Puzzle Solution Research Articles

CoinFA: an efficient coin mixing scheme with flexible amounts

Abstract Coin mixing is an efficient anonymization technology of cryptocurrency used to eliminate the linkability of transaction parties by hiding their addresses in an anonymous set. However, a common weakness with most existing coin mixing schemes is that the amount of mixed coins must be the same for all requests within a mixing cycle, otherwise it is easy for an attacker to restore the linkability of transaction parties. In this paper, we design a stage-payable puzzle solution mechanism, named CoinFA, which reverses the control of the requesting amounts to the users for flexible mixing amounts. In our design, the payee (with an output address) first requests a puzzle from the mixers and the latter are the only ones who know the solution of the puzzle. If the payee solves the puzzle successfully, he can be rewarded with the corresponding Bitcoins. The payer (allowed to have multiple input addresses) then requests the solution by paying in installments. We achieve better security by weakening the rights of the involved third parties, while the hierarchical structure allows our solution to have better efficiency and robustness. We perform a security analysis on CoinFA based on the standard Rivest-Shamir-Adleman (RSA) assumption and Elliptic Curve Digital Signature Algorithm unforgeability. We also analyze the performance of CoinFA by comparing it with two related schemes, and the results show that our CoinFA scheme has a greater advantage when the mixing amount is relatively small.

RECONFIGURATION OF SOLAR PANELS TO PRODUCE MAXIMUM POWER USING NOVEL METHOD (TOUR PUZZLE)

This paper introduces a new reconfiguration technique called tour puzzle for better shadow dispersion and obtaining maximum output power under partial shade conditions. In the presented method, partial shadows are spread in all rows and maximum power can be achieved. The puzzle tour can be applied to all kinds of PV arrays of different dimensions and sizes. Accordingly, the puzzle tour procedure is applied in several cases in the form of squares and rectangles with different dimensions and various shading conditions in each case. To directly compare and present the efficiency of the proposed method, the total cross-connection model and conventional methods such as magic Square puzzle, competence Square puzzle, Skyscraper and improved Sudoku are also implemented in the introduced cases. Finally, the evaluations emphasize the capability and efficiency of the Tour puzzle solution compared to other methods by achieving GMPP values such as 63.9 VmIm, 69.3 VmIm, 69.3 VmIm and 68.4 VmIm for cases 1 to 4, respectively. The results show that the proposed method can provide acceptable performance for solving the problem of achieving maximum power under PSC in PV.

A BACKTRACKING APPROACH FOR SOLVING PATH PUZZLES

We study algorithmic aspects of the Path puzzle--a logic puzzle created in 2013 and confirmed NP-complete (Non-deterministic Polynomial-time-complete) in 2020. We propose a polynomial time algorithm for verifying an arbitrary Path puzzle solution and a backtracking-based method for finding a solution to an arbitrary Path puzzle instance.To our knowledge, our study is the first rigorous investigation of an imperative algorithmic approach for solving Path puzzles. We prove that the asymptotic running time of our proposed method in solving an arbitrary Path puzzle instance of size $m \times n$ is $O(3^{mn})$. Despite this exponential upper bound, experimental results imply that a C++ implementation of our algorithm can quickly solve $6 \times 6$ Path puzzle instances in less than 30 milliseconds with an average of 3.02 milliseconds for 26 test cases. We finally prove that an $m \times n$ Path puzzle instance without row and column constraints is polynomially solvable in $O(\max\{m,n\})$ time.

Siamese-Discriminant Deep Reinforcement Learning for Solving Jigsaw Puzzles with Large Eroded Gaps

Jigsaw puzzle solving has recently become an emerging research area. The developed techniques have been widely used in applications beyond puzzle solving. This paper focuses on solving Jigsaw Puzzles with Large Eroded Gaps (JPwLEG). We formulate the puzzle reassembly as a combinatorial optimization problem and propose a Siamese-Discriminant Deep Reinforcement Learning (SD2RL) to solve it. A Deep Q-network (DQN) is designed to visually understand the puzzles, which consists of two sets of Siamese Discriminant Networks, one set to perceive the pairwise relations between vertical neighbors and another set for horizontal neighbors. The proposed DQN considers not only the evidence from the incumbent fragment but also the support from its four neighbors. The DQN is trained using replay experience with carefully designed rewards to guide the search for a sequence of fragment swaps to reach the correct puzzle solution. Two JPwLEG datasets are constructed to evaluate the proposed method, and the experimental results show that the proposed SD2RL significantly outperforms state-of-the-art methods.

