How Can e-Grocers Use Artificial Intelligence Based on Technology Innovation to Improve Supply Chain Management?

[EN] The digital transformation among grocery sales is in full swing. However, some retailers are struggling to adapt to technological innovation in the grocery industry to achieve digital excellence. The purpose of this article is to analyse artificial intelligence systems applied in e-commerce that could be implemented in online grocery sales. Unlike other online businesses, grocery sales face logistical challenges that differentiate them, such as fresh product conservation and tight delivery times. Through a literature review, this study aims to provide researchers and practitioners with a starting point for the selection of technological innovation to solve e-grocery problems.Vazquez-Noguerol, M.; Prado-Prado, C.; Liu, S.; Poler, R. (2021). How Can e-Grocers Use Artificial Intelligence Based on Technology Innovation to Improve Supply Chain Management?. IFIP Advances in Information and Communication Technology. 626:142-150. https://doi.org/10.1007/978-3-030-78288-7_1414215062

ANALYZING THE POSSIBILITY OF DELAYS OF SPP PAYMENTS WITH C4.5 ALGORITHM (CASE STUDY OF POLITEKNIK TEDC BANDUNG)

Payment of tuition as one of the sources of funds, plays an important role in the sustainability of the operations of higher education. The problem that arises is that students are not often late to make payments in a timely manner. One of the factors causing the many cases of late payment of tuition fees due to lack of policy and decisive action on the part of the campus when students are late in making payments, besides the factors of parents and students also have an influence on the delay. The purpose of this study is to classify students who are late and timely in making SPP payments using the C4.5 algorithm. From the total sample used then divided into 4 partitions, partition 1 for 90% training data and 10% testing data, partition 2 for 80% training data and 20% testing data, and partition 3 for 70% training data and 30% testing data, and partition 4 for 60% training data and 40% testing data. The classification results of the C4.5 algorithm are evaluated and validated with a cross-validation and confusion matrix to determine the accuracy of the C4.5 algorithm in predicting late SPP payments. Based on the comparison of the results of evaluations and validations conducted, it shows that data partition 2 has a better level of accuracy than the other partitions, which is 75%

Social mining for sustainable cities: thematic study of gender-based violence coverage in news articles and domestic violence in relation to COVID-19

We argue that social computing and its diverse applications can contribute to the attainment of sustainable development goals (SDGs)—specifically to the SDGs concerning gender equality and empowerment of all women and girls, and to make cities and human settlements inclusive. To achieve the above goals for the sustainable growth of societies, it is crucial to study gender-based violence (GBV) in a smart city context, which is a common component of violence across socio-economic groups globally. This paper analyzes the nature of news articles reported in English newspapers of Pakistan, India, and the UK—accumulating 12,693 gender-based violence-related news articles. For the qualitative textual analysis, we employ Latent Dirichlet allocation for topic modeling and propose a Doc2Vec based word-embeddings model to classify gender-based violence-related content, called GBV2Vec. Further, by leveraging GBV2Vec, we also build an online tool that analyzes the sensitivity of Gender-based violence-related content from the textual data. We run a case study on GBV concerning COVID-19 by feeding the data collected through Google News API. Finally, we show different news reporting trends and the nature of the gender-based violence committed during the testing times of COVID-19. The approach and the toolkit that this paper proposes will be of great value to decision-makers and human rights activists, given the prompt and coordinated performance against gender-based violence in smart city context—and can contribute to the achievement of SDGs for sustainable growth of human societies

Intelligent classification algorithms in enhancing the performance of support vector machine

Performing feature subset and tuning support vector machine (SVM) parameter processes in parallel with the aim to increase the classification accuracy is the current research direction in SVM. Common methods associated in tuning SVM parameters will discretize the continuous value of these parameters which will result in low classification performance. This paper presents two intelligent algorithms that hybridized between ant colony optimization (ACO) and SVM for tuning SVM parameters and selecting feature subset without having to discretize the continuous values. This can be achieved by simultaneously executing the selection of feature subset and tuning SVM parameters simultaneously. The algorithms are called ACOMVSVM and IACOMV-SVM. The difference between the algorithms is the size of the solution archive. The size of the archive in ACOMV is fixed while in IACOMV, the size of solution archive increases as the optimization procedure progress. Eight benchmark datasets from UCI were used in the experiments to validate the performance of the proposed algorithms. Experimental results obtained from the proposed algorithms are better when compared with other approaches in terms of classification accuracy. The average classification accuracies for the proposed ACOMV–SVM and IACOMV-SVM algorithms are 97.28 and 97.91 respectively. The work in this paper also contributes to a new direction for ACO that can deal with mixed variable ACO

