Reviewerly/exHarmony huggingface dataset:
Tackling algorithmic collusion: the scope of the Indian Competition Act

The debate about algorithmic collusion has gained substantial momentum leading to divergent views amongst economists. Although some have expressed serious concerns over the menace of algorithmic collusion and its adverse impact on the competition, others have disregarded it as an unlikely threat. The common scepticism that emanates in any discourse concerning the regulation of the unique forms of algorithmic collusion is the inadequacy of the anti-trust legal framework to effectively address issues of detection, investigation and evidence collection that are incumbent in the process of proving such collusion. Much of these apprehensions are attributable to the inconsistencies in the Indian jurisprudence concerning the elements of ‘hub-and-spoke’, ‘tacit collusion’ and the acceptable ‘plus factors’ required to establish the same. Furthermore, the restrictive approach adopted by the anti-trust authorities in pronouncing judicial decisions impedes the scope of the 2002 Competition Act to address the algorithm problem in its present form. This chapter examines the rise of algorithmic collusion and explains how algorithms can destroy competition under the guise of maintaining competitive balance. It further expounds in how traditional notions of tacit collusion and hub-and-spoke should be reconstrued in the context of digital markets to bring algorithmic collusion within the sweep of Section 3 of The Indian Competition Act. It further offers an array of reforms and recommendations to adapt the Competition Law and to better equip the antitrust authorities to suit the changing needs of the digital market.
Real-time Pose Estimation in Mobile with Dense Upsampling Convolution

Human pose estimation (HPE) has been gradually applied to our daily life. It’s significant to design a simple yet effective model structure for real-time HPE. Several backbones are available for pose estimation, but many of them are imprecise, complex, and mislocalized when it comes to reconstruction. In order to narrow the gaps, several recent studies have demonstrated that deconvolution reconstruction is highly effective in achieving high levels of accuracy. Using the current popular backbones, we re-analyze and reconstruct the models. The efficiency and accuracy are state-of-the-art. Additionally, we release a new dataset that represents real-world data related to yoga. As a result of the development of our framework, we are able to achieve improvements in our released Yoga dataset named SAILPOSE-YOGA as well as other existing benchmarks for the estimation of single poses. The dataset will be released on https://github.com/carolchenyx/SAILPOSE-YOGA.git
Forecasting Credit Card Defaults Using Light Gradient Boosting Machine with Dart Algorithm

With the rapid development of financial services and technologies, credit cards have been increasingly used for personal daily consumption and small loans. However, bad debts caused by credit card defaults remarkably affect the healthy development of financial markets. Therefore, forecasting potential credit card defaults is of great significance with respect to financial stability and economic order. For this purpose, we propose a machine learning method based on Light Gradient Boosting Machine to detect credit card defaults in this paper. DART algorithm is utilized in our model instead of the traditional gradient boosting tree. The model is trained and evaluated using the dataset provided by American Express in the Kaggle competition American Express - Default Prediction. Based on feature analysis and engineering, raw data with 190 descriptors are transformed into data with 2358 descriptors, and are used to train 3 LightGBM models with different hyper-parameters. By applying the model ensemble and pseudo-label technique, the competition metric of our method reaches 0.80029/0.80767 on the public/private test set. This score ranks 106/4874 (top 2.2%), and can get a silver medal in the Kaggle competition.
Annotation of person marking constructions in the Corpus of Hungarian Lyrical Poetry

This paper presents the annotation scheme for the manual annotation of the Corpus of Hungarian Lyrical Poetry. The corpus will consist of 400-600 annotated texts, grouped into four sub-corpora: 20th century lyrical texts from the canon of Hungarian public education, contemporary lyrical texts, slam poetry texts, and song lyrics. The manual annotation is based on automatically generated and manually checked annotations of lemmas, parts of speech and morphosyntactic features. The manual annotation of syntactic properties proposed in the annotation scheme follows a dependency analysis approach and allows us to obtain quantitative data on person marking constructions in Hungarian lyrical texts. Besides the annotation of verb-dependent relations, the paper also presents the annotation of specific phenomena such as auxiliary verbs, vocatives, elliptical structures, and nominal predicates. The annotation scheme was tested using a test corpus of 16 texts. We also provide some examples of the types of quantitative data that can be extracted from the annotated corpus.
Profile of Nursing professionals during the new Coronavirus Pandemic in a southwest Pará municipality