Comparison of A* Algorithm and Greedy Best Search in Searching Fifteen Puzzle Solution

Artificial Intelligence is an exciting field to research. Artificial Intelligence itself is a broad subject. The application of artificial intelligence in daily routine is various. One of the usages of artificial intelligence is finding the shortest route on a map. In general, the algorithm which can be used for finding the shortest route is A*. A* is often used in finding the shortest route in a graph or map. Generally speaking, A* is used to make a game, especially for finding the shortest route of an intelligent agent inside it. In this paper, the finding solution of puzzle game using A* and Greedy Best First Search is to be discussed. The puzzle game which is discussed is the Fifteen Puzzle. This research compares the two algorithms used, A* and Greedy Best First Search. This research shows that Greedy Best First Search gives a slightly faster solution than A*.

DEVELOPING AN EDUCATIONAL CULTURAL HERITAGE 3D PUZZLE IN A VIRTUAL REALITY ENVIRONMENT

Abstract. The ways our cultural heritage reserve is preserved and disseminated to the public have changed significantly, with the use of immersive technologies, such as virtual reality environments, and serious games. Nowadays, these technologies are also exploited for developing interactive informative applications, to support historical education and enhance museum visits, physical or virtual, especially to younger generations. The field of edutainment, educational entertainment, has been rapidly developing during the last 10 or 15 years. The main goal of this research is to develop an educational 3D puzzle-like serious game which can operate within a virtual reality environment while aiming towards the dissemination of cultural heritage content to the younger public, i.e., students, children etc., through a pleasant gamification process. The cultural heritage objects used are an ancient Greek temple and a statue of the Roman era, whose high-resolution fully textured 3D models were available from previous projects. The game application was developed in Unity game engine with suitable coding to enable the smooth execution of the 3D puzzle solution. The application verified that it is more interesting to learn about cultural assets through a game than in the conventional ways, and even more when it is implemented within a Virtual Reality environment, where the contact with the assets appears to be more direct and realistic. The same application can also be utilized in different educational areas and can be expanded by the inclusion of other digital assets.

DONS: Dynamic Optimized Neighbor Selection for smart blockchain networks

Blockchain (BC) systems mainly depend on the consistent state of the Distributed Ledger (DL) at different logical and physical places of the network. The majority of network nodes need to be enforced to use one or both of the following approaches to remain consistent: (i) to wait for certain delays (i.e. by requesting a hard puzzle solution as in PoW and PoUW, or to wait for random delays as in PoET, etc.) (ii) to propagate shared data through shortest possible paths within the network. The first approach may cause higher energy consumption and/or lower throughput rates if not optimized, and in many cases these features are conventionally fixed. Therefore, it is preferred to enhance the second approach with some optimization. Previous works for this approach have the following drawbacks: they may violate the identity privacy of miners, only locally optimize the Neighbor Selection method (NS), do not consider the dynamicity of the network, or require the nodes to know the precise size of the network at all times. In this paper, we address these issues by proposing a Dynamic and Optimized NS protocol called DONS, using a novel privacy-aware leader election within the public BC called AnoLE, where the leader anonymously solves the The Minimum Spanning Tree problem (MST) of the network in polynomial time. Consequently, miners are informed about the optimum NS according to the current state of network topology. We analytically evaluate the complexity, the security and the privacy of the proposed protocols against state-of-the-art MST solutions for DLs and well known attacks. Additionally, we experimentally show that the proposed protocols outperform state-of-the-art NS solutions for public BCs. Our evaluation shows that the proposed DONS and AnoLE protocols are secure, private, and they acutely outperform all current NS solutions in terms of block finality and fidelity.

July puzzle solution

July puzzle solution

The evolutionary puzzle solution for the origins of the partial loss of the Cτ2 exon in notothenioid fishes

Cryonotothenioidea is the main group of fishes that thrive in the extremely cold Antarctic environment, thanks to the acquisition of peculiar morphological, physiological and molecular adaptations. We have previously disclosed that IgM, the main immunoglobulin isotype in teleosts, display typical cold-adapted features. Recently, we have analyzed the gene encoding the heavy chain constant region (CH) of the IgT isotype from the Antarctic teleost Trematomus bernacchii (family Nototheniidae), characterized by the near-complete deletion of the CH2 domain. Here, we aimed to track the loss of the CH2 domain along notothenioid phylogeny and to identify its ancestral origins. To this end, we obtained the IgT gene sequences from several species belonging to the Antarctic families Nototheniidae, Bathydraconidae and Artedidraconidae. All species display a CH2 remnant of variable size, encoded by a short Cτ2 exon, which retains functional splicing sites and therefore is included in the mature transcript. We also considered representative species from the three non-Antarctic families: Eleginopsioidea (Eleginops maclovinus), Pseudaphritioidea (Pseudaphritis urvillii) and Bovichtidae (Bovichtus diacanthus and Cottoperca gobio). Even though only E. maclovinus, the sister taxa of Cryonotothenioidea, shared the partial loss of Cτ2, the other non-Antarctic notothenioid species displayed early molecular signatures of this event. These results shed light on the evolutionary path that underlies the origins of this remarkable gene structural modification.

