Design and Implementation of a Neural Machine Translation Engine for Computer-Assisted Translations

This research investigates the development of a Neural Machine Translation (NMT) engine for seamless integration into Computer-Assisted Translation (CAT) software via an Application Programming Interface (API). The study conducts a comprehensive review of state-of-the-art NMT techniques and relevant Language Models (LLMs), including mT5, mBart, MarainMT, and SMaLL100. The study extracts data from Trados Studio .tmx files, preprocesses it to construct suitable datasets spanning 22 languages, and fine-tunes pre-trained LMs. The NMT engine's performance undergoes rigorous evaluation, employing a multifaceted approach, including statistical metrics such as BLEU, ROUGE, and Semantic Similarity (cosine similarity) to gauge translation accuracy. The successful integration of the NMT engine into CAT software is facilitated through the development of an API using Flask. Additionally, a user-friendly web frontend provides web-based access to the NMT engine. The findings of this research showcase a significant enhancement in translation performance through the successful integration of the NMT engine into CAT software, opening doors for practical applications in real-world translation scenarios, and empowering human translators with an efficient and powerful tool

Hierarchical Visual Content Modelling and Query based on Trees

In recent years, such vast archives of video information have become available that human annotation of content is no longer feasible; automation of video content analysis is therefore highly desirable. The recognition of semantic content in images is a problem that relies on prior knowledge and learnt information and that, to date, has only been partially solved. Salient analysis, on the other hand, is statistically based and highlights regions that are distinct from their surroundings, while also being scalable and repeatable. The arrangement of salient information into hierarchical tree structures in the spatial and temporal domains forms an important step to bridge the semantic salient gap. Salient regions are identified using region analysis, rank ordered and documented in a tree for further analysis. A structure of this kind contains all the information in the original video and forms an intermediary between video processing and video understanding, transforming video analysis to a syntactic database analysis problem. This contribution demonstrates the formulation of spatio-temporal salient trees the syntax to index them, and provides an interface for higher level cognition in machine vision

Using Business Process Management to improve organisational efficiency: Evidence from a Lithuanian company

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementThe project at hand focused on improving the organisational efficiency of the company Cleaners by optimising a purposefully selected process in light of the specific context at play. The company's legacy process architecture was used as a foundation of the identification phase, which resulted in the selection of the "Equipment repair" process as the subject of the project. After the context of the chosen process was determined, the identification phase followed. A series of semi-structured interviews with process participants allowed to achieve the "as-is" model, which was both qualitatively and quantitatively analysed to attain a number of recommendations for the "to-be" process. These propositions were to employ more technicians (and invest more into their professional development), remove the project manager from the process (although provide visibility of its progress), establish business rules (that would diminish dependency on middle to high-level managers), partially automate certain activities, employ a DBMS, and, finally, enable cleaners to fix equipment themselves. All of the aforementioned recommendations were then incorporated into the "to-be" process model, which represents an optimal configuration of the "Equipment repair" process

Who Blames Female Victims of Revenge Pornography?

Revenge pornography refers to any kind of uploading or publishing private photos or videos of someone without their consent. The public can often blame female victims of revenge pornography for engaging in the risky behaviour of taking nude pictures or videos in the first place. Certain individual and socio-demographic characteristics of the public can lead to victim-blaming. We wanted to see if characteristics relevant in the context of blaming rape victims for their victimisation, such as ambivalent sexism, moral foundations, conservatism, age and gender, contribute to blaming victims of revenge pornography. Convenient sample consisted of N = 364 participants (73.3% women), with an average age of 38.07 (SD = 13.74), and slightly more socio-liberal orientation, according to self-ssessment (a broad social attitudes 7-point scale ranging from 1-liberal to 7-conservative (M = 2.97, SD = 1.49)). In an online survey, participants were presented with a vignette describing a bogus case of a woman whose pictures a man posted on the internet. The participant's task was to assess who should take responsibility for this event on a 7-point scale, ranging from 1, meaning the woman, through 4, meaning both the woman and the man equally, to 7, meaning the man. The distribution of answers was trimodal (on word anchors) and negatively asymmetric because 52.2% of participants said that the man should take responsibility. After attributing responsibility, participants filled out the Ambivalent sexism inventory with 22 items (α = .91) and the Moral foundations questionnaire with 30 items (all five subscales, α = .66-.81). Regression model with sociodemographics, together with ambivalent sexism and moral progressivity, explained 19.8% of the variance in victim-blaming (F(5, 354) = 17.22, p < .001). Ambivalent sexism (β = -0.27, p < .001) contributed the most, followed by moral progressivity (β = 0.17, p = .01), while gender, age, and conservatism were not significant predictors. Content analysis of ambivalent sexist attitudes and less progressive moral foundations can help us create a substitute for the victim-blaming narrative around victims of revenge pornography which would still fit the mindset of current victim-blamers (e. g. “women take and share their private photos or videos to special men in their life to please them”). Besides the practical application, the study's findings contribute to the ongoing debate over the theoretical soundness of Moral foundations theory because holding less progressive moral foundations, which are exclusively proposed by this theory, leads to an apology for violence

