Methanias Colaço Júnior
Universidade Federal de Sergipe, Dsi, Faculty Member
Research Interests:
Research Interests:
Contexto: Apesar do avanço da tecnologia, muitos processos, especialmente no setor público, ainda necessitam de buscas manuais ou não inteligentes, para construção de conhecimento. Para as auditorias do Ministério da Saúde e do Sistema... more
Contexto: Apesar do avanço da tecnologia, muitos processos, especialmente no setor público, ainda necessitam de buscas manuais ou não inteligentes, para construção de conhecimento. Para as auditorias do Ministério da Saúde e do Sistema Único de Saúde (SUS), as diversas fontes de pesquisa a serem exploradas provocam demora e altos custos. Objetivo: Avaliar preliminarmente uma ferramenta, baseada em recuperação de conteúdo textual, o Sussurro, para coletar e apresentar as diversas matérias relacionadas à saúde pública, as quais podem nortear auditorias. Método: Prova de conceito do Sussurro. Resultados: Entre mais de 2 milhões de registros de matérias, 56.053 foram classificadas como indícios para auditoria em saúde. Conclusão: O Sussurro otimiza a seleção de conteúdo necessário para executar uma auditoria, beneficiando a investigação e o combate à corrupção na área de saúde.
The study of cell’s electric properties began in XVIII. Since then, several researchers began focusing their studies in biomedical signals, making way for today’s high precision tech for modern medicine - expensive and used by... more
The study of cell’s electric properties began in XVIII. Since then, several researchers began focusing their studies in biomedical signals, making way for today’s high precision tech for modern medicine - expensive and used by professionals. However, the emergence of new research fields in the biomedical area like monitoring of human activity and human-machine interface brought the need to measure biomedical signals through simple devices. In addition, there was a growth of the DIY (do-it-yourself) movement boosted by prototyping platforms such as Arduino and Raspberry-pi. Thus, came the idea to develop YouMake, a platform for acquisition and conditioning of biomedical signals with low cost, easy prototyping, versatile and generic. For evaluation purposes, an experimental study using YouMake with twenty-four participants was divided into two groups, the first consisting of participants with experience in the study area and the latter represented by participants with no experience. Usability and prototyping time of the participants in the prototyping of the platform for the acquisition of three biological signals were evaluated: ECG, EMG and EOG. The usability and prototyping time of the participants were evaluated in the prototyping of the platform for the acquisition of three biological signals: ECG, EMG and EOG. The results were statistically analyzed using the Shapiro-Wilk, Levene and t-student tests, which showed that there was no statistical difference between the means of the experienced and the non-experienced groups. This showed that both experienced and inexperienced people in the study have the same ease in using the platform.
Research Interests:
Research Interests:
Contexto: A evolução dos meios de comunicação tem contribuído com a disseminação de notícias falsas, principalmente após o surgimento das redes sociais digitais. A velocidade com que estas notícias se espalham tornaram inviável a checagem... more
Contexto: A evolução dos meios de comunicação tem contribuído com a disseminação de notícias falsas, principalmente após o surgimento das redes sociais digitais. A velocidade com que estas notícias se espalham tornaram inviável a checagem manual desse imenso volume de dados. Diante deste contexto, trabalhos em diversas áreas têm sido realizados a fim de tentar minimizar os danos causados pela proliferação das denominadas fake news. Objetivo: O objetivo deste trabalho é avaliar a eficácia dos métodos mais utilizados para verificar correspondência de textos, no contexto da detecção de notícias falsas, tendo como base as eleições presidenciais brasileiras de 2018, bem como fazendo um comparativo com os resultados da eleição norte-americana de 2016, publicados na literatura. Adicionalmente, uma visão geral das fakes por seguidores de cada candidato é apresentada. Método: Foi planejado e executado um experimento controlado, para comparar a eficácia dos métodos selecionados. Resultados: O...
