Reviewerly/exHarmony huggingface dataset:
Neutral Electron (e°) or Neutrino (ν): e° ≡ ν

In order to solve the Neutron decay mass gap problem, Pauli proposed a precise solution. The brilliant idea of a 3rd particle came to Pauli (fully shared by Fermi) to compensate the energy-mass gap that emerged from the disintegration of the neutron, or negative b decay (bd-): N&amp;reg; P + e-.&#x0D; &#x0D; The basic requirements originally requested by Pauli and Fermi for the new particle, later called neutrino, are essentially three: it is electrically neutral and it must have the same mass and spin of an electron. Hence, if the mass of the neutrino (n) corresponded to that assumed by Pauli and Fermi, the &amp;beta;d- mass gap problem would be brilliantly solved.&#x0D; &#x0D; However, the current upper limits of the mass of the n are &amp;lt; 2eV.&#x0D; &#x0D; Here we show that a clear incongruity comes out: the mass attributed to the n will never be able to solve the energy gap problem of the &amp;beta;d- : it takes ≃ 250,000 n to compensate the energy-mass gap. &#x0D; &#x0D; Unless we consider, instead of n, another particle, probably still unknown, as the 3rd particle of &amp;beta;d-. To find a solution, we hypothesized the existence of an electron with no electric charge: a neutral electron (e&amp;deg;).
A Novel Framework for Image Encryption by Integrating Modified Moth Flame Optimization and Logistic Chaotic Map for Enhanced Security

Abstract Preserving the confidentiality of sensitive image data is of paramount importance in the digital world. Therefore, an optimized image encryption algorithm is proposed in this paper for securing image-based communication. The proposed Modified Moth Flame Optimization Algorithm (MMFO) delved along with a Logistic Chaotic Map is used to obtain improved values of evaluation parameters such as Correlation Coefficient(CC), Image Entropy (IE), Unified Average Changing Intensity (UACI) and Normalized Pixel Change Rate (NPCR) along with Uniform Histograms for the encrypted image that outperforms various state-of-the-art metaheuristic algorithms coupled with diverse chaotic maps. Using multiple plain image-dependent session keys and a Logistic Chaotic map, several encrypted images are generated which act as an initial population for the Modified algorithm. The results are presented to validate the performance of the proposed algorithm. It has been observed that the proposed algorithm has a substantial de-correlation of adjacent pixels in the encrypted image, achieving values on the order of 10 −6 .
DEThresh: Enhancing Cloud Computing Performance with Differential Evolution-Driven Datacenter Selection and Threshold-based Load Balancing Optimization

Abstract The advent of cloud computing has introduced a novel paradigm in user services, enabling on-demand access to information technology services, irrespective of time and location, with a pay-per-use model. Meeting user expectations necessitates cloud service providers to furnish an infrastructure that is efficient, reliable, and resilient to faults. Addressing the substantial volume of user requests, selecting cloud datacenters and load balancing strategies become pivotal for delivering real-time services economically and selecting appropriate datacenters and virtual machines. This research introduces DEThresh, combining a smart differential evolution-based datacenter selection method with a threshold-based load balancing mechanism aimed at enhancing resource management by focusing on cost and performance considerations. The differential evolution-based datacenter selection employs evolutionary operations to identify the most suitable DC for the userbase. Simultaneously, threshold-based load balancing ensures the reasonable distribution of tasks and optimal resource utilization, preventing task overload on virtual machines and underutilization due to task scarcity. Simulation results demonstrate that the proposed DEThresh algorithm exhibits superior response and data processing time compared to well-established popular algorithms currently in use, especially under varying userbase and datacenter conditions. Impressively, DEThresh achieves this even with fewer datacenters, ultimately reducing cloud service costs.
Programmatic Data Analyst Continuous Process Improvement (CPI) Tracking within the Sarah Cannon Transplant and Cellular Therapy Network (SCTCTN)

