Optimising Pedestrian Flow Around Large Stadiums

This study proposes a method that combines the cellular automaton model and the differential evolution algorithm for optimising pedestrian flow around large stadiums. A miniature version of a large stadium and its surrounding areas is constructed via the cellular automaton model. Special mechanisms are applied to influence the behaviour of an agent that leaves from a certain stadium gate. The agent may be attracted to a nearby business facility and/or guided to uncongested areas. The differential evolution algorithm is then used to determine the optimal probabilities of the influencing agents for each stadium gate. The main goal is to reduce the evacuation time, and other goals such as reducing the costs for the influencing agents’ behaviours and the individual evacuation time are also considered. We found that, although they worked differently in different scenarios, the attraction and guidance of agents significantly reduced the evacuation time. The optimal evacuation time was achieved with moderate attraction to the business facilities and strong guidance to the detouring route. The results demonstrate that the proposed method can provide a goal-dependent, exit-specific strategy that is otherwise hard to acquire for optimising pedestrian flow.

From 3 to 5: Pragmatic Functions of Child Code-Switching

The paper focuses on the pragmatic peculiarities of Russian-English code-switching in the speech of the children who simultaneously acquire Russian and English according to "one person – one language" strategy within a Russian family in Russia. The research data are pragmatically marked utterances of the two boys made when each of them was at the age of three to five. Their bilingualism developed as a monoethnic one since they acquire one of the languages (Russian) from a native Russian speaker and the other (English) from a non-native speaker who belongs to Russian ethnos and culture. The authors argue that pragmatic functions of code-switching reflect the children's attitude to each language and bilingual communication. Child bilingual pragmemes are studied longitudinally, which helps the researchers to reveal the dynamics of code-switching intentions within three years of children's bilingual communication. The results of the study demonstrate the prevalence of addressee-oriented and inducing pragmatic functions of code-switches during the whole period under study. The explanation for this fact lies in the specific strategy of bilingual development and the understanding of the importance of each language in children's bilingual communication. By the age of five, the children gradually develop their bilingual self-reflection, which results in more frequent metalinguistic pragmemes in their mixed utterances.

Aksi Penyerangan Non-Player Character (NPC) Menggunakan Metode Naive Bayes pada Shooter Game

<p>Aksi penyerangan pada <em>non-player character </em>(NPC) merupakan salah satu substansi penting dalam pembuatan <em>game</em>. Dalam melakukan penyerangan diperlukan strategi khusus agar NPC tidak mudah dikalahkan. Salah satunya adalah adanya variasi serangan terhadap pemain. Salah satu metode yang digunakan untuk mengatur penyerangan NPC adalah <em>rulebase</em>. Metode <em>rulebase </em>dapat memberikan variasi serangan sesuai kondisi NPC, namun metode <em>rulebase </em>bisanya menghasilkan <em>behaviour </em>yang statis dan tidak adaptif jika terdapat kondisi baru. AI seperti ini akan mudah diprediksi dan repetitif sehingga menurunkan tingkat tantangan bermain <em>game</em>. Untuk mengatasi masalah tersebut banyak peneliti yang menggunakan teknik <em>learning</em>. Salah satunya menggunakan metode <em>naïve bayes.</em> Pada penelitian ini dilakukan penerapan metode <em>naïve bayes </em>sebagai strategi penyerangan NPC pada <em>shooter game</em>. Metode <em>naïve bayes </em>digunakan untuk keputusan serangan yang diambil oleh NPC. Adapun parameter yang digunakan untuk keputusan penyerangan adalah nyawa, jarak, jumlah granat, dan jumlah amunisi yang dimiliki NPC. Sedangkan keputusan penyerangan dibagi menjadi serangan tembak, serangan granat, dan serangan pisau. Hasil penelitian menunjukkan penerapan metode <em>naïve bayes </em>membuat NPC mampu melakukan penyerangan secara otonom jika terdapat kondisi baru dengan akurasi 80%. Penerapan metode <em>naïve bayes </em>juga lebih unggul dalam persentase kemenangan NPC dibanding metode <em>rulebase</em>. Tingkat kemenangan NPC menggunakan metode <em>naïve bayes </em>sebesar 60% sedangkan <em>rulebase </em>sebesar 16%.</p><p> </p><p><em><strong>Abstract</strong></em></p><p><em>Non-Player Character’s (NPC) attacks behaviour is one important substance in making games. While NPC attacks needs specific strategy to not get defeated easily. One of the NPC attacks strategy is a variation of offense to player. One of the methods to manage the NPC attack strategy is rulebase. Rulebase method can give variations of the NPC attacks according in conditions, but rulebase method usually producing static behaviour and not adaptive where there is new condition. AI like this would easy too predictive and repetitive so that decrease the challenge of playing games. To overcome these problems, we use naïve bayes method. In this study, naïve bayes method are applied as an NPC’s attack strategy to the shooter game. Naïve bayes method used for attack decisions taken by the NPC. The parameters used for the attack’s decision are health point, distance, number of grenades, and number of ammunitions owned by the NPC. While attacks decision is divided into firing attacks, grenade attacks, and melee attacks. The results showed that the use naïve bayes method can attack autonomously if there are new condition with an accuracy of 80%. The implementation of naïve bayes method at NPC more superior than rulebase method in percentage of NPC winning. The NPC win rate uses the naïve bayes method is 60% while the rulebase is 16%.</em><em></em></p><p><em><strong><br /></strong></em></p>