Research Interests: Physics and Humanities
Research Interests:
Abstract Context: The criminality phenomenon affects the quality of life, the economic growth and the reputation of a nation. Each year, governments spend millions of dollars fighting violence, and consequently, crime prevention and... more
Abstract Context: The criminality phenomenon affects the quality of life, the economic growth and the reputation of a nation. Each year, governments spend millions of dollars fighting violence, and consequently, crime prevention and control are highly concerning issues to the public safety agencies. Objective: Applying Data Science fundamentals to analyze open government data on the crimes that occurred in the Brazilian States. Method: We have conducted a controlled experiment to discover the association rules (AR) between the crimes and the States. Additionally, we have developed a ranking of the most dangerous States. Results: From a general viewpoint, with weights for all available crimes, Paraná was the most dangerous local during all the assessed years, followed by Rio de Janeiro. From the single perspective of murders, in 2019, the States of Roraima, Rio Grande do Norte, Sergipe, Acre and Pernambuco were ranked as the ten most violent ones, being Pernambuco and Acre among the most dangerous States from the two perspectives (weighted average and murders). Conclusion: The Data Science enables the execution of more precise diagnoses. The year of 2019 presented a general drop in the crime rates, with special emphasis on Paraíba, Goiás, Rio Grande do Norte and Ceará.
Research Interests:
Research Interests:
Context: Nowadays, people do not only navigate, but also contribute content to the Internet. Thoughts and opinions are written on rating sites, forums, social networks, blogs and other media. Such opinions constitute a valuable source of... more
Context: Nowadays, people do not only navigate, but also contribute content to the Internet. Thoughts and opinions are written on rating sites, forums, social networks, blogs and other media. Such opinions constitute a valuable source of information for companies, governs and consumers, but it would be humanly impossible to analyze and locate the opinions in those assessments, due to the large volume and different origins of the data. For this, approaches and techniques of opinion mining in texts are used. Objective: To identify and characterize the techniques used for mining data in public opinion repositories regarding hotels, since the opinion mining area has offered necessary subsidies for decision-making related to hotel management. Besides, to identify, specifically, studies that investigated the opinions about the sustainability of hotels. Method: A systematic mapping was performed to characterize the research area. Results: It was identified that, among the main approaches, 31% of the works found use only data mining, while 55% exclusively use machine learning techniques, and 14% both. Conclusion: The most relevant studies in such research lines adopt machine learning algorithms such as Naive Bayes, SVM, LDA, decision tree, besides aspect-based techniques and SentiWordNet lexicon dictionaries. There are still opportunities to explore opinion mining solutions in online hotel reviews, mainly by taking into consideration aspects related to sustainable practices and sustainability levels practiced by each hotel.
Research Interests:
Open Source Software (OSS) mailing lists are used by developers to discuss software engineering tasks performed in the project. In the last years, researchers have been conducting mailing lists linguistic analyses for understanding the... more
Open Source Software (OSS) mailing lists are used by developers to discuss software engineering tasks performed in the project. In the last years, researchers have been conducting mailing lists linguistic analyses for understanding the intricacies of OSS development. An unpublished approach for that is to use NeuroLinguistic Theory (NT). NT postulates the use of a Preferred Representational cognitive System (PRS)
Research Interests:
Research Interests:
Data quality is one of the bases for effective data mining. Flexible, consistent and extensible data storage is one of the requirements for effective data analysis. For more than 15 years, researchers in the database and decision making... more
Data quality is one of the bases for effective data mining. Flexible, consistent and extensible data storage is one of the requirements for effective data analysis. For more than 15 years, researchers in the database and decision making world have been studying the construction of data repositories for data analysis. Named data warehouses, these repositories are historical databases, which are
Research Interests: Computer Science, Software Engineering, Decision Making, Data Mining, Data Analysis, and 12 moreSoftware Development, Data Warehousing, Data Warehouse, Mining Software Repositories, Data Quality, Data storage, Organic production, Decision making process, Software Development in Agile Environment, Capability Maturity Model, Data Warehouses, and Data Gathering
Research Interests:
Context: Software code review aims to early find code anomalies and to perform code improvements when they are less expensive. However, issues and challenges faced by developers who do not apply code review practices regularly are... more
Context: Software code review aims to early find code anomalies and to perform code improvements when they are less expensive. However, issues and challenges faced by developers who do not apply code review practices regularly are unclear. Goal: Investigate difficulties developers face to apply code review practices without limiting the target audience to developers who already use this practice regularly. Method: We conducted a web-based survey with 350 Brazilian practitioners engaged on the software development industry. Results: Code review practices are widespread among Brazilian practitioners who recognize its importance. However, there is no routine for applying these practices. In addition, they report difficulties to fit static analysis tools in the software development process. One possible reason recognized by practitioners is that most of these tools use a single metric threshold, which might be not adequate to evaluate all system classes. Conclusion: Improving guidelines...
