilities. This pipeline allows analysts to more rapidly identify and structure information contained in patient safety data, which can enhance the evaluation and the use of this information over time.

Expertise and the work of football match analysts in TV sport broadcasts

In this paper we describe expertise as a way of seeing. We use match analysis `punditry’ as a setting to show how professional vision is interactionally achieved in TV sport broadcasts through environmentally coupled gestures enhanced by camera actions and a new technology of vision called telestrator. The paper is based on data from video sequences of (English) football TV broadcasts where the pundit shows to the TV host in the studio and to the non-expert audience at home what happened during a football match. We argue that the transparency of seeing is the product of an artfully instructed process whereby the pundit shows what should be seen, how it should be made accountable, and what the audience should expect in order to fully appreciate what they see. The paper shows how broadcasted match analysis expertise interactionally achieves this through the time-critical linking of talk, gesture, and technological environment.

Stock market prediction with deep learning: The case of China

We consider stock price charts as images and use deep learning neural networks (DLNNs) for image modeling. DLNNs can imitate the work of a technical analyst to predict stock price movements in the short term with price charts and stock fundamentals (e.g., price-to-earnings ratio). We find that a deep learning model performs better than a single-layer model in the prediction of the Chinese stock market. DLNNs provide customizable statistical tools for analyzing price charts effectively. More importantly, price trends established by different periods of past daily closing prices dominate stock fundamentals in predicting future price movements.

Application of a management and storage system for knowledge generated from simulation projects as a teaching and assessment tool

During the development of a simulation project, people involved in the study acquire greater knowledge of the system being simulated. However, this knowledge is usually not externalized and ends up being lost at the end of the project. In this context, knowledge management allied with information technology may assist in information management and enable the collection, storage, and dissemination of knowledge. Thus, this paper aims to discuss and present a knowledge management system to manage and to store the knowledge generated by analysts in simulation projects. Our intention was to demonstrate a way that the knowledge can be stored and accessed at any moment by anyone to recover the development process and avoid mistakes during a simulation project. In order to achieve this goal, some graduate and undergraduate simulation courses at a Brazilian federal university were used as objects of study. At the end of the study, it was concluded that knowledge management integrated with information technology contributes to the work of simulation analysts by supporting information and knowledge management throughout the stages of the simulation projects.

PSYCHOANALYTIC MANNER AND ITS RELATION TO THE LITERATURE

This research continues the methodological discussion between psychoanalytically-oriented therapists and their colleagues, who understand the point, the process and the influence of psychotherapy through a CBT-oriented lens. The central point of research is the question of connections between psychoanalysis and literature, or even, of psychoanalysis itself as a kind of literature. The key features of a psychoanalysts mode of thinking is to be found in the plane of aesthetics. It is proposed, that, unlike a CB-therapist, who mainly goes by the rational principles of cognition, a psychoanalyst is prone to experience the reality of psychotherapy in terms of literary aesthetics, and their attempts to verbalize their understanding of the patient is based on a literary perspective. There exists certain similarity between a writers work, as he tries to embody an imaginary character onto a page, and an analysts work, as he tries to incorporate his analytic intuition into a psychodynamic hypothesis and create a psychological portrait of the patient. Thus, the article is focused on the empirical exploration of therapeutic texts, made by therapists based on viewing an unstructured first-session interview, executed by therapists with different levels of psychotherapeutic education, experience and predisposition to psychoanalytic thinking. (For measuring said predisposition an adaptation of the Comparative Psychotherapy Process Scale(CPPS) has been carried out, its inner coherence and diagnostic validity have been established. The results of simultaneous independent criterion-based analysis of the produced texts by literary experts and psychoanalytic supervisors have shown, that the literary aesthetic is an a priory feature of the descriptions of psychoanalysts, and the more so, the higher the analysts therapeutic quality. This does not so much concern the artistic value of the descriptions, but the artistic taste: the ability to distinguish kitsch and artistic form, and the ability to integrate them into new gestalts on basis of sensual harmony. Thus, the evidence supports the claim, that artistic taste is a fundamental feature of a psychoanalysts therapeutic cognition. It is particularly the aesthetic ability of the analyst, which allows for the specific non-goal-oriented approach to his therapeutic influence, which gives room to the development of the true Self according to Winnicott, and further separates the therapeutic process from the goal-oriented therapeutic learning. Thus it is concluded, that the analytic process from the position of aesthetics may fall under the risk of devolving into forms of kitsch practices.