Outcome Bias in Judging Revenge Pornography Toward Women

Revenge pornography refers to any kind of uploading or publishing private photos or videos of someone without their consent. At the beginning of 2021, the public in the Balkans region found out about private groups on social networks, counting around 30,000 participants, mostly men, involved in revenge pornography toward women. Laws in Serbia do not explicitly prohibit revenge pornography. In this study, we wanted to examine whether legal consequences for the perpetrator would affect the negative public opinion of revenge pornography acts. The sample consisted of 509 participants (70% women), with an average age of 36.5 (SD = 13.2), and slightly more liberal according to self-assessment on a broad social attitudes scale ranging from 1 - liberal to 7 - conservative (M = 3.1, SD = 1.5). Firstly, all participants read a vignette describing a bogus case of a woman whose pictures a man posted online. Further, half of them read the second part about the legal consequences the perpetrator has suffered for his act - imprisonment, while the other half of participants read that he was not punished due to revenge pornography not being officially prohibited in our country. All participants provided judgment of the act itself on a 7-point scale ranging from 1 - very bad to 7 - very good, as well as their opinion on who is to blame for this act, also on a 7-point scale: 1 - the woman, 4 - both equally, 7 - the man. These judgements were provided twice, once after reading the first part of the vignette and after reading the second part. We expected that change in judgments would be led by outcome bias. Actually, in both of the judgment measurements, 90% of participants marked the act of the man as very bad. Due to the ceiling effect, we did not proceed with the planned analysis of change. The distribution of answers on the responsibility scale was trimodal (on word anchors) and negatively asymmetric because 52% of participants said that the man should take responsibility. We did not test if the change in victim-blaming is moderated by gender because of the insufficient number of men per experimental group. Whatsoever, a Wilcoxson signed-rank test (W = 50.50, p = .007) showed that all participants who read about the legal consequences blamed the perpetrator slightly more afterwards, which did not happen in the other group (W = 47.00, p = .054). Legal consequences can reduce victim-blaming and consequently form a social norm by which revenge pornography toward women is perceived as deviant behaviour

Struktura socijalnih stavova u adolescenciji i nadolazećem odraslom dobu

Analizom reči sa sufiksom “-izam” u srpskom rečniku utvrđeno je šest bazičnih socijalnih stavova prema kojima se odrasli pripadnici srpskog govornog područja razlikuju u evaluaciji društvenih prilika: podrška “Tradicionalnim i religioznim izvorima autoriteta”, zastupanje “Ličnih interesa”, “Spiritualizam”, “Humanizam”, “Egalitarizam” i "Nacionalizam”. Eksploratornim istraživanjem proverili smo da li je struktura socijalnih stavova izmerena upitnikom sa 36 užih “-izama” održiva u adolescenciji i nadolazećem odraslom dobu. Odabran je dizajn poprečnog preseka na četiri uzrasne grupe: prvi (N=212) i treći (N=222) razred srednje škole, prva godina studija (N=197) i kraj studija (N=196). Kako bismo iskontrolisali ispitanike kroz tri mlađe uzrasne grupe, homogenizovali smo uzorak gimnazijalcima čime je generalizabilnost nalaza na celu populaciju adolescenata i nadolazećih odraslih u Srbiji ograničena. Multigrupna analiza Eksploratornim modeliranjem strukturalnim jednačinama (ESEM) pokazala je metričku invarijantnost (RMSEA=0.052; SRMR=0.068; χ²(2256)= 3533.828, p&lt;0.001; χ²/df=1.566; CFI=0.856). Rezultati ukazuju ne samo da mladi imaju istih šest stabilnih dispozicija kojima evaluiraju društvene prilike kao i odrasli već i da svaka od šest stavskih dispozicija ima isto značenje kroz sve uzraste. Istovetnost značenja bazičnih stavova koje ispoljavaju mladi i odrasli pomaže nam da razumemo motivaciju za sudelovanje mladih u društvenim procesima ili njihovo iskazivanje stavova i uverenja o aktuelnim društvenim prilikama. S obirom na to da se adolescencija smatra formativnim periodom za socijalne stavove, nalaz koji pokazuje odsustvo uzrasnih razlika u formativnom periodu je iznenađujuć. S druge strane, nalaz o istovetnosti značenja socijalnih stavova koje meri upitnik leksičkih socijalnih stavova kod mladih i kod odraslih je pragmatičan - potvrđuje da se upitnik može koristiti prilikom odgovaranja na različita istraživačka pitanja razvojne psihologije