Research Interests:
Requirements elicitation is one of the early stages of any software development methodology, leading directly into the product to be developed. In this research presents a survey intent to identify the techniques of requirements... more
Requirements elicitation is one of the early stages of any software development methodology, leading directly into the product to be developed. In this research presents a survey intent to identify the techniques of requirements elicitation, when using agile methods, verifying the prevalence by iterative elicitation and as technical meetings. The conclusions indicated that most information technology professionals adopt Scrum as agile method, and elicitation of requirements made under incrementally.
Fast delivery of functional parts has been one of the most complex challenges in the software development process. This article aims at using a systematic review of literature between 2005 and 2015, to identify the state of the art on the... more
Fast delivery of functional parts has been one of the most complex challenges in the software development process. This article aims at using a systematic review of literature between 2005 and 2015, to identify the state of the art on the technical continuum integration and tools of version control, Subversion and Git, identified as the most used. The works found are analyzed and presented in this article
Research Interests:
Research Interests:
Contexto: Crime é um problema social comum e complexo, que afeta a qualidade de vida, o crescimento econômico e a reputação de uma nação. Governantes e a sociedade em geral têm tido enormes problemas causados por esse fenômeno. A cada... more
Contexto: Crime é um problema social comum e complexo, que afeta a qualidade de vida, o crescimento econômico e a reputação de uma nação. Governantes e a sociedade em geral têm tido enormes problemas causados por esse fenômeno. A cada ano, os governos gastam milhões de dólares combatendo a violência e, consequentemente, a prevenção e o controle do crime são questões de grande preocupação para as agências de segurança pública. Objetivo: Aplicar fundamentos de Data Science e fornecer um modelo automatizado, constantemente atualizado, para analisar dados abertos governamentais relacionados aos crimes ocorridos em Minas Gerais. Método: Um experimento foi executado para descoberta de associações entre os municípios, Regiões Integradas de Segurança Pública (RISPs), crimes e alvos de roubo e furto. Adicionalmente, foram desenvolvidos rankings com os municípios mais perigosos. Resultados: Do ponto de vista geral, com ponderações para os crimes, os munícipios de Belo Horizonte, Confins e Co...
Research Interests:
Research Interests:
Research Interests: Psychology and Empathy
Em um mercado continuadamente competitivo, as empresas estão dependendo cada vez mais de sistemas informatizados para reduzir custos e aumentar sua produtividade. Uma falha no mapeamento ou na definição dos processos de desenvolvimento de... more
Em um mercado continuadamente competitivo, as empresas estão dependendo cada vez mais de sistemas informatizados para reduzir custos e aumentar sua produtividade. Uma falha no mapeamento ou na definição dos processos de desenvolvimento de software pode provocar sérios riscos às organizações, que passaram a reconhecer a importância das tecnologias para o negócio. Com isso, as empresas passaram a adotar práticas e metodologias para gerenciar os serviços de TIC e do processo de desenvolvimento de software. O objetivo deste trabalho foi apresentar os resultados de um survey realizado com 52 gestores de TIC de empresas do estado de Sergipe para investigar a adoção de práticas de governança de TIC e processos de desenvolvimento de software nestas empresas. O produto deste estudo é um registro do panorama da adoção de práticas de governança e da utilização de processos de desenvolvimento de software pelas empresas sergipanas. Observou-se que 19,2% dos entrevistados indicaram que as empresa...
Research Interests:
Research Interests:
Journal of Research and Practice in Information Technology, Vol. 47, No. 1, February 2015 Copyright© 2015, Australian Computer Society Inc. General permission to republish, but not for profi t, all or part of this material is granted,... more
Journal of Research and Practice in Information Technology, Vol. 47, No. 1, February 2015 Copyright© 2015, Australian Computer Society Inc. General permission to republish, but not for profi t, all or part of this material is granted, provided that the JRPIT copyright notice is given and that reference is made to the publication, to its date of issue, and to the fact that reprinting privileges were granted by permission of the Australian Computer Society Inc.
