The Influence of Digital Marketing Competence and Financial Statements on Performance (Case Study on the Development Business of the West Java Chamber of Commerce and Industry in Bandung)

The study aims to shed light on the lean management method and its role in reducing waste in its various forms and to show the extent of application of this method in industrial companies. ) in reducing supply chain risks before, during and after their occurrence and demonstrating the role of agile management in the sustainability of supply chains. The researcher relied on the descriptive analytical approach. In the theoretical section of the research, the concept of lean management, its principles and objectives were studied, the concept of supply chain and the concept of supply chain risks and types of these risks were studied. In the practical section, a questionnaire was designed that included a set of statements related to the topic of research and appropriate statistical methods were used depending on The program (SPSS23) in analyzing data and testing hypotheses, the research community is represented by the administrative cadres in the industrial companies in the industrial city in Hasya, where an intentional sample of the administrative cadres in the industrial companies in Hasya was selected, where the size of the research sample was (64) individuals The study reached a (positive) significant relationship between lean management dimensions (organizing work site, continuous improvement, standard work, multi -functional workers, six Sigma) and reducing supply chain risks before it occurs. And a (positive) significant relationship between lean management dimensions (organizing work site, continuous improvement, standard work, multi -functional workers, six soms) and between reducing supply chain risks during its occurrence. And a (positive) significant relationship between lean management dimensions (organizing work site, continuous improvement, standard work, multi -functional workers, six Sigma) and between reducing supply chain risks after its occurrence.

EDTC: A Corpus for Discourse-Level Topic Chain Parsing

Discourse analysis has long been known to be fundamental in natural language processing. In this research, we present our insight on discourse-level topic chain (DTC) parsing which aims at discovering new topics and investigating how these topics evolve over time within an article. To address the lack of data, we contribute a new discourse corpus with DTC-style dependency graphs annotated upon news articles. In particular, we ensure the high reliability of the corpus by utilizing a two-step annotation strategy to build the data and filtering out the annotations with low confidence scores. Based on the annotated corpus, we introduce a simple yet robust system for automatic discourse-level topic chain parsing.

Salience-Aware Event Chain Modeling for Narrative Understanding

Storytelling, whether via fables, news reports, documentaries, or memoirs, can be thought of as the communication of interesting and related events that, taken together, form a concrete process. It is desirable to extract the event chains that represent such processes. However, this extraction remains a challenging problem. We posit that this is due to the nature of the texts from which chains are discovered. Natural language text interleaves a narrative of concrete, salient events with background information, contextualization, opinion, and other elements that are important for a variety of necessary discourse and pragmatics acts but are not part of the principal chain of events being communicated. We introduce methods for extracting this principal chain from natural language text, by filtering away non-salient events and supportive sentences. We demonstrate the effectiveness of our methods at isolating critical event chains by comparing their effect on downstream tasks. We show that by pre-training large language models on our extracted chains, we obtain improvements in two tasks that benefit from a clear understanding of event chains: narrative prediction and event-based temporal question answering. The demonstrated improvements and ablative studies confirm that our extraction method isolates critical event chains.

Multilingual Neural Machine Translation: Can Linguistic Hierarchies Help?

Multilingual Neural Machine Translation (MNMT) trains a single NMT model that supports translation between multiple languages, rather than training separate models for different languages. Learning a single model can enhance the low-resource translation by leveraging data from multiple languages. However, the performance of an MNMT model is highly dependent on the type of languages used in training, as transferring knowledge from a diverse set of languages degrades the translation performance due to negative transfer. In this paper, we propose a Hierarchical Knowledge Distillation (HKD) approach for MNMT which capitalises on language groups generated according to typological features and phylogeny of languages to overcome the issue of negative transfer. HKD generates a set of multilingual teacher-assistant models via a selective knowledge distillation mechanism based on the language groups, and then distills the ultimate multilingual model from those assistants in an adaptive way. Experimental results derived from the TED dataset with 53 languages demonstrate the effectiveness of our approach in avoiding the negative transfer effect in MNMT, leading to an improved translation performance (about 1 BLEU score in average) compared to strong baselines.

Audiovisual Translation through NMT and Subtitling in the Netflix Series `Cable Girls'

In recent years, the emergence of streaming platforms such as Netflix, HBO or Amazon Prime Video has reshaped the field of entertainment, which increasingly relies on subtitling, dubbing or voice-over modes. However, little is known about audiovisual translation when dealing with Neural Machine Translation (NMT) engines. This work-in-progress paper seeks to examine the English subtitles of the first episode of the popular Spanish Netflix series Cable Girls and the translated version generated by Google Translate and DeepL. Such analysis will help us determine whether there are significant linguistic differences that could lead to miscomprehension or cultural shocks. To this end, the corpus compiled consists of the Spanish script, the English subtitles available in Netflix and the translated version of the script. For the analysis of the data, errors have been classified following the DQF/MQM Error typology and have been evaluated with the automatic BLEU metric. Results show that NMT engines offer good-quality translations, which in turn may benefit translators working with audiovisual entertainment resources.

Encryption using a private vectors generate triangular matrices from the top (or bottom)

This research gives a new type of encryption, using vectors give me a private encryption key, which generates a triangular matrices from the top (bottom), and check conditions matrix Hill. These matrices resulting from private vectors constitute a relatively preliminary numbers of size n = 256 The encryption process produces by multiplying the original matrix encryption keys.

Prevalence of hepatitis D antibodies in chronic hepatitis B patient

Several studies and reports have indicated the prevalence of hepatitis D virus infection in many parts of the world at different rates , Ranging from areas of epidemiological and areas with a low prevalence of it. Till now there is no study in Syria shows us the prevalence of viruse Delta in chronic hepatitis B patients . The aim of our study was to determine the current prevalence of hepatitis D in chronic hepatitis B patients . And to take appropriate measures in dealing with these patients due to the increased risk of liver disease in the event of injury by it . 77 patients with chronic hepatitis B certainly proved with PCR analysis 25 women and 52 men visiting the center of hepatitis in Latakia were tested for antibody to hepatitis D virus (anti-HDV) by ELISA test . The results indicate a positive antibody in three patients (women and 2 men) and the prevalence was 3.8% , which point to a moderate prevalence of hepatitis D comparing with neighboring countries.

Isolation And Cloning Of AapJ Gene From Brucella melitensis

Economic losses resulting from the impact of brucellosis on animals have increased, which is reflected in turn on humans. Brucella is pathogenic bacteria shared by humans and pet animals. They still pose a significant risk that threatens health and economics in Syria. Many efforts have focused to prevent the spread of brucellosis disease, by resorting to the use of vaccines prepared from Brucella strains, where now the target is preparation of vaccine components proteins of Brucella can be used as a vaccine or an improved traditional vaccine.