The COVID-19 pandemic has highlighted the critical role of healthcare professionals, who are now known as “frontline professionals”, who provide direct or indirect support to suspected or confirmed SARS-CoV-2 patients. Therefore, this research aimed to identify the nursing professionals profile who work in Basic Health Units and in the Municipal Hospital during the pandemic in the municipality of Itaituba/Pará. This descriptive and exploratory study used a quantitative approach and included 109 professionals, comprising 49 nurses and 60 nursing technicians. The age ranged from 20 to 62 years old, with an average of 36.92 years old. The majority of participants were female (82.6%), identified as mixed-race (85.3%), and were single (44%). The most common level of education was specialization (39.4%), followed by complete high school (26.7%). Regarding monthly income, 33.9% earn up to two minimum wages, while 24.9% earn up to one minimum wage. Approximately 42.2% had a history of illness, with rhinitis being the most prevalent, followed by obesity and hypertension. Anxiety treatment was mentioned by 10.1%, and depression by 3.7% of professionals. Most part do not engage in physical activity (55%), are non-smokers (98.2%), and none are drug users. As for religion, most participants reported having a religious affiliation (88.1%), with Catholicism being the most common, followed by Evangelism. Understanding the profile of healthcare professionals working in the fight against the pandemic is essential to develop health promotion interventions to support them.
Machine Learning-Based Intelligent Video Surveillance in Smart City Framework

The proposed method of using Machine Learning in Motion Detection and Pedestrian Tracking-assisted Intelligent Video Surveillance Systems (ML-IVSS) can be seen as an application of intelligent fusion techniques. ML-IVSS combines the power of motion detection, pedestrian tracking, and machine learning to create a more accurate and efficient surveillance system for smart cities. By fusing these techniques, ML-IVSS can effectively detect unusual behaviors such as trespassing, interruption, crime, or fall-down, and provide accurate depth data from surveillance footage to protect residents. Intelligent fusion techniques can help improve the accuracy and effectiveness of surveillance systems in smart cities, making them safer and more secure for residents. Combination channel models are used at first, and an object area with prominent features is selected for surveillance. Scaled modification and extraction of features are carried out on the presumed object's region. Identifying the low-level characteristic is the first step in incorporating it into neural architectures for deep feature learning. A smart CCTV data set is used to evaluate the proposed method's performance. According to the numerical analysis, the proposed ML-IVSS model outperforms other traditional approaches in terms of abnormal behaviour detection (98.8%), prediction (97.4%), accuracy (96.9%), F1-score (97.1%), precision (95.6%), and recall (96.2%).
Visual Room Rearrangement

There has been a significant recent progress in the field of Embodied AI with researchers developing models and algorithms enabling embodied agents to navigate and interact within completely unseen environments. In this paper, we propose a new dataset and baseline models for the task of Rearrangement. We particularly focus on the task of Room Rearrangement: an agent begins by exploring a room and recording objects' initial configurations. We then remove the agent and change the poses and states (e.g., open/closed) of some objects in the room. The agent must restore the initial configurations of all objects in the room. Our dataset, named RoomR, includes 6,000 distinct rearrangement settings involving 72 different object types in 120 scenes. Our experiments show that solving this challenging interactive task that involves navigation and object interaction is beyond the capabilities of the current state-of-the-art techniques for embodied tasks and we are still very far from achieving perfect performance on these types of tasks. The code and the dataset are available at: https://ai2thor.allenai.org/rearrangement
Co-Creation in Secure Software Development: Applied Ethnography and the Interface of Software and Development

Long-term ethnographic research conducted at a software company examined how security concerns and practices became part of software development. Participant observation over a two-year period was done by researchers with cybersecurity backgrounds and training in both computer science and qualitative research, with ongoing analysis done by a larger interdisciplinary team. In situ researchers joined as software engineers and participated in daily work activities while observing development practices and analyzing software (in)security. The first year of research found that improving security during software development can be helped by a co-creation model, whereby security experts work directly with software developers to provide security tools applicable to the specific software within the workflow. Researchers-as-developers fostered conversations, concerns, and considerations of how to implement security within the process of development. The second year used a situated learning approach to understand the interface between software development, security, and the development team. Through an interactive learning process, software engineers gathered knowledge and applied it, helping to foster greater concerns for security as part of the overall “culture” of development within the company. This locally situated co-creation approach has resonances with participatory approaches in business anthropology and implications for how to promote the co-creation of knowledge and expertise more broadly.
Developmental Challenges: Capture the Flag and the Professionalization of Cybersecurity