Research Interests: Cognitive Psychology, Computer Science, Item Response Theory, Learning Styles, Cognitive Neuropsychology, and 15 moreNeurolinguistics, Cognitive Style, Estatística, Experimental Software Engineering, Neurolinguistic programming, Learning Strategies, Experimentation, Requeriments Engineering, Cognitive Strategies, Cognitive Learning Strategies, Neuroaprendizagem, Neurolingüística, Engenharia De Requisitos, Programação Neurolinguística, and Cognitive and Metacognitive Strategies
Research Interests:
Research Interests:
Research Interests:
Business Intelligence (BI) and Data Analytics applications depend on an effective ETL (Extract, Transform and Load) process . This paper presents an approach and a Rapid Application Development (RAD) tool to increase efficiency and... more
Business Intelligence (BI) and Data Analytics applications depend on an effective ETL (Extract, Transform and Load) process . This paper presents an approach and a Rapid Application Development (RAD) tool to increase efficiency and effectiveness of ETL programs development and maintenance. Furthermore, it is also described a controlled experiment conducted in industry to carefully evaluated the efficiency and effectiveness of the tool. The results indicate that our approach can indeed be used as method aimed at improving and speed up ETL process maintenance.
Research Interests:
Research Interests:
The scenario of great competition among companies has awakened the constant need to optimize the way their internal processes are conducted. The continuous process improvement cannot be achieved in any way without strategic alignment,... more
The scenario of great competition among companies has awakened the constant need to optimize the way their internal processes are conducted. The continuous process improvement cannot be achieved in any way without strategic alignment, without digital transformation and without the analysis of the human resources responsible for carrying out the activities. The three dimensions of management mentioned above need to be synchronized for the perfect functioning of the organizational gears. This article presents a Business Transformation Methodology that integrates the business process management (BPM) with the strategic objectives, digital transformation and people management to improve the operational efficiency of the business. In addition, an in vivo experiment on the implementation of the methodology using agile project management in a food distributor company is also described.
Research Interests:
Stemming algorithms are commonly used during textual preprocessing phase in order to reduce data dimensionality. However, this reduction presents different efficacy levels depending on the domain that it’s applied to. Hence, this work is... more
Stemming algorithms are commonly used during textual preprocessing phase in order to reduce data dimensionality. However, this reduction presents different efficacy levels depending on the domain that it’s applied to. Hence, this work is an experimental analysis about dimensionality reduction by stemming a real database of judicial jurisprudence formed by four subsets of documents. With such document base, it is necessary to adopt techniques that increase the efficiency of storage and search for such information, otherwise there is a loss of both computing resources and access to justice, as stakeholders may not find the document they need to plead their rights. The results show that, depending on the algorithm and the collection, there may be a reduction of up to 52% of these terms in the documents. Furthermore, we have found a strong correlation between the reduction percentage and the quantity of unique terms in the original document. This way, RSLP algorithm was the most effecti...
Uma falha no mapeamento ou na definicao dos processos de negocio e de software pode provocar serios riscos as organizacoes, que passaram a dar atencao cada vez maior a essas questoes, principalmente no que se refere ao alinhamento do... more
Uma falha no mapeamento ou na definicao dos processos de negocio e de software pode provocar serios riscos as organizacoes, que passaram a dar atencao cada vez maior a essas questoes, principalmente no que se refere ao alinhamento do desempenho, a organizacao e a estrategia a ser seguida. Os processos, alem de ser eficientes e eficazes, devem agregar valor aos objetivos empresariais. Com isso, as organizacoes sao levadas a adotar praticas e metodologias que permitam monitorar os resultados e a relacao destes com a estrategia da organizacao. Este artigo apresenta os resultados de um survey, com CIOs da Associacao dos CIOs do estado de Sergipe, acerca da gestao dos processos de negocio, dos processos de software e da utilizacao de praticas de governanca de TIC. Como resultados, em apenas 19% dos casos, evidenciou-se uma adocao integral do processo de desenvolvimento de software com o intuito de assegurar que o software a ser desenvolvido atenda as necessidades das organizacoes. No mes...