Using Useful Tasks for Proof-of-Work for Blockchain Systems

This paper logically continues the paper about possible approaches to solving the “useful proof-of-work for blockchains” problem. We propose some alternative lines of searching for useful tasks for proof-of-work. These approaches are based on a fact that solving the hash puzzle is close to the multiple and independent repetition of the following experiment: assume that there is a fairly large set defined (for example, consisting of 2n elements for a fairly high n), and only a minor portion of the elements have a certain property. The experiment consists in uniformly choosing an element from this set and then checking whether this element has the indicated property. Thus the hash puzzle solution process can be replaced, for example, with searching for rare astronomical objects or positions in a game of Go that meet certain conditions. Moreover, we describe a possible attack against the blockchain system in which the task instance generation algorithm is replaced with the algorithm of choosing instances from the available database by unscrupulous task instance suppliers in case of their public collection. In addition, some ways of protecting against this attack are discussed.

Kurdish Language Learning Tool in Serious Game

In this era, technology has a great impact on the educational system as they have on the other different areas of today’s life, for instance, smartphone devices are the best examples. Software technology vendors moving toward developing tremendous applications in the education field. However, the lack of applications that satisfy the ambition of those wishing to learn the Kurdish language is still an obstacle in this field, specifically the field of smartphone devices technology and gaming industry. Hence smartphone devices become user-friendly and necessary tools in every individuals’ life, as it is a multi-function device. In this paper we designed and implemented a smartphone application to learn the Kurdish language and improve vocabulary via a serious game. The application designed for android devices, enables users to learn and improve the Kurdish language. The application is also suitable for foreign people who desire to learn the Kurdish language. The system proposed in this paper introduces a smartphone application with an acceptable user interface for an exciting, interesting and challenging puzzle game at a time. The main goal is to learn Kurdish vocabulary using crossword puzzle, solving hidden words, find and circle the crossword in the puzzle solution in the context of a serious game.

ChemEscape, Polymer Chemistry: Solving Interactive Puzzles Featuring Scaffolded Learning to Promote Student Understanding of Polymers and Structure–Property Relationships

The introduction of polymer chemistry in undergraduate science courses is becoming more popular in recent years, introducing content into the relationships between polymer structure and physical properties in a variety of contexts. However, active learning techniques, outside of laboratory experience, for teaching polymer chemistry are extremely limited. The ChemEscape project has successfully integrated escape-room type puzzle design and course specific learning objectives into an interactive learning experience. The novel battle box design, a self-contained puzzle unit, allows for puzzles to be easily transported and applied as a teaching tool in large postsecondary classrooms as well as an outreach tool. Herein, we describe the design and application of a series of new polymer puzzles, focusing on tacticity, elasticity, and hydrophobicity, into the battle box design as well as an all-in-one backdrop design. Puzzles are scaffolded to allow for all learning to be combined in the final puzzle solution as well as a workbook provided for participants to record observations and learning during the puzzles’ solutions.

The Equity Premium Puzzle Solution: Incentives to Under-Report Inflation

The biggest and most well-known unsolved problem in academic finance is famously referred to as the Equity Premium Puzzle. It refers to the unexplained phenomenon that for over 100 years the average return on a well-diversified portfolio of equities has far outperformed that of risk-free, short-term US treasuries. Although there have been countless proposed solutions, all have failed as these attempts implicitly assume perfectly-correct inflation statistics. Examining these assumptions, we discover that not only are the inflation numbers materially flawed, but more so, there are significant incentives for government entities to under-report inflation. With this, we find that to explain the Equity Premium Puzzle, inflation would only need to be under-reported by about 2-6% per year: an exceedingly likely scenario given the significance of these incentives.