Over the past two decades, Capture the Flag (CTF) style competitions have grown expansively from their origins at early hacker conferences into a persistent feature of the cybersecurity workforce worldwide (Gondree et al., 2016). Today CTFs operate as a gateway into the workforce, operating as a hands-on educational experience, recruitment mechanism for industry and government, and as a marker of legitimacy within the cybersecurity/hacker community. Individual CTF challenges (ideally) interweave often complex software-based puzzles that map contemporary cybersecurity skill sets with hacker and cybersecurity subcultural touchstones, conferring status upon both players who successfully complete the challenges and the developers themselves. Drawing on a genealogy of DEFCON CTF competitions, this paper traces the “growing pains” of cybersecurity as a professional field. Reading these challenges as engines of hacker culture, this analysis will examine the contested cultural values embedded within CTF challenges over time, providing insight into the intertwined and co-constituted elements of hacker culture and cybersecurity skill sets.
Volgordevariatie in groepen met receptief krijgen + voltooid deelwoord in de Nederlands Nederlandse krantentaal1

This article presents the results from a corpus-based investigation of the word order variation observed in verb clusters with ‘receptive’ or ‘semipassive’ krijgen ‘to get’ + a past participle, i.e. between the order in dat hij het boek overhandigd kreeg and the one in dat hij het boek kreeg overhandigd ‘that he was handed (literally: got handed) the book’. In contrast to the same word order variation in clusters with the much more frequent (and much older) auxiliaries hebben ‘to have’, zijn ‘to be’ and worden ‘to be/ become’, which has been the subject of numerous existing studies, including multifactorial corpus-based work by De Sutter (2005, 2007, etc.) and Bloem, Versloot &amp; Weerman (2014, 2017), the variation in krijgen-clusters has never been investigated before, barring a preliminary study by Colleman &amp; Rens (2016). A mixed-effects logistic regression analysis of data culled from a diachronic corpus of Dutch newspaper texts shows (i) that the variation in krijgen-clusters, though it is fairly new, is driven by largely the same language-internal factors as the variation in clusters with hebben etc., and (ii) that, in the course of the 20th century, there has been a significant increase in the relative frequency of the ‘auxiliarised’ krijgen + participle order.
An Efficient Privacy - Aware Authentication Framework for Mobile Cloud Computing

The approach of distributed computing, information proprietors are inspired to re-appropriate their intricate information the board frameworks from neighbourhood locales to business public cloud for extraordinary adaptability and financial investment funds. Yet, for safeguarding information security, delicate information must be scrambled prior to re-appropriating, which obsoletes customary information use in view of plaintext catchphrase search. In this way, empowering an encoded cloud information search administration is of fundamental significance. Taking into account the enormous number of information clients and reports in cloud, it is pivotal for the pursuit administration to permit multi-watchword question and give result similitude positioning to meet the compelling information recovery need. Related works on accessible encryption centre around single catchphrase search or Boolean watchword search, and seldom separate the indexed lists. In this paper, interestingly, we characterize and tackle the difficult issue of protection safeguarding multi-watchword positioned metaphysics catchphrase planning and search over encoded cloud information (EARM), and lay out a bunch of severe protection prerequisites for such a solid cloud information use framework to turn into a reality. Content-based distribute/buy in gives an inexactly coupled and expressive type of correspondence for enormous scope circulated frameworks. Secrecy is difficult for distribute/buy in middleware conveyed over various regulatory areas. This component that lessens the expense of encoded coordinating, as a profiteering administrator utilizing Blossom channels and straightforward randomization procedures. Propose regulation obscurity procedures and give a thorough security examination of the data spilled by Blossom channels for this situation. Among different multi-watchword semantics, we pick the effective guideline of "Improved Affiliation Rule Mining coordinate coordinating", i.e., whatever number matches as could reasonably be expected, to catch the closeness between search inquiry and information records, and further use "inward item likeness" to formalize such standard for comparability estimation quantitatively. We initially propose an essential EARM conspire utilizing secure inward item calculation, and afterward fundamentally further develop it to meet different protection prerequisites in two degrees of danger models.
Reading Fiction in the Tomsk City Public Library in the Late 19th — Early 20th Centuries

The relevance of reading is determined by its great role in the life of individual and society, due to its multifunctionality and priority position among other means of education and upbringing. Therefore, its study, including in historical retrospective, is an important area of the modern scientific research. Due to the lack of comprehensive studies of library reading in pre-revolutionary Siberia, this article for the first time examines the fiction books lending in the Tomsk City Public Library in the late 19th — early 20th centuries. The purpose of the article is to analyse the demand for fiction by users of the Tomsk City Public Library during the specified period. The tasks are to determine the share of fiction in the total amount of book lending; to make ratings of the most popular domestic and foreign authors of fiction works. The authors use methods of comparative analysis, statistical and source studies. Data were collected from ten reports of the Tomsk City Public Library, as well as from its catalogue, that allowed us to recognize the source base of the article as representative. For the first time, the relative and average number of fiction lending was calculated. The obtained results demonstrate that in the late 19th — early 20th centuries the fiction book lending compounds at least two-thirds of all books lending in the Tomsk City Public Library. The number of fiction lending exceeded the number of lending from other departments by dozens of times. The authors compiled and presented joint and separate ratings of popularity of Russian and foreign authors among users of the library, among whom there were almost only prose writers. It is proven that the works of domestic writers were more in demand among library users, and the percentage of female authors in the top 10 and top 30 was minimal. This study expanded the idea of reading fiction in pre-revolutionary Tomsk, its place in the reading circle and popular authors.
Choosing a Data Caching Strategy in the Implementation of Mobile Application Projects for Working with Clients (In Russ.)

