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In this paper, several research topics are presented that provide productive avenues of exploration for students in an undergraduate cryptography course. The topics are intended for a variety of skill levels and interests. In some cases, a student might be inspired to try to solve the proposed problem or write computer code. Other topics might motivate them to learn new mathematics or algorithms, or research a historical event or person. In all cases, a short description of the topic is given along with several references that can be used as a starting point for student research. The author also describes some challenges and recommendations when teaching a course where a project is a main component. [ABSTRACT FROM AUTHOR]

The recent adoption of deep learning-based models for the processing and coding of multimedia signals has brought noticeable gains in performance, which have established deep learning-based solutions as the uncontested state-of-the-art both for computer vision tasks, targeting machine consumption, as well as, more recently, coding applications, targeting human visualization. Traditionally, applications requiring both coding and computer vision processing require first decoding the bitstream and then applying the computer vision methods to the decompressed multimedia signals. However, the adoption of deep learning-based solutions enables the use of compressed domain computer vision processing, with gains in performance and computational complexity over the decompressed domain approach. For point clouds (PCs), these gains have been demonstrated in the single available compressed domain computer vision processing solution, named Compressed Domain PC Classifier, which processes JPEG Pleno PC coding (PCC) compressed streams using a PC classifier largely compatible with the state-of-the-art spatial domain PointGrid classifier. However, the available Compressed Domain PC Classifier presents strong limitations by imposing a single, specific input size which is associated to specific JPEG Pleno PCC configurations; this limits the compression performance as these configurations are not ideal for all PCs due to their different characteristics, notably density. To overcome these limitations, this paper proposes the first Adaptive Compressed Domain PC Classifier solution which includes a novel adaptive bridge model that allows to process the JPEG Pleno PCC encoded bit streams using different coding configurations, now maximizing the compression efficiency. Experimental results show that the novel Adaptive Compressed Domain PC Classifier allows JPEG PCC to achieve better compression performance by not imposing a single, specific coding configuration for all PCs, regardless of its different characteristics. Moreover, the added adaptability power can achieve slightly better PC classification performance than the previous Compressed Domain PC Classifier and largely better PC classification performance (and lower number of weights) than the PointGrid PC classifier working in the decompressed domain. [ABSTRACT FROM AUTHOR]

The expansion of underwater scenarios and missions highlights the crucial need for autonomous underwater vehicles (AUVs) to make informed decisions. Therefore, developing an efficient decision-making framework is vital to enhance productivity in executing complex tasks within tight time constraints. This paper delves into task planning and reconstruction within the AUV control decision system to enable intelligent completion of intricate underwater tasks. Behavior trees (BTs) offer a structured approach to organizing the switching structure of a hybrid dynamical system (HDS), originally introduced in the computer game programming community. In this research, an intelligent search algorithm, MCTS-QPSO (Monte Carlo tree search and quantum particle swarm optimization), is proposed to bolster the AUV's capacity in planning complex task decision control systems. This algorithm tackles the issue of the time-consuming manual design of control systems by effectively integrating BTs. By assessing a predefined set of subtasks and actions in tandem with the complex task scenario, a reward function is formulated for MCTS to pinpoint the optimal subtree set. The QPSO algorithm is then leveraged for subtree integration, treating it as an optimal path search problem from the root node to the leaf node. This process optimizes the search subtree, thereby enhancing the robustness and security of the control architecture. To expedite search speed and algorithm convergence, this paper recommends reducing the search space by pre-grouping conditions and states within the behavior tree. The efficacy and superiority of the proposed algorithm are validated through security and timeliness evaluations of the BT, along with comparisons with other algorithms for automatic AUV decision control behavior tree design. Ultimately, the effectiveness and superiority of the proposed algorithm are corroborated through simulations on a multi-AUV complex task platform, showcasing its practical applicability and efficiency in real-world underwater scenarios. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) and related technologies have a long history of being used in education for motivating learners and enhancing learning. However, there have also been critiques for a too uncritical and naïve implementation of AI in education (AIED) and the potential misuse of the technology. With the release of the virtual assistant ChatGPT from OpenAI, many educators and stakeholders were both amazed and horrified by the potential consequences for education. One field with a potential high impact of ChatGPT is programming education in Computer Science (CS), where creating assessments has long been a challenging task due to the vast amount of programming solutions and support on the Internet. This now appears to have been made even more challenging with ChatGPT's ability to produce both complex and seemingly novel solutions to programming questions. With the support of data collected from interactions with ChatGPT during the spring semester of 2023, this position paper investigates the potential opportunities and threats of ChatGPT for programming education, guided by the question: What could the potential consequences of ChatGPT be for programming education? This paper applies a methodological approach inspired by analytic autoethnography to investigate, experiment, and understand a novel technology through personal experiences. Through this approach, the authors have documented their interactions with ChatGPT in field diaries during the spring semester of 2023. Topics for the questions have related to content and assessment in higher education programming courses. A total of 6 field diaries, with 82 interactions (1 interaction = 1 question + 1 answer) and additional reflection notes, have been collected and analysed with thematic analysis. The study finds that there are several opportunities and threats of ChatGPT for programming education. Some are to be expected, such as that the quality of the question and the details provided highly impact the quality of the answer. However, other findings were unexpected, such as that ChatGPT appears to be "lying" in some answers and to an extent passes the Turing test, although the intelligence of ChatGPT should be questioned. The conclusion of the study is that ChatGPT have potential for a significant impact on higher education programming courses, and probably on education in general. The technology seems to facilitate both cheating and enhanced learning. What will it be? Cheating or AI-enhanced learning? This will be decided by our actions now since the technology is already here and expanding fast. [ABSTRACT FROM AUTHOR]