Research Interests:
Information systems that support public sector daily activities generate large data sets. As a large proportion of the data in these data sets are text, Text Mining can play an important role in deriving potentially useful and previously... more
Information systems that support public sector daily activities generate large data sets. As a large proportion of the data in these data sets are text, Text Mining can play an important role in deriving potentially useful and previously unknown information. The overall goal of this paper is evaluate the performance and quality of three text mining classification algorithms applied to detect irregularities in public sector records. To evaluate the algorithms, a tool was designed and a case study was carried out at the Court of Accounts of Sergipe. Performance and Quality metrics were evaluated: mean execution time, accuracy, precision, coverage and F-measure. The results show that the multinomial naive bayes algorithm using inverse document frequency was the best approach to find evidences of travel reimbursement irregularities.
Research Interests:
Context: Opinions given by hotel clients in tourism social networks, the ones which can be a great source of knowledge extraction in the Big Data context, including the sustainable aspects of the hotels clients opinions. Objective:... more
Context: Opinions given by hotel clients in tourism social networks, the ones which can be a great source of knowledge extraction in the Big Data context, including the sustainable aspects of the hotels clients opinions. Objective: Evaluate performance and quality of deep learning neural networks, especially the Target-Connection LSTM (TC-LSTM) and Attention-based LSTM (AT-LSTM) algorithms, aiming to mine and classify the opinions posted on the TripAdvisor and Booking social networks, by considering sustainability aspects. Method: A controlled experiment to compare the efficiency and efficacy of the classifiers was carried out. Results: The AT-LSTM algorithm presented the best results, especially in terms of accuracy, precision, f-measure, average training time and average classification time. The first with 74,58%, the second with 95,54%, the third with 85,37%, then fourth with 7,3 s and the last one with 1,12 s. Conclusion: The AT-LSTM algorithm was expressly more effective than T...
Research Interests:
Empathy plays an important role in social interactions, for example, in effective teaching-learning processes in teacher-student relationships, and in the company-client or employee-customer relationships, retaining potential partners and... more
Empathy plays an important role in social interactions, for example, in effective teaching-learning processes in teacher-student relationships, and in the company-client or employee-customer relationships, retaining potential partners and providing them with greater satisfaction. In parallel, the Computer-Mediated Communication (CMC) support people in their interactions, especially when the interlocutors are geographically distant from one another. In CMC, there are several approaches to promote empathy in social or human- computer interactions. However, for this type of communication, a little explored mechanism to gain empathy is the use of the theory of Neurolinguistics that presents the possibility of developing a Preferred Representation System (PRS) for cognition in humans. In this context, this paper presents an experimental evaluation of the NeuroMessenger, a collaborative messenger library that uses Neurolinguistics, Psychometry and Text Mining to promote empathy among interlocutors, from the PRS identification and suggestion of textual matching. The results showed that the performance with the use of NeuroMessenger, in favor of empathy, was higher, as well as there was an evidence statistically significant of the difference between the distribution of grades in the empathy evaluation,in favor of NeuroMessenger. Despite the results are satisfactory, more research on textual matching to gain empathy is needed.
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Many researches around code clone detection rely on Open Source Software (OSS) repositories to execute their studies. These cases do not reflect the corporative code development scenario. Big Companies repositories’ are protected from the... more
Many researches around code clone detection rely on Open Source Software (OSS) repositories to execute their studies. These cases do not reflect the corporative code development scenario. Big Companies repositories’ are protected from the public’s access, so their content and behavior remain as a black box on the researchers’ viewpoint. This article presents an experiment performed on systems developed in a large private education company, to observe and compare the incidence of cloned code on proprietary software with other studies involving open source systems, using different similarity thresholds. The results indicate that the closed-source repository presents similar clone incidence as the OSS ones.
Research Interests:
Research Interests:
Aplicações de Business Intelligence (BI) efetivas dependem de um Data Warehouse (DW), um repositório histórico de dados projetado para dar suporte a processos de tomada de decisão. Sem um DW eficiente, as organizações não podem extrair,... more
Aplicações de Business Intelligence (BI) efetivas dependem de um Data Warehouse (DW), um repositório histórico de dados projetado para dar suporte a processos de tomada de decisão. Sem um DW eficiente, as organizações não podem extrair, em um tempo aceitável, os dados que viabilizam ações estratégicas, táticas e operacionais mais eficazes. Ambientes de BI possuem um processo de Engenharia de Software particular, baseado em dados, para desenvolver programas de Extração, Transformação e Carga (ETL) de informações para o DW. Este artigo apresenta um método e uma ferramenta de Desenvolvimento Rápido de Aplicações (RAD) para aumentar a eficiência do desenvolvimento de programas ETL. A avaliação experimental da abordagem foi realizada em um experimento controlado feito na indústria para analisar a efetividade da ferramenta neste tipo de ambiente. Os resultados indicaram que a nossa abordagem pode ser usada como método para acelerar e melhorar o desenvolvimento de processos ETL.