Data-driven conceptual modeling: how some knowledge drivers for the enterprise might be mined from enterprise data

As organizations perform their business, they analyze, design and manage a variety of processes represented in models with different scopes and scale of complexity. Specifying these processes requires a certain level of modeling competence. However, this condition does not seem to be balanced with adequate capability of the person(s) who are responsible for the task of defining and modeling an organization or enterprise operation. On the other hand, an enterprise typically collects various records of all events occur during the operation of their processes. Records, such as the start and end of the tasks in a process instance, state transitions of objects impacted by the process execution, the message exchange during the process execution, etc., are maintained in enterprise repositories as various logs, such as event logs, process logs, effect logs, message logs, etc. Furthermore, the growth rate in the volume of these data generated by enterprise process execution has increased manyfold in just a few years. On top of these, models often considered as the dashboard view of an enterprise. Models represents an abstraction of the underlying reality of an enterprise. Models also served as the knowledge driver through which an enterprise can be managed. Data-driven extraction offers the capability to mine these knowledge drivers from enterprise data and leverage the mined models to establish the set of enterprise data that conforms with the desired behaviour. This thesis aimed to generate models or knowledge drivers from enterprise data to enable some type of dashboard view of enterprise to provide support for analysts. The rationale for this has been started as the requirement to improve an existing process or to create a new process. It was also mentioned models can also serve as a collection of effectors through which an organization or an enterprise can be managed. The enterprise data refer to above has been identified as process logs, effect logs, message logs, and invocation logs. The approach in this thesis is to mine these logs to generate process, requirement, and enterprise architecture models, and how goals get fulfilled based on collected operational data. The above a research question has been formulated as whether it is possible to derive the knowledge drivers from the enterprise data, which represent the running operation of the enterprise, or in other words, is it possible to use the available data in the enterprise repository to generate the knowledge drivers? . In Chapter 2, review of literature that can provide the necessary background knowledge to explore the above research question has been presented. Chapter 3 presents how process semantics can be mined. Chapter 4 suggest a way to extract a requirements model. The Chapter 5 presents a way to discover the underlying enterprise architecture and Chapter 6 presents a way to mine how goals get orchestrated. Overall finding have been discussed in Chapter 7 to derive some conclusions

Task switching ability in mild cognitive impairment

There is growing evidence of executive function deficits in mild cognitive impairment (MCI) and task switching ability has been shown to predict MCI transition to Alzheimer's disease. We tested task switching ability using a cued task switching paradigm in 27 MCI patients. Sixteen patients could perfume the task (MCI-able) and 11 could not (MCI-unable). Neuropsychological, electrophysiological, neuroanatomical, genetic, demographic, health-related data are presented for the MCI sub-groups and normal controls. The most significant finding of this study is that task-switching ability can be a powerful tool in characterizing this heterogeneous population. We found that most MCI patients exhibit some form of task-switching deficits, but to vastly different degrees. On the one hand there are individuals closer to the normal aging end of the cognitive spectrum; these individuals may present with memory deficits relative to their normal age peers but can compensate these with quasi-intact executive functions and have a high probability of remaining dementia free as long as their executive functions remain adequate. On the other side of the spectrum, there are individuals who perfume poorly on executive tasks as well as having significant episodic memory deficits. These individuals appear to have a high probability of developing AD or dying within four years. ii