Puzzle Solution of the compilation and circulation of Classics on Acupuncture and Plain Questions

Through mining and collecting the compiling thought of Miraculous Pivot (《》) and Plain Questions (《》), which were handed down from ancient times, it is discovered that these two ancient works refer to two components of one integrity book. With regard to the character and relationship, Miraculous Pivot is the main section and the essence, focusing on theoretic innovation. "Writing" is predominated in its statement. Plain Questions is the supplementary opinions to the main section, containing clinical application and material collection. "Compiling" is predominated in its statement. Both of two works were completed between the late Western Han Dynasty and the Eastern Han Dynasty. The author was a leading scholar and had worked in a national library for a long time. Before the Song Dynasty, Plain Questions had been widely circulated, while the spreading of Miraculous Pivot was limited. In the process of inheritance, some of the content of these two works were lost or supplemented, and the chapters were disarranged or adjusted artificially. But, in general, the original is not distorted seriously, especially the essential section, Miraculous Pivot.

ChemEscape: Educational Battle Box Puzzle Activities for Engaging Outreach and Active Learning in General Chemistry

Escape rooms are physical adventure games where players solve a series of puzzles and riddles. Using clues and hints participants focus on completing a series of tasks within a set time frame. Because participants of escape rooms interact with a variety of challenging problems in an experiential manner they are of interest as active learning tools. To engagingly accommodate a broad audience, however, the puzzles in traditional escape rooms have limited requirements for specialized participant skills or knowledge. In contrast, ChemEscape strives to both engage and have participants enhance and apply discipline specific skills and knowledge during puzzle solution. This is achieved by incorporating opportunities to learn about objectives and hands-on problem-solving skills typical of research-based experiences. Described herein are four hands-on general chemistry puzzles for use in the novel Battle Box design at the grade 4–12 level and first year general chemistry.

The negative growth of a brief depressive spell among U.S. adolescents

Studying adolescent-onset brief depressive spells, we saw a chance to adapt a cross-cohort approach for successive cross-sectionally gathered epidemiological estimates on birth cohorts. The United States (US) study population estimates are for noninstitutionalized community-dwelling 17- to 18-year-olds, sampled, recruited, and assessed using audio computer assisted self-interviews for the National Surveys on Drug Use and Health each year, 2008-2016. Estimated age and year-specific lifetime history cumulative incidence proportions are presented, with 95% confidence intervals, as well as age-specific meta-analysis summary estimates. Occurrence of a brief depressive spell (BDS) among the 2008 U.S. 17-year-olds showed a surprising difference with the 2009 statistically independent sample of that same "birth cohort" assessed at age 18 years. "Negative growth" was seen instead of an expected increase in those affected. Independent replication estimates of this BDS negative growth difference were seen in multiple successive birth cohorts. This well-replicated difference in BDS estimates offers a fascinating puzzle to be solved with focused inquiry. The puzzle's solution is important because National Surveys on Drug Use and Health does not assess Major Depression unless a BDS lifetime history is ascertained.

Crossword: June puzzle solution

Crossword: June puzzle solution

Teacher-learner interaction quantifies scaffolding behaviour in imitation learning

Teachers often believe that they take into account learners’ ongoing learning progress in their teaching. Can behavioural data support this belief? To address this question, we investigated the interactive behavioural coordination between teachers and learners during imitation learning to solve a puzzle. The teacher manually demonstrated the puzzle solution to a learner who immediately imitated and learned it. Manual movements of teachers and learners were analysed using a bivariate autoregressive model. To identify bidirectional information exchange and information shared between the two agents, we calculated causality and noise covariance from the model. Information transfer observed from teacher to learner in the lateral component of their motion indicated imitation of the spatial information of the puzzle solution. Information transfer from learner to teacher in the vertical component of their motion indicated the monitoring process through which teachers adjust their timing of demonstration to the learner’s progress. The shared information in the lateral component increased as learning progressed, indicating the knowledge was shared between the two agents. Our findings demonstrated that the teacher interactively engaged in and contingently supported (i.e. scaffolded) imitation. We thus provide a behavioural signature of the teacher’s intention to promote learning indispensable for understanding the nature of teaching.

Crossword: May puzzle solution

Crossword: May puzzle solution

Penerapan Metode Steepest Ascent Hill Climb pada Permainan Puzzle

Puzzle is one example of the application of artificial intelligence, in the process of completion there are many search algorithms that can be applied. The 8 puzzle solution will be faster obtained if the array principle is used with a variation of the Steepest-Ascent Hill Climbing (Hill Climbing algorithm by choosing the sharpest / steepest slope) with the correct heuristic parameters and distance heuristics and combined with LogList as the storage state ever passed to overcome the problems in the hill climbing algorithm itself and avoid the looping state that has been passed. Steepest Ascent Hill Climbing is an algorithm method that is widely used for optimization problems. The application of the SAHC (Steepest Ascent Hill Climbing) Algorithm to the puzzle is needed so that the game is completed with optimal time.