New finance: Psychological measurement of value

Subject. The article addresses emotional factors that affect value under psychological concepts. It describes processes of obtaining information for surveys when measuring emotions, adjusting the evaluation tools, taking into account new analytical capabilities provided by the use of psychological measurement. Objectives. The study aims at creating a methodology to consider the impact of emotional factors that become apparent under the influence of psychological concepts, on value. Methods. I employ methods of induction and deduction in survey data processing. Results. The paper discloses the content of the main methods for recording emotions in the process of making a conclusion about the value by financial decision makers under the influence of psychological concepts. It demonstrates tools for implementing the methods of psychological measurement in valuation. The findings may be helpful in the work of modern appraisers and value analysts. It is especially important to use the tools for measuring emotions in conditions of digital economy, instability and crisis, a change in the market paradigm, distortion of traditional financial and economic indicators, market volatility. The use of psychological concepts complements and expands the classic assessment toolkit, improves the quality of valuation. Conclusions. The paper concludes on opportunities that financial analysts have, when applying new advances in behavioral finance and modern psychological studies. It outlines prospects for analytical tools development, using new indicators to enhance the efficiency of valuation results.

ІНТЕЛЕКТУАЛЬНА СИСТЕМА ДЛЯ ВИБОРУ МАЙБУТНЬОЇ ПРОФЕСІЇ

Finding a professional field in which a person is going to develop all his life is not easy, especially when a person does not have the tools to make accurate and informed choices. When we talk about professional orientation, we mean the psychological and pedagogical process, which aims to help choose a profession that corresponds to the skills and moods of man. On the other hand, orientation not only intends to look for a job, but also to know what motivates a person or who he would like to see himself in a few years. Professional discrimination is a process that creates controversy among young people, who often do not immediately get a higher education or decide to change careers due to lack of professional orientation. People are struck by the uncertainty about how to choose the right future profession: according to interests, according to employment opportunities, or according to the usefulness of this career. Another important factor is the future salary we will earn. Our vocation and our abilities are also factors to consider, as they will ultimately motivate us to continue our studies. To make the best decision about choosing a future career, a professional test will be the most useful tool with which a person can determine their capabilities. As modern technologies are increasingly used to analyze data around the world, it is an expected task to translate testing from a general cohort of psychological techniques into the digital world. For best results, it was decided to solve this problem using an artificial neural network. Scientists who have studied and continue to study neural networks believe that they are an almost indispensable tool in the work of analysts, because they allow you to work with both qualitative and quantitative characteristics. The main function of the developed system is to advise students and entrants on the choice of future profession, as well as to provide information in a form convenient for analyzing the results of career guidance work.

Towards Improving Transparency of Count Data Regression Models for Health Impacts of Air Pollution

In studies on the health impacts of air pollution, regression analysis continues to advance far beyond classical linear regression, which many scientists may have become familiar with in an introductory statistics course. With each new level of complexity, regression analysis may become less transparent, even to the analyst working with the data. This may be especially true in count data regression models, where the response variable (typically given the symbol y) is count data (i.e., takes on values of 0, 1, 2, …). In such models, the normal distribution (the familiar bell-shaped curve) for the residuals (i.e., the differences between the observed values and the values predicted by the regression model) no longer applies. Unless care is taken to correctly specify just how those residuals are distributed, the tendency to accept untrue hypotheses may be greatly increased. The aim of this paper is to present a simple histogram of predicted and observed count values (POCH), which, while rarely found in the environmental literature but presented in authoritative statistical texts, can dramatically reduce the risk of accepting untrue hypotheses. POCH can also increase the transparency of count data regression models to analysts themselves and to the scientific community in general.

Notes on a pandemic.