Alan Turing's "Computing Machinery and Intelligence," published in 1950, is one of the founding texts in the field of artificial intelligence (AI), although the term was not coined until 1958, 4 years after his death. From the treatment of human intelligence as computational and the brain as mechanical to the comparison of animals to machines to the disregard for the materiality of computers to programming as a stand-in for procreation to fiction-inspired science, many of the core tenets that have shaped the field of AI have their origins in Turing's paper. A close analysis of the paper exposes some of the problematic logic underlying these tenets that are now proving damaging for both society and the planet. [ABSTRACT FROM AUTHOR]

Learning computer programming is typically difficult for newcomers. Demotivation and learned helplessness have received much attention. Besides the subject's intricacy, low in-class participation has been associated with poor student achievement. This paper presents a follow-up, stage 2 study on the novel instructional technique, Student-Driven Probe Instruction (SDPI), to address low in-class participation in programming courses. Instead of the teacher lecturing/explaining content to the class and asking questions, students were shown a snippet of code or other relevant material and given the option to ask questions beforehand. The study was conducted in two stages: stage 1 pilot and stage 2. This paper presents the results of stage 2, while stage 1 operations and results are discussed briefly. The number of questions asked in class, real-time Trello board postings, and emails/Slack conversations with the instructor were used to track participation. In-class participation showed significant improvement. Average quiz and in-class activity scores showed marginal gains. Results from the endof-course survey show that students preferred SDPI over the traditional lecture style since it stirred their interest in the content and provided them the confidence to ask questions in class. The study is purely exploratory in nature, and no conclusions can be drawn due to the extremely small sample size of the student population. [ABSTRACT FROM AUTHOR]

One of the major challenges arising in internet of military things (IoMT) is accommodating massive connectivity while providing guaranteed quality of service (QoS) in terms of ultra-high reliability. In this regard, this paper presents a class of code-domain nonorthogonal multiple accesses (NOMAs) for uplink ultra reliable networking of massive IoMT based on tactical datalink such as Link-16 and joint tactical information distribution system (JTIDS). In the considered scenario, a satellite equipped with Nr antennas servers K devices including vehicles, drones, ships, sensors, handset radios, etc. Nonorthogonal coded modulation, a special form of multiple input multiple output (MIMO)-NOMA is proposed. The discussion starts with evaluating the output signal to interference-plus-noise (SINR) of receiver filter, leading to the unveiling of a closed-form expression for overloading systems as the number of users is significantly larger than the number of devices admitted such that massive connectivity is rendered. The expression allows for the development of simple yet successful interference suppression based on power allocation and phase shaping techniques that maximizes the sum rate since it is equivalent to fixed-point programming as can be proved. The proposed design is exemplified by nonlinear modulation schemes such as minimum shift keying (MSK) and Gaussian MSK (GMSK), two pivotal modulation formats in IoMT standards such as Link-16 and JITDS. Numerical results show that near capacity performance is offered. Fortunately, the performance is obtained using simple forward error corrections (FECs) of higher coding rate than existing schemes do, while the transmit power is reduced by 6 dB. The proposed design finds wide applications not only in IoMT but also in deep space communications, where ultra reliability and massive connectivity is a keen concern. [ABSTRACT FROM AUTHOR]

Supervisory control and data acquisition (SCADA) system are used in industries to monitor the machines' performances. The machine produced many data that fed into the computer for processing. From the data given, the controller or operator will know the performance of the machines. In this research, the use of SCADA is proposed to monitor the enrolment process in an institution. The proposed SCADA system is a mobile SCADA where an app is designed to monitor the number of candidates enrolled, dropped the programmes enrolled and reasons of dropping the programmes enrolled. All the detail of enrolment data is fed from the front-line operators and the data is interface to the management's mobile terminal via the Internet connection. The paper provides the design of the system using Fuzzy Logic (FL) technology and the app design. The results will show how the Fuzzy Logic (FL) plays an important role to manage and control the data of the enrolment. [ABSTRACT FROM AUTHOR]