O impacto das características da função e das funcionalidades das tecnologias no desempenho profissional: o papel mediador do modelo Task-Technology Fit

O mundo em que vivemos tem vindo a sofrer mudanças e transformações de uma forma rápida, sendo cada vez mais notável o incremento digital na sociedade. Estes progressos têm assumido uma grande importância e presença nas organizações, porque têm alterado a forma como as funções são executadas. Quando as tarefas são suportadas pelas tecnologias para a sua realização conduzem à eficiência no decurso do cumprimento das funções. Como consequências positivas, o colaborador atinge um bom nível de desempenho e mostra o seu potencial nomeadamente, os conhecimentos e habilidades que detém. A presente investigação insere-se nesta temática e tem como objetivo analisar o impacto das características das tarefas e das funcionalidades das tecnologias no desempenho profissional e perceber em que medida esta relação é mediada pelo modelo Task-Technology Fit (TTF). Participaram no estudo 353 indivíduos cujas idades variam entre os 18 e os 65 anos, sendo que mais de um terço pertence à Geração X. Os dados foram recolhidos através do Questionário das características das tarefas, do Questionário das funcionalidades das tecnologias, do Questionário Task-Technology Fit e do Questionário do desempenho profissional. Os resultados obtidos revelaram que a perceção dos participantes, relativamente às funcionalidades das tecnologias diferem em função da geração a que os mesmos pertencem. Apurou-se, ainda, que as características das tarefas e as funcionalidades das tecnologias têm um impacto positivo no desempenho profissional e que esta relação é mediada pelo modelo TTF

O impacto da inteligência artificial no negócio eletrónico

Pela importância que a Inteligência Artificial exibe na atualidade, revela-se de grande interesse verificar até que ponto ela está a transformar o Negócio Eletrónico. Para esse efeito, delineou-se uma revisão sistemática com o objetivo de avaliar os impactos da proliferação destes instrumentos. A investigação empreendida pretendeu identificar artigos científicos que, através de pesquisas realizadas a Fontes de Dados Eletrónicas, pudessem responder às questões de investigação implementadas: a) que tipo de soluções, baseadas na Inteligência Artificial (IA), têm sido usadas para melhorar o Negócio Eletrónico (NE); b) em que domínios do NE a IA foi aplicada; c) qual a taxa de sucesso ou fracasso do projeto. Simultaneamente, tiveram de respeitar critérios de seleção, nomeadamente, estar escritos em inglês, encontrarem-se no intervalo temporal 2015/2021 e tratar-se de estudos empíricos, suportados em dados reais. Após uma avaliação de qualidade final, procedeu-se à extração dos dados pertinentes para a investigação, para formulários criados em MS Excel. Estes dados estiveram na base da análise quantitativa e qualitativa que evidenciaram as descobertas feitas e sobre os quais se procedeu, posteriormente, à sua discussão. A dissertação termina com as conclusão e discussão de trabalhos futuros.Due to the importance that Artificial Intelligence exhibits today, it is of great interest to see to what extent it is transforming the Electronic Business. To this end, a systematic review was designed to evaluate the impacts of the proliferation of these instruments. The research aimed to identify scientific articles that, through research carried out on Electronic Data Sources, could answer the research questions implemented: a) what kind of solutions, based on Artificial Intelligence, have been used to improve the Electronic Business; b) in which areas of the Electronic Business Artificial Intelligence has been applied; c) what the success rate or failure of the project is. At the same time, they must comply with selection criteria, to be written in English, to be found in the 2015/2021-time interval and to be empirical studies supported by actual data. After a final quality evaluation, the relevant data for the investigation were extracted for forms created in MS Excel. These data were the basis of the quantitative and qualitative analysis that evidenced the findings found and on which they were subsequently discussed. The dissertation ends with the conclusion and discussion of future works