Mobile applications are used to implement business processes of interaction with customers. The authors of the article raised the problem of inefficient, and in some cases incorrect, use of caching in mobile applications, and also indicated what difficulties users may face and what problems this may lead to application developers. The analysis of various caching strategies for mobile applications, such as lazy cache, synchronized cache, write-through cache and lru cache, is carried out. Their advantages and disadvantages are described, the bottlenecks of the caching strategies under consideration are identified. The results of the analysis are summarized in a table. For each of the caching strategies under consideration suitable places of use in the structure of the mobile application are identified and rec-ommendations for their use are proposed. Based on these recommendations, a plan for caching integration was drawn up and an example of such integration was given on a test application with universal functionality. During the integra-tion, the choice of the necessary caching strategy in each of the modules was reasoned and explained. In addition, measurements of the number of requests to the server for data before and after integration were carried out. As a result, the coefficients of the ratio of the number of requests for each of the strategies are obtained.
Mapping of Actual Concentrations of Mobile Forms of Copper in Soils of the Northern Industrial Complex of Volgograd

This paper presents an analysis of the results of a study of the actual concentrations of mobile forms of copper in the soil cover of the northern industrial hub of Volgograd within the assumed zone of influence of local sources of anthropogenic impact. As objects of influence on the components of the environment, the following were selected: a ferrous metallurgy enterprise (JSC “VMK “Krasny Oktyabr”) and a multidisciplinary enterprise (JSC “FNPC “Titan-Barricades”) of Volgograd, characterized by the specifics of the location relative to the functional zoning of the city. Sampling was carried out in 2017-2021 at control points at a distance of 0-4.5 km from the enterprises. During the same period, laboratory studies were carried out using the precision method of atomic absorption spectrometry. A map of the results of monitoring the content of mobile forms of copper in the soil cover in the study area is presented. The identified zone of influence of enterprises, taking into account the presence of additional sources of contamination of the soil cover and the MPC of cuprum, instead of its background concentrations, extends 3-3.5 km from the border of the metallurgical enterprise in the form of elongated areas of increased concentrations. It is noted that there are two pronounced foci of pollution located to the west of the operating SPC of the enterprise, as well as a focus of pollution located outside the boundaries of the sanitary protection zones of JSC “VMK “Krasny Oktyabr” and JSC “FNPC “Titan-Barricades”, in the intersection zone of the 2nd longitudinal highway and General Vatutin Street. The data obtained confirm the expediency of organizing regular monitoring of the soil cover in the city as one of the areas of environmental quality assessment.
Sampling Distributions

Sampling of a distribution and as well as how to treat the sampling distribution of the sample mean is an important topic for understanding statistics. The central limit theorem, when applied to this type of dataset can allow researchers to make predictions about future datasets as well as to better understand current datasets. Normally distributed populations are important to correctly treating the data occurring within the dataset.
Continuous Random Variables

Distributions of data give important information about the dataset, both to researchers and to analysts. Continuous random variables are those variables whose outcomes are measured instead of random variables that are counted. These variables can be handled using probability density functions and cumulative distribution functions. Both have appropriate times and usage cases.
Criminality: As An Aspect Of Psychological Conflicts In Alex Michaelides’ 'The Silent patient'

Psychological conflicts those assist for criminality
Philosophical Reflections on Technology, Politics and Communication in an Ever- changing World

&#x0D; &#x0D; &#x0D; This article is an overview and introduction of the current issue of Filosofija. Sociologija, thematically divided into five chapters. The topics cover various aspects of contemporary world: from the challenges related to technology and democracy to researches on youth values and worldview. What seems to unite all these articles (in spite of their plurality of themes, views and approaches) is the idea of an ever-changing world in which philosophy is interconnected with other sciences and disciplines, in order to provide more consistent and perhaps universal interpretations to the challenges that human beings must face in the contemporary world.&#x0D; &#x0D; &#x0D;