The paper provides a detailed overview of the development of a containment pressure and temperature (P/T) analysis methodology for advanced power reactor 1400 (APR1400) nuclear power plants (NPPs). The study addresses the restrictions on exporting independent nuclear power plants by utilizing the containment analysis package (CAP) computer code developed in Korea. One of the key aspects highlighted in the paper is the comparison of results obtained from the CAP code with those from the CONTEMPT-LT/028 code which is used P/T analysis. The analysis focuses on two types of accidents: loss of coolant accidents (LOCA) and main steam line break (MSLB) accidents, which are considered as design basis accidents. By comparing the outcomes of both codes, the paper evaluates the performance and effectiveness of the CAP code in predicting the P/T behavior within the containment during these accidents. The paper also discusses the criteria and technical standards for the containment P/T analysis. It emphasizes the importance of ensuring that the peak P/T remain within the safety related systems, equipment, and structures of NPP. The design pressure is identified as a critical factor in achieving these objectives. In conclusion, the study presents the successful development of a containment P/T analysis methodology using the CAP computer code for APR1400. The methodology considers the specific characteristics of Korean NPPs and new code, CAP. The paper emphasizes the applicability and effectiveness of the CAP code in this context. However, further research and validation efforts are recommended to enhance the accuracy and reliability of the methodology for various design basis accidents. The developed methodology is expected to contribute to the safe and efficient operation of APR1400 NPPs and support Korea's ambitions in exporting NPPs' technology to other countries. [ABSTRACT FROM AUTHOR]

Construction project delays can stem from a myriad of factors and pose significant challenges for owners and contractors. While numerous methods for analyzing delays exist, the majority are designed for network scheduling, lack contemporaneous tracking (i.e., do not allow for identifying and tracking delays as they occur), and struggle with attributing delays to specific stakeholders. Therefore, this paper introduces a novel graphical approach to monitor delays by comparing as-planned and as-built schedules at the activity level. Distinguished by its contemporaneous nature, the new method allows real-time tracking and quantification of delays. This facilitates identifying their origin and potential causes. Rules for constructing the graphs of various delay scenarios are demonstrated for typical activity combinations. The effectiveness of the proposed method is validated via a case study that showcases its practical application. Implementing it is straightforward, and while the method could be applied to network schedules, its relevance lies in linear and repetitive schedules. The cyclic nature of tasks in such schedules underscores the importance of contemporaneous delay tracking to facilitate swift remedial actions and pinpoint liability. Practical Applications: In this study, the authors present a new way to track delay using graphs by comparing starts, productivities, and finishes of as-planned and as-built schedules at the activity level. Because it is contemporaneous, the new approach tracks and measures delays in real time, currently manually, but easily implemented as computer code. This method makes it easier to find the source and possible causes of activity and project delays. Detailed rules are derived for common activity scenarios and interactions on how to create the respective graphs. A real-world study demonstrates how the proposed method can be used to substantiate its potential value to practitioners in industry. The proposed approach is practical, and while it could be used for network schedules, it is especially useful for linear and repetitive schedules. [ABSTRACT FROM AUTHOR]

Teaching programming is a complex process requiring learning to develop different skills. To minimize the challenges faced in the classroom, instructors have been adopting active methodologies in teaching computer programming. This article presents a Systematic Mapping Study (SMS) to identify and categorize the types of methodologies that instructors have adopted for teaching programming. We evaluated 3,850 papers published from 2000 to 2022. The results provide an overview and comprehensive view of active learning methodologies employed in teaching programming, technologies, programming languages, and the metrics used to observe student learning in this context. In the results, we identified thirty-seven different ALMs adopted by instructors. We realized that seventeen publications describe teaching approaches that combine more than one ALM, and the most reported methodologies in the studies are Flipped Classroom and Gamification-Based Learning. In addition, we are proposing an educational and collaborative tool called CollabProg, which summarizes the primary active learning methodologies identified in this SMS. CollabProg will assist instructors in selecting appropriate ALMs that align with their pedagogical requirements and teaching programming context. [ABSTRACT FROM AUTHOR]

This work studied in detail for the first time the bending of laminated composite plates subjected t mechanical variations by new theory Trigonometric and Trigonometric-Hyperbolic functions of shear deformation. From the Euler-Lagrange hypothesis and the equations of the shear deformation theory, we will develop a present method. One of the most important problems of composite plates is the analysis of their bending behavior. The correct approach used to study their bending behavior includes two trigonometric and trigonometric-hyperbolic functions satisfying the null shear stress condition at the free edges. In this paper the bending problem is solved analytically by developing a computational code and numerically solved by Finite Element Method. In order to simplify the study of the bending behavior, an approach taking into consideration the effect of the transverse shear deformation without the shear coefficient of correction with only four unknowns has been developed while requiring five or more unknowns for other theories. Convergence analysis has been carried and the results are compared to open literature available for plate bending analysis. The approach proves to be simple and useful in analyzing the bending behavior of composite layered plates. [ABSTRACT FROM AUTHOR]