Why Perpetrators and Innocent Victims are Sometimes Harshly judged? Belief in a Just World and Other Situational Determinants

Although Belief in a Just World (BJW) has positive influences on well-being, the attempts to maintain these beliefs may give rise to awry judgments in contexts of harm. In a scenario-based study, we examined the associations of general belief in a just world (GBJW) with BJW maintenance strategies, including victim blaming, victim derogation, perpetrator demonization, and compensation. We hypothesized that because these harsh judgments about victims and offenders along with compensation are used as defensive mechanisms against threats to BJW, using a specific strategy depends on the availability of each strategy and the level of a person’s GBJW. Thus, we also tested whether GBJW and situational cues for victim’s respectability and perpetrator’s evilness have interaction effects on various strategies to defend BJW. By manipulating the characteristics of the victim (professor vs. car dealer) and offender (with evilness cues vs. without evilness cues) in a crime scenario, the interaction effects on judgments about victims and perpetrators as well as compensation were investigated. The results indicated that while GBJW interacted with victim’s respectability and perpetrator’s evilness to predict demonization and derogation, there was no three-way interaction and two-way interaction effects between victim’s respectability and perpetrator’s evilness on the four BJW-maintenance strategies. Taken together, our findings highlight the nuanced effects of just world beliefs on how people react to and make sense of violent incidents.

Fostering Statistical Literacy in Greece

The Hellenic Statistical Authority (ELSTAT), the National Statistical Institute of Greece, as the guarantor of the quality of official statistics in Greece, has been pursuing, since 2016, an ambitious strategy aiming to foster Statistical Literacy, focusing on strengthening ties with citizens in their dual capacity both as providers of data and ultimately as users of statistics, and thus, operate as crucial enablers of a smoothly functioning virtuous circle of official statistics. Objectives include the development of an understanding of basic methodologies and tools used in official statistics, along with the awareness of its institutional foundations and core principles. This critically contributes to the value of official statistics being spread and effectively communicated, making, at the same time, a convincing case for fact-based decision making in the daily lives of the main stakeholders. This article motivates the approach followed in developing a specific strategy on statistical literacy, outlines its philosophy and main objectives and browses through the array of initiatives and actions undertaken over the last five years. In addition, it explores the responsiveness of citizens to these initiatives and the extent to which these initiatives lead to an increased engagement of key targeted stakeholders.

Netflix in Argentina: accelerated expansión and little local production

The aim of this article is to analyze the development of Netflix in Argentina, showing its market penetration, its business strategies, the regulatory framework in which it operates, its content offerings and its subscribers’ consumption. Regarding the menu they offer, the analysis focuses on the “Netflix Originals” section, where the company includes the contents they consider most attractive. The main hypothesis is that the accelerated expansion that the platform has had in Argentina, strengthened by agreements with the main telephone and pay tv companies, has not been accompanied by a specific strategy to develop the production of local contents.

Artificial Intelligence for Smart Systems Critical Analysis of the Human Centered Approach

A program for Artificial Intelligence (AI) is knowledge as intelligent agent, which typically interacts with the ecosystem. This agent is capable of identifying the status of the ecosystem using the sensors before affecting the state via the actuators. We call the smart systems "agents” whenever they are able to make some decisions on their own with respect on particular goals. On the other hand, Machine Learning (ML) signifies a specific strategy meant to design smart systems whereby these systems can adapt to specific behaviors with respect to data. In the modern age, humans are rapidly collaborating with ML and AI systems. The AI that is human-based is a perspective of ML and AI, which algorithms have to be established with the awareness that they are a major segment of the massive system incorporating human. In this paper, we have presented a research that means that AI systems understand humans with respect to their socio-cultural aspects and that AI system assist humans comprehend them. We also present an argument of the challenges of social responsibility e.g. transparency, interpretability, accountability and fairness.

A Bacteriophage DNA Mimic Protein Employs a Non-specific Strategy to Inhibit the Bacterial RNA Polymerase

DNA mimicry by proteins is a strategy that employed by some proteins to occupy the binding sites of the DNA-binding proteins and deny further access to these sites by DNA. Such proteins have been found in bacteriophage, eukaryotic virus, prokaryotic, and eukaryotic cells to imitate non-coding functions of DNA. Here, we report another phage protein Gp44 from bacteriophage SPO1 of Bacillus subtilis, employing mimicry as part of unusual strategy to inhibit host RNA polymerase. Consisting of three simple domains, Gp44 contains a DNA binding motif, a flexible DNA mimic domain and a random-coiled domain. Gp44 is able to anchor to host genome and interact bacterial RNA polymerase via the β and β′ subunit, resulting in bacterial growth inhibition. Our findings represent a non-specific strategy that SPO1 phage uses to target different bacterial transcription machinery regardless of the structural variations of RNA polymerases. This feature may have potential applications like generation of genetic engineered phages with Gp44 gene incorporated used in phage therapy to target a range of bacterial hosts.