The author reflects on her experience as an analyst working in Lima, Peru, all through 2020, when the COVID-19 pandemic altered the so-called normality. She intersperses her thoughts on the anxiety and fears it generated, and how it felt to analyze over the phone or the internet. Analysts shared the surround with patients: the same uncertainties, hopelessness, fear of getting infected, and dying. Denial played a crucial role in this process—as many people disregarded the lethality of the virus—which remains to be addressed if the pandemic is to be controlled. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

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The paper deals with the main issues of creating situational centers. Making decisions in com-plex systems is a very complex problem that can be solved using decision support systems. Solving management tasks at the state level, forecasting, analyzing in conditions of hostilities and a state of emergency, overcoming the consequences of emergency situations are intersec-toral. These tasks are solved through the work of experts and analysts on the technological basis of decision support systems functioning as the part of situational management systems in the form of situational centers. Situational centers of the security and defense sector are designed to make management decisions on a complex, multifunctional governance structure, elements of which are often poorly structured and insufficiently formalized. Input information is incom-plete, ambiguous, sometimes contradictory. Thus, the determination of the functional and or-ganizational principles for the creation and development of situational management systems, based on these principles, is an urgent task. Today, the most important task for government agencies is to improve the efficiency of management activities based on comprehensive moni-toring of the current situation and prompt response to its changes. The complexity and unusual-ness of the tasks facing management structures determine the need for proper scientific, intel-lectual, information and analytical support for their solution. Therefore, summarizing the international experience of creating and using situational centers in management structures, the article proposes a substantiation of the organizational and functional structure and gives recommendations for improving the decision support technology, as well as directions and pre-requisites for creating situational centers for public authorities in the security and defense sec-tor. Approaches to achieving compatibility of their work in a single network are proposed, if necessary, and the modes of their functioning are identified.

Six Useful Websites for Practitioners Working in Schools.

A substantial, and seemingly increasing, number of Board Certified Behavior Analysts work in pre-K-12 schools. Many of them will be unfamiliar with the roles and activities of other school professionals, as well as with the structure, function, and mandates of schools. This article introduces 6 websites that are devoted to education. Accessing these free and user-friendly sites can provide practitioners with information and training activities that will help them function comfortably and competently in schools and benefit their clients to a greater extent. Our purpose in writing this article is to introduce and recommend these websites.

Female body representations

Este trabalho analisa os discursos das representações do corpo feminino nas telas pintadas pelo artista pernambucano Francisco Brennand que fazem parte da série intitulada Chapeuzinho Vermelho. A perspectiva é analisar o discurso imagético, enquanto efeito de sentido e apresentar gestos de interpretação da representação do corpo feminino ao longo dos séculos, partindo da prática de leitura do discurso imagético, doravante DI. Assim, à luz da perspectiva teórica da AD francesa, mobilizaremos os conceitos sobre os movimentos parafrásticos e polissêmicos, e tentaremos analisar tais discursos e seus modos de funcionamento que produzem sentidos. Nosso corpus de análise é constituído de 3 sequências imagéticas pertencentes à série do artista. Assim, propomos fazer uma reflexão sobre como a imagem, trabalhando no sentido de mobilizar um entrecruzamento com o contexto histórico das interpretações sobre o corpo feminino. Propomos um trabalho de analista que tenta dar conta do fato de que tais movimentos presentes no discurso são sempre reconstruídos, retomados em um novo discurso. Desse modo, enquanto discurso, as telas reportam à memória discursiva quando percebemos retomadas constantes do que é dito em outro lugar, tanto para apoiar quanto para deslocar sentidos.

MENGEMBANGKAN LEARNING ORGANIZATION DI GARK SURABAYA PT BANK CENTRAL ASIA TBK.