The corrosion problem of the tank floor of the oil depot tank area becomes more and more serious with the extension of the operation time. At present, how to determine the potential distribution of the storage tank floor and how to judge the cathodic protection effect of the storage tank floor is the bottleneck of technological development. In this paper, by constructing a mathematical model of cathodic protection in the tank area, influence of deep well anode on potential distribution of tank bottom is calculated by boundary element method (BEM) with computer programming, to study the potential distribution of the tank floor under different anode parameters. The results show that the calculated results are in good agreement with the field measured results, which verifies the accuracy and reliability of the calculation. [ABSTRACT FROM AUTHOR]

In cloud networks, especially those with distributed computing setups and data centers, one of the biggest obstacles is allocating resources. This is the key area, and this must be balanced between optimizing system performance on one side and affordability, stability (reliance) of operation, and energy efficiency. The importance of improving resource allocation methodologies in these complex cloud computing systems is recognized, and therefore this paper comes with an appropriate title-"Enhanced Feature-Driven Multi-Objective Learning for Optimal Cloud Resource Allocation" (OCRA), which integrates together both the latest machine learning techniques as well as traditional concepts from research into cloud computing. OCRA capably analyzes historical files on CPU, memory, disk and network usage. In addition to neatly assimilating large data sets such as that was the compliance rate with past SLAs or workload frequencies over certain time periods and resource allocations; even their patterns of service requests are an important piece of information for many busy people's lives today the adaptive mechanism is one of the defining traits of the model. It can accurately anticipate changes in resource demand and immediately adjust supply, fully able to respond rapidly when fluctuations arise suddenly or unexpectedly. Multi-Objective Random Forests are at the very core of OCRA. Each tree for decision making is specially designed to meet a particular performance objective in mind. Combining these trees into a Random Forest ensemble increases not only the model's predictive accuracy but also its stability. Pareto optimization is wisely used to maintain a balance among performance indicators, without an excessive focus on one effect alone. OCRA is proven empirically through experimental studies where key performance indicators such as Resource Utilization Rate and Quality of Service (QoS) Adherence Rate are taken into account. OCRA is both energy-efficient, an important attribute in today's environmentally conscious world, and does not sacrifice performance. As far as speed, flexibility and overall efficiency are concerned, OCRA has always been superior to the other cloud resources allocation programs of its own day. While it's still not quite ready for users who don't have a firm background in computer science or programming skills (ocra is plotted on 0-x), with sufficient memory and dominant minutes turn into mechanical equipment without configuration services. [ABSTRACT FROM AUTHOR]

Due to the development of social networks and the Internet of things, we recently have faced with large datasets. High-dimensional data is mixed with redundant and irrelevant features, so the performance of machine learning methods is reduced. Feature selection is a common way to tackle this issue with the aim of choosing a small subset of relevant and non-redundant features. Most of the existing feature selection works are for supervised applications, which assume that the information on class labels is available. While in many real-world applications, it is not possible to provide complete knowledge of class labels. To overcome this shortcoming, an unsupervised feature selection method is proposed in this paper. The proposed method uses the matrix factorization-based regularized self-representation model to weight features based on their importance. Here, we initialize the weights of features based on the correlation among features. Several experiments are performed to evaluate the effectiveness of the proposed method. Then the results are compared with several baselines and state-of-the-art methods, which show the superiority of the proposed method in most cases. [ABSTRACT FROM AUTHOR]

The purpose of this article is to present grassroots concepts and ideas about "the algorithm" in the religious context. The power and causality of algorithms are based on lines of computer code, making a society influenced by "black boxes" or "enigmatic technologies" (as they are incomprehensible to most people). On the other hand, the power of algorithms lies in the meanings that we attribute to them. The extent of the power, agency, and control that algorithms have over us depends on how much power, agency, and control we are willing to give to algorithms and artificial intelligence, which involves building the idea of their omnipotence. The key question is about the meanings and the ideas about algorithms that are circulating in society. This paper is focused on the analysis of "vernacular/folk" theories on algorithms, reconstructed based on posts made by the users of Polish Catholic forums. The qualitative analysis of online discourse makes it possible to point out several themes, i.e., according to the linguistic concept, "algorithm" is the source domain used in explanations of religious issues (God as the creator of the algorithm, the soul as the algorithm); algorithms and the effects of their work are combined with the individualization and personalization of religion; algorithms are perceived as ideological machines. [ABSTRACT FROM AUTHOR]