Business Intelligence (BI) relies on Data Warehouse (DW), a historical data repository designed to support the decision making process. Without an effective Data Warehouse, organizations cannot extract the data required for information... more
Business Intelligence (BI) relies on Data Warehouse (DW), a historical data repository designed to support the decision making process. Without an effective Data Warehouse, organizations cannot extract the data required for information analysis in time to enable more effective strategic, tactical, and operational insights. This paper presents an approach and a Rapid Application Development (RAD) tool to increase efficiency and effectiveness of ETL (Extract, Transform and Load) programs development. An experimental evaluation of the approach is carried out in a controlled experiment that carefully evaluated the efficiency and effectiveness of the tool in an industrial setting. The results indicate that our approach can indeed be used as method aimed at improving ETL process development.
Research Interests:
Em investigações criminais complexas, os envolvidos lidam com uma quantidade enorme e complexa de dados que necessitam de recursos computacionais especializados na extração de informações e correlações relevantes para o processo... more
Em investigações criminais complexas, os envolvidos lidam com uma quantidade enorme e complexa de dados que necessitam de recursos computacionais especializados na extração de informações e correlações relevantes para o processo investigativo. Neste cenário, é necessário que haja apoio computacional, desde a etapa de armazenamento e integração entre diferentes bases de dados, até a etapa de análise estatística e descoberta de padrões. Este artigo discute os resultados de um Survey aplicado aos principais órgãos de combate ao crime organizado, tais como as agências de Inteligência de Segurança Pública – ISP, os Laboratórios de Tecnologia de Combate à Lavagem de Dinheiro – LABLDs e os Grupos de Atuação Especial de Repressão ao Crime Organizado – GAECO. O objetivo principal foi o de conhecer o cenário atual da utilização de ferramentas de análise de dados nessas agências, projetando as necessidades de pesquisa e investimentos nesta área. Entre os resultados encontrados, observou-se que...
Research Interests:
O Galactus é um ambiente projetado, integrador, com capacidade para armazenar todo o acervo digital investigativo de órgãos ou departamentos que atuam com a atividade de Inteligência de Segurança Pública (ISP). O Ministério Público de... more
O Galactus é um ambiente projetado, integrador, com capacidade para armazenar todo o acervo digital investigativo de órgãos ou departamentos que atuam com a atividade de Inteligência de Segurança Pública (ISP). O Ministério Público de Sergipe tem utilizado este ambiente tecnológico para prospecção e descoberta de informações essenciais ao processo investigativo. Estudos de casos diários têm apresentado resultados que evidenciam a necessidade inerente ao investigador de possuir um único modal customizável de busca.
Research Interests:
Research Interests:
Contexto: A criminalidade tem sido um problema ao redor do mundo, causando danos às sociedades. Educação, pobreza, emprego e clima são alguns fatores que afetam a taxa de criminalidade, levando as autoridades a gastar, anualmente, milhões... more
Contexto: A criminalidade tem sido um problema ao redor do mundo, causando danos às sociedades. Educação, pobreza, emprego e clima são alguns fatores que afetam a taxa de criminalidade, levando as autoridades a gastar, anualmente, milhões com ações de combate à violência e planos estratégicos de prevenção e redução da criminalidade. Objetivo: Aplicar conceitos de Data Science para análise de dados governamentais relacionados a crimes no Brasil. Método: Uso de mineração de dados, especificamente regras de associação (RA), em um experimento controlado, para detecção de padrões entre os tipos de crimes, como também entre os tipos de crime e meses do ano. Resultados: No contexto das associações entre crimes, os estados com regras mais interessantes foram: Bahia, com 15 associações, São Paulo, com 12, Goiás, 11, e Paraná, com 9. Destaque para a associação “Latrocínio Roubo de Carga”, encontrada para o Estado da Bahia, a qual atingiu uma confiança de 99% (0.99). Já no âmbito das associaç...