GARK Surabaya is one of the analyst work units in PT Bank Central Asia Tbk. (BCA), which plays an important role in lending. BCA is very aware that human resources are one of the important assets to support the sustainability of existing businesses. The development of quality human resources is BCA's commitment in implementing the bank's strategic direction to provide quality services for customers. This study aims to see the learning process at GARK Surabaya in terms of the system learning organizational model approach, to find out which subsystems are encouraging and inhibiting and the reasons, so that they can provide alternative recommendations so that the existing learning process can be more effective. The approach in this study uses qualitative methods, through interviews, observations, documents, and literature books. Interviews were conducted using an open standardized question guide. Interview guidelines include issues related to the research topic. Interview guidelines are used to maintain the conversation that occurs during the interview, so that it remains in the focus of research. The learning process at GARK Surabaya has been going well, although it is still not fully in accordance with the system of learning organization models. Dimensions of structure in the organization subsystem, dimensions of personal mastery and mental models in learning subsystems, dimensions of customers in people subsystems and technology subsystems are the dimensions and subsystems that most support the learning process at GARK Surabaya. While the dimensions and subsystems that must be considered more and improved are the vision dimensions of the organization subsystem, the strategy dimension of the organization subsystem and the knowledge subsystem (storage dimension, analysis and data mining dimensions, transfer and dissemination dimensions, and transfer and dissemination dimensions).Keywords: GARK Surabaya, learning process, learning organizations, system learning organization model

Mapping the subaquatic animals in the Aquatocene: Offshore wind power, the materialities of the sea and animal soundscapes

This paper examines the controversy around marine animal management in Taiwan Strait, where the sea has been territorialized by offshore wind power developers. Concerns have been focused on the impacts of pile-driving noise on the Taiwanese white dolphin which is on the IUCN list of extremely endangered species. To deal with the problem, both state and developers have been involved in volumetric practices which attempt to render the marine mammals knowable, and in turn, governable. While recent work on volumetric thinking has revealed that power is exercised through volume, we contend that insufficient attention has been given to those lively ‘non-human’ subjects living in the volumetric spaces. Inspired by recent scholarship on animal atmospheres and the wet ontologies, we argue that marine animals are sentient beings that cannot be known, or mapped, by the state-corporate volumetric practices which are mainly based on scientific experiments, conducted in isolated social contexts. To illustrate this, we draw on assemblage thinking and develop the idea of marine animal soundscapes. We suggest that marine animal soundscapes exist only through the embodied experience of a sensory, marine animal body, which is able to affect, and learn to be affected by, others, through non-linguistic ‘signs’, such as sound. We maintain that animal soundscapes are shaped by social, ecological and material circumstances, of which, the materialities of the sea, such as its liquidity, rapidity and fluidity, are of great importance. With an emphasis on the subaquatic animal soundscapes, our approach intends to extend social relationality to non-humans and calls for an ontology, distinct from the one with which existing volumetric analysts work.

Analyst Incentives and Stock Return Synchronicity: Evidence from MiFID II

Implemented in 2018, MiFID II changed sell-side analyst incentives in Europe, forcing analysts to justify the value they add. While the number of analysts decreases, the average stock return synchronicity with the market also decreases, implying an improvement in price informativeness. The decrease in synchronicity is larger for firms that are more important for the analysts and brokers covering them. It is also asymmetric and substantially larger for downside market movements. Our results suggest that, by changing incentives, MiFID II not only improves the quality of individual analyst work, but also achieves an improvement in the aggregate stock price informativeness.

Speech-Language Pathologists and Behavior Analysts: A Survey of Video Modeling Use and Perspectives.

Speech-language pathologists (SLPs) and board-certified behavior analysts (BCBAs) work with clients with autism spectrum disorder (ASD). In general, these practitioners support a variety of skills during treatment, including language, social skills, daily living, and academics. Video modeling (VM) is an intervention that is often used to improve skills (e.g., independent living, social, behavioral, academic) for clients with disabilities. It is unknown how SLPs and BCBAs are specifically using VM to support clients, including those with ASD. The primary purpose of this study was to use an existing perception scale to analyze SLPs' and BCBAs' perspectives on and use of VM. Results have indicated that while most practitioners have heard of VM and use it with clients, barriers related to training and video creation still exist. VM is still predominantly used in clinics and special education classrooms, indicating that this evidence-based strategy is being used, but more training and generalization support is needed.

Организация информационных потоков и управление ими как неотъемлемая функция аналитика

The article is devoted to the importance of the analyst's information work in the context of considering information analytics as flowing data analytics. The authors consider the problems of studying data flows, the laws of their formation and managing them, including their fine-tuning (modification, reorganization, adaptation), and pay a special attention to the organization of new flow that meet the research goals, analyst's personal daily participation in the process of collecting, processing, indexing and primary generalization of information.