Analog computing is often considered to be an outdated technology only to be found and cared for in museums but not as the basis of modern cutting edge computing. Nothing could be further from reality. Together with quantum computers, analog computers complement today's stored program digital computers, acting as co-processors for certain types of computationally intensive tasks. They are highly energy efficient and exhibit a degree of parallelism that by far surpasses classic digital computers. In contrast to quantum computers, analog computers do not require exotic technologies, no intricate cooling systems, no elaborate shielding systems, etc. In addition to this there already exists a plethora of proven programs for analog computers to solve a wide variety of problems. This paper describes the necessity of analog computing for the twenty-first century, gives a short introduction to the structure and programming of analog computers, before discussing future application areas. Analog computing will drastically alter the way we think about computing in the years to come as it will become an integral part of every high performance computer. It will be an indispensable technology for future AI systems, it will revolutionize many medical applications, it might even replace or at least complement, certain types of quantum computers, etc. [ABSTRACT FROM AUTHOR]

News recommender systems (NRS) are crucial for helping users navigate the vast amount of content available online. However, traditional NRS often suffer from biases that lead to a narrow and unfair distribution of exposure across news items. In this paper, we propose a novel approach, the Contextual-Dual Bias Reduction Recommendation System (C-DBRRS), which leverages Long Short-Term Memory (LSTM) networks optimized with a multi-objective function to balance accuracy and diversity. We conducted experiments on two real-world news recommendation datasets and the results indicate that our approach outperforms the baseline methods, and achieves higher accuracy while promoting a fair and balanced distribution of recommendations. This work contributes to the development of a fair and responsible recommendation system. [ABSTRACT FROM AUTHOR]

This paper presents a study guide and an analysis of its use in the computer programming learning process of an 8-year-old elementary school student through the Scratch program. The research's objective is to explore and understand how this individual student approaches learning programming skills and tackles challenges within the Scratch environment. An individual case study approach was adopted at home, combining qualitative and quantitative methods to gain a comprehensive insight into the student's learning process. The study was conducted without grant support, and the researcher actively participated as an educator and observer in the student's learning sessions. Performance was assessed, and a semi-structured interview was conducted to inquire about the student's experiences, motivations, and interests regarding programming in Scratch, as well as their feelings after the training. Additionally, the student's activities during programming sessions were meticulously recorded, and projects created in Scratch were analyzed to assess progress and understanding of concepts. The findings of this research have the potential to contribute to the field of programming education and provide valuable insights into how young elementary school-aged individuals can acquire computer and programming skills in an interactive environment such as Scratch. The results obtained demonstrate that using the proposed guide to introduce elementary school students to programming at home, with parents acting as educators, is feasible. Therefore, it helps facilitate access to this knowledge, which is currently limited for many individuals in an official educational setting. [ABSTRACT FROM AUTHOR]

Pedagogic Conversational Agents (PCAs) are interactive systems that engage the student in a dialogue to teach some domain. They can have the roles of a teacher, student, or companion, and adopt several shapes. In our previous work, a significant increase of students' performance when learning programming was found when using PCAs in the teacher role. However, it is not common to find PCAs used in classrooms. In this paper, it is explored whether pre-service teachers would accept PCAs to teach programming better if they were co-designed with them. Pre-service teachers are chosen because they are still in training, so they can be taught what PCAs are and how this technology could be helpful. Moreover, pre-service teachers can choose whether they integrate PCAs in the teaching activities that they carry out as part of their degree's course. An experiment with 35 pre-service primary education teachers was carried out during the 2021/2022 academic year to co-design a robotic PCA to teach programming. The experience validates the idea that involving pre-service teachers in the design of a PCA facilitates their involvement to integrate this technology in their classrooms. In total, 97% of the pre-service teachers that stated in a survey that they believed robot PCA could help children to learn programming, and 80% answered that they would like to use them in their classrooms. [ABSTRACT FROM AUTHOR]

This paper presents a new method of reducing the inrush current and improving the starting performance of a line-start permanent-magnet synchronous motor (LSPMSM). The novelty of the proposed method relies on the selection of the time instant of the connection of the stator winding to the grid, for which the smallest values of the amplitudes of inrush currents are obtained. To confirm the effectiveness of the developed method of limiting the inrush current, simulations and experimental studies were carried out. The algorithm and dedicated computer code developed by the authors for the analysis of transient coupled phenomena in the LSPMSM were used to study the impact of the time instant of connection of the winding to the grid on the motor start-up process. The algorithm was based on a field model of coupled electromagnetic and thermal phenomena in the studied motor. To verify the developed model of the phenomena and the proposed method, experimental research was carried out on a purpose-built computerised test stand. Good concordance between the results of the experiments and simulations confirmed the high reliability of the proposed model, as well as the effectiveness of the developed approach in limiting the inrush current and improving the starting performance of LSPMSMs. [ABSTRACT FROM AUTHOR]

Introduction: The likelihood ratio (LR) can be an efficient means of distinguishing various relationships in forensic fields. However, traditional list-based methods for derivation and presentation of LRs in distant or complex relationships hinder code editing and software programming. This paper proposes an approach for a unified formula for LRs, in which differences in participants' genotype combinations can be ignored for specific identification. This formula could reduce the difficulty of by-hand coding, as well as running time of largesample-size simulation. Methods: The approach is first applied to a problem of kinship identification in which at least one of the participants is alleged to be inbred. This can be divided into two parts: i) the probability of different identical by descent (IBD) states according to the alleged kinship; and ii) the ratio of the probability that specific genotype combination can be detected assuming the alleged kinship exists between the two participants to the similar probability assuming that they are unrelated, for each state. For the probability, there are usually recognized results for common identification purposes. For the ratio, subscript letters representing IBD alleles of individual A's alleles are used to eliminate differences in genotype combinations between the two individuals and to obtain a unified formula for the ratio in each state. The unification is further simplified for identification cases in which it is alleged that both of the participants are outbred. Verification is performed to show that the results obtained with the unified and list-form formulae are equivalent. Results: A series of unified formulae are derived for different identification purposes, based on which an R package named KINSIMU has been developed and evaluated for use in large-size simulations for kinship analysis. Comparison between the package with two existing tools indicated that the unified approach presented here is more convenient and time-saving with respect to the coding process for computer applications compared with the list-based approach, despite appearing more complicated. Moreover, the method of derivation could be extended to other identification problems, such as those with different hypothesis sets or those involving multiple individuals. Conclusion: The unified approach of LR calculation can be beneficial in kinship identification field. [ABSTRACT FROM AUTHOR]

The present paper explains the performance of a production process of finite capacity for two classes of customers who may exhibit impatience. The arrivals can be found in terms of batches and will be picked for service in FIFO mode. The production requests can come in two ways (i) on immediate demand, (ii) for future stock purposes. Taking this point, we have taken two-class customers with different arrival rates. Also assumed state-dependent service with which process has to be triggered to avoid congestion. A computer programme has been executed for the R-K method to solve the transient equations for transient probabilities with the given input values of arrival rates of two-class customer orders, service rates and system capacity. System performance indices have been computed and shown numerical illustrations to assess the influence input parameters on performance indices. [ABSTRACT FROM AUTHOR]

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Artificial General Intelligence is the idea that someday an hypothetical agent will arise from artificial intelligence (AI) progresses, and will surpass by far the brightest and most gifted human minds. This idea has been around since the early development of AI. Since then, scenarios on how such AI may behave towards humans have been the subject of many fictional and research works. This paper analyzes the current state of artificial intelligence progresses, and how the current AI race with the ever faster release of impressive new AI methods (that can deceive humans, outperform them at tasks we thought impossible to tackle by AI a mere decade ago, and that disrupt the job market) have raised concerns that Artificial General Intelligence (AGI) might be coming faster that we thought. In particular, we focus on 3 specific families of modern AIs to develop the idea that deep neural networks, which are the current backbone of nearly all artificial intelligence methods, are poor candidates for any AGI to arise due to their many limitations, and therefore that any threat coming from the recent AI race does not lie in AGI but in the limitations, uses, and lack of regulations of our current models and algorithms. [ABSTRACT FROM AUTHOR]

The need to develop new systems for detecting and counteracting malware remains relevant. In addition to malware detection methods, the need to develop new systems for detecting and counteracting malware has become increasingly important. The use of various detection systems and the formation of a variable architecture in them significantly improves the effectiveness of detection, since both for attackers in computer attacks and for malware, understanding the system is significantly complicated. In addition, such systems may contain baits, traps, and, accordingly, modifiable operating environments to deceptively execute programs for research. This paper develops a conceptual model of multicomputer systems, which is designed to ensure the functioning of antivirus bait and traps to detect malware and computer attacks in corporate networks. The proposed approach is intended to prevent and counteract metamorphic virus penetration. This paper presents the conceptual model of multicomputer systems and introduces a defining characteristic responsible for the control of decisions and other defining characteristics of the system. Methods for detecting metamorphic viruses with the possibility of their implementation in the architecture of multi-computer systems with bait and traps are developed so that the system directly joins the detection procedure through its components and decides on the presence of metamorphic code in the executable file. An implementation of a multi-computer malware detection system with metamorphic functionality was developed to prove the feasibility of the proposed conceptual architecture model and the developed methods for detecting metamorphic viruses. An experiment on the functioning of a multi-computer malware detection system was set up, and experimental studies were conducted. The conducted experiments included metamorphic virus detection. In addition, an experiment on the effectiveness of detecting the metamorphic code of viruses was conducted. The efficiency of detecting metamorphic virus code using the developed multi-computer system was also investigated, and the presence of improved detection was established. The directions of further work are to extend the results of this work to new types of malware. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to present an easier and more efficient method for the determination of the geometry of a bevelled gear tooth. Based on a method that provides an easier way for the rack generation of involute helical gears, the mathematical model of a beveloid gear is studied. The mathematical procedure for developing two-dimensional cross-sections has been extended to three-dimensional gear models. A computer programme is developed to obtain generating and generated surfaces. The proposed algorithm is compared with the previous studies for verification and validation. The results demonstrate that the coordinates obtained from the given method are nearly the same on the start and end points of the main gear parts, such as the involute and root fillets regions. Also, between the limits, the values can be considered acceptable. A coordinate deviation of the gear profile has been observed in the mathematical model, because of the profile shift. Modifications have been developed in the equations to eliminate these cases. The main advantage of the proposed method is to obtain mathematical models without carrying out some of the calculation steps used in previous studies. Eventually, this feature will provide an easier and faster method to develop computer-aided models of the beveloid gear types. [ABSTRACT FROM AUTHOR]

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Whereas hackathons are widespread within and outside academia and have been argued to be a valid pedagogical method for teaching interdisciplinarity, no detailed frameworks or methods are available for conceptualizing and organizing educational hackathons, i.e., hackathons dedicated to best achieving pedagogic objectives. This paper is dedicated to introducing EDUCational Hackathons for learning how to solve Interdisciplinary Challenges (EDUCHIC) through: (1) defining the fundamental principles for framing an activity as an EDUCHIC, integrating principles from pedagogical methods, hackathon organization, and interdisciplinarity processes; (2) describing general properties that EDUCHIC possess as a consequence of the interaction of the fundamental principles; (3) developing operational guidelines for streamlining the practical organization of EDUCHIC, including an exhaustive end‐to‐end process covering all the steps for organizing EDUCHIC and practical frames for carrying the key decisions to be made in this process; and (4) a demonstration of these guidelines through illustrating their application for organizing a concrete EDUCHIC. [ABSTRACT FROM AUTHOR]

Hackathon has been growing and taking various industries by storm thanks to its flexibility and ability to fit into them. It has been proven successful and helpful in solving different IT and non-IT challenges. They also serve as an intriguing educational and networking tool, encouraging people to pursue innovative studies and activities. However, a hackathon is like a two-edged sword with its downsides – it requires significant investment and can fail if mismanaged. It is critical to recruit and gather participants suitable to face a particular technological or non-technological challenge and to motivate a group to perform innovative action and benefit from the learning-by-doing approach. This paper identifies 21 reasons to attend hackathons backed by existing research and presents a study conducted on 109 hackathon participants that help to score, rank and explain those attributes. Results have proven the importance of challenge and networking over monetary prizes and glory. [ABSTRACT FROM AUTHOR]

Computer programming and municipal engineering (ME) students' specialised knowledge are still poorly integrated, leading to limited improvement of students' programming abilities. This paper describes an effective attempt in ME at Xi'an University of Architecture and Technology (XAUAT). Students were divided into several teams and required to develop software tools for ME design problems using Visual C++ 6.0. In this teaching approach, students need to identify the solutions by integrating knowledge in mathematics, physics, chemistry, basic engineering science, and ME. Moreover, students should develop programmes with friendly interfaces, essential prompts, and reliable results. The example programmes, positive feedback from the survey, and better performance in the final examination proved that the students' abilities of knowledge application and problem-solving had been developed, and their motivation in learning programming had been improved. [ABSTRACT FROM AUTHOR]

Cirques are often the most representative and numerous landforms in alpine glaciated watersheds. The readily mappable and measurable nature of cirques (especially aspects and floor elevations) may yield information about the climatic, geologic, and topographic conditions that created them. These ubiquitous landforms are the foci of an alpine glacial geomorphology exercise in an intermediate-level, university geomorphology course. The exercise involves a step-by-step approach using topographic maps and remotely sensed imagery to identify and map cirques, measure cirque aspects and floor elevations, and plot and analyze the resulting data. Students interpret their mapping and analysis results in the context of published literature, ultimately incorporating all into a research paper. Student comments and self-evaluations over time show that the exercise is an effective tool for learning glacial geomorphology, topographic map, and remotely sensed image analysis, data analysis, and report writing. [ABSTRACT FROM AUTHOR]

This work is primarily the product of the first listed author, who completed it as a student under the direction of the second and third listed authors. In this paper we analyze three progressive betting strategies, each applied to three casino games. The betting strategies considered are Martingale, Paroli, and Fibonacci, each applied to the casino games blackjack, craps, and roulette. The aim of this analysis is to try to identify optimal betting strategies for each game with a given or maximum number of bets placed that pay 1:1. The purpose of this work is not to try to discover methods for “beating the house,” which are already known to not exist, but rather to search for methods for advancing gameplay through a given or maximum number of bets while retaining the possibility of earning a profit. Programming in the computer algebra system Maple, more specifically through the use of a Maplet, which is like an applet but uses (and requires) Maple’s engine, will be used for calculations. [ABSTRACT FROM AUTHOR]

Background: With the development of computational literacy, there has been a surge in both research and practice application of text‐based and block‐based modalities within the field of computer programming education. Despite this trend, little work has actually examined how learners engaging in programming process when utilizing these two major programming modalities, especially in the context of secondary education settings. Objectives: To further compare programming effects between and within text‐based and block‐based modalities, this research conducted a quasi‐experimental research in China's secondary school. Methods: An online programming platform, Code4all, was developed to allow learners to program in text‐based and block‐based modalities. This research collected multimodal data sources, including programming platform data, process data, and performance data. This research further utilized multiple learning analytics approaches (i.e., clustering analysis, click stream analysis, lag‐sequential analysis and statistics) to compare learners' programming features, behavioural patterns and knowledge gains under two modalities. Results and Conclusions: The results indicated that learners in text‐based modality tended to write longer lines of code, encountered more syntactical errors, and took longer to attempt debugging. In contrast, learners in block‐based modality spent more time operating blocks and attempt debugging, achieving better programming knowledge performances compared to their counterparts. Further analysis of five clusters from the two modalities revealed discrepancies in programming behavioural patterns. Implications: Three major pedagogical implications were proposed based on empirical research results. Furthermore, this research contributed to the learning analytics literature by integrating process‐oriented and summative analysis to reveal learners' programming learning quality. Lay Description: What is currently known about the subject matter: Programming has the potential to improve learners' higher‐order thinking skills.Block‐based and text‐based modalities are two major instructional methods.There has been a growing interest to understand how learning occurs in two modes.Most previous work has evaluated two modalities based on learners' knowledge, skills, and attitudes. What this paper adds: Code4all allows learners to programming in text‐based and block‐based modalities.Quasi‐experimental research was conducted to examine block‐based and text‐based programming modalities.Multimodal learning analytics were used to compare programming under two modalities.Learners' programming features, behaviouralbehavioral patterns, and knowledge gains were identified under two modalities. The implications of study findings for practitioners: Instructors should integrate text‐based and block‐based modalities into programming courses.Process‐oriented assessment should be integrated with summative assessment. Adaptive, timely scaffoldings should be provided with the external support (this should be marked like above two points). [ABSTRACT FROM AUTHOR]

There is rapidly developing interest in legal coding, the development of machine-consumable code representations of legal rules. However, interpretive ambiguities inherent in legal rules make it challenging to directly translate law into code. Interpretive ambiguities pose challenges for legal coders, who must determine the extent to which they disambiguate rules, as well as the interpretive methods applied. Similar interpretive issues have been historically addressed in the field of legal translation. This paper argues that a legal translation framework, known as the principle of fidelity, can be used to better understand and resolve interpretive ambiguities inherent in the legal coding process. Three models of fidelity prominently discussed in legal translation literature are adapted and applied to legal coding. Accordingly, the application of fidelity models to the legal coding process could provide new understanding and methods to address complex interpretive ambiguities. [ABSTRACT FROM AUTHOR]

In statistical process monitoring, control charts typically depend on a set of tuning parameters besides its control limit(s). Proper selection of these tuning parameters is crucial to their performance. In a specific application, a control chart is often designed for detecting a target process distributional shift. In such cases, the tuning parameters should be chosen such that some characteristic of the out-of-control (OC) run length of the chart, such as its average, is minimized for detecting the target shift, while the control limit is set to maintain a desired in-control (IC) performance. However, explicit solutions for such a design are unavailable for most control charts, and thus numerical optimization methods are needed. In such cases, Monte Carlo-based methods are often a viable alternative for finding suitable design constants. The computational cost associated with such scenarios is often substantial, and thus computational efficiency is a key requirement. To address this problem, a two-step design based on stochastic approximations is presented in this paper, which is shown to be much more computationally efficient than some representative existing methods. A detailed discussion about the new algorithm's implementation along with some examples are provided to demonstrate the broad applicability of the proposed methodology for the optimal design of univariate and multivariate control charts. Computer codes in the Julia programming language are also provided in the . [ABSTRACT FROM AUTHOR]

In response to a 2023 article by Jay Lampert in Deleuze and Guattari Studies, this paper develops the question of what Deleuze and Guattari might make of AlphaGo, the artificial intelligence developed by Google which defeated one of the top human Go players in 2016. It approaches the question in a way that supplements and complements Lampert's analysis, by noting the well-worn analogy between computer programming and evolutionary biology and then cross-referencing it with Deleuze and Guattari's attitude towards the latter in A Thousand Plateaus. The results reinforce Lampert's conclusion that AlphaGo is not 'nomadic', but they show that this is precisely because AlphaGo's algorithms are reminiscent of Darwin's mechanism of natural selection. [ABSTRACT FROM AUTHOR]