The SCTCTN is compromised of 7 blood cancer and cellular therapy programs that collectively performed over 1600 transplant and cellular therapies in 2022. Making the SCTCTN the largest network in the United States. In September 2022, the SCTCTN began tracking the CPI status of each program with the goal of strategizing programmatic form completion, aimed at maximizing resource utilization for CPI planning. The CPI report represents forms that are due and their priority. Develop a CPI tracking model that shows weekly progress for autologous (auto) and allogeneic (allo) forms completed, due, and overdue forms to inform and drive CPI work efforts (CAR-T forms are included in the autologous patient population). Captured the weekly form completion per program in excel pivot tables, differentiating between auto and allo infusions. Each tab represents a week of the current CPI trimester forms completed (Figure 1). Next, captured all forms completed per program since the beginning of the trimester per program. Similarly, captured all due and overdue forms to complete the CPI tracking table with the programmatic specific information (Figure 2). Each program is classified in either “Due/Overdue”, or “Real-Time” status. The percentages show the completion per trimester, depending on how they are classified. For those that are abstracting in real-time, percentages show “Real-Time” form completion. For those not abstracting in real-time, percentages show “Due/Overdue” form completion. Communications were tailored to inform the needs of each program. Weekly meetings established expectations. The discussions were generally comprised of: forms completed the prior week, prioritization of efforts towards CPI (queries, critical forms, all other forms, study forms, CTA, CVDR, etc.) and a plan for upcoming weeks. Using the CPI tracking model assisted with holding programs accountable for their CPI requirements, and revealed when teams had specific challenges like: emergent time sensitive requests, data workflow flaws, source documentation incompleteness, among others. Additionally, it gave transparency to the work distribution and assisted ensuring that each data analyst works at the top of their capabilities utilizing their diverse strengths and talents, whilst improving on any weaknesses. This model has allowed for direct feedback to the data analysts. It highlights those that are performing well and gives insight into those that experiencing challenges. Lastly, this practice also helped programs find their optimal work pace and promoted more cohesive team work.
Predicting Agent Behavior over Repeated Trials

Agents act on an important part of an individual’s environment. An increasing amount of these agents are machines and software. In a cooperative setting, each individual needs to understand the partners’ intentions and corresponding actions to plan their own actions adequately. Misunderstandings have negative effects and diminish the efficiency of cooperation. We created a game-based experiment to study the effects of understanding a partner’s actions in a cooperative setting. In this game, the players are dependent on the ability of the other to make good decisions in the game to succeed. In two studies (N = 87, N = 281), we collected data on the understanding of an artificial agent, operationalized as the ability to predict its actions and the skill at the task itself. The participants improve at predicting the agent’s actions and at their subtask in the game over time. Following a misunderstanding, the participants’ performance at their subtask was worse, as measured by the quality, the speed, and the efficiency of their actions. Results of Study 2 suggest that the improvements in predicting the agent’s actions are likely the result of an improved understanding of the game rather than an improved understanding of the agent.
Analysis of Engineering Undergraduates’ Confidence with Hands-on Tasks – Preparation for Collaborative Manufacturing Environments in the Era of Industry 4.0

Abstract Many engineering students are expected to become skilled and experienced in solving practical hands-on projects before they graduate. For students without formal engineering experiences (co-ops, internships, full/part-time jobs) this is often achieved through courses such as capstone design, cornerstone design, and in labs. The need for engineers with hands-on exposure will only increase as we experience a revitalization of manufacturing in the United States and the emergence of Industry 4.0. However, we currently do not know students' hands-on ability as it varies between majors and students in the context of Industry 4.0. To address this, a survey of engineering students who are interested in manufacturing is necessary to assess their readiness for hands-on projects in manufacturing settings. This paper presented an analysis of engineering students' perception towards hands-on tasks in manufacturing environments. In a study with students who expressed interest in manufacturing, we collect qualitative interview data from 30 students across four engineering majors. We compare students' majors, perceptions, experience, and the courses they completed related to hands-on projects. The results suggest that many students did not feel prepared or confident to work in manufacturing environments in preparation for Industry 4.0. Further, students formal engineering experiences contributed more to their confidence in hands-on projects than curricular experiences.
Summary-Sentence Level Hierarchical Supervision for Re-Ranking Model of Two-Stage Abstractive Summarization Framework

Fine-tuning a pre-trained sequence-to-sequence-based language model has significantly advanced the field of abstractive summarization. However, the early models of abstractive summarization were limited by the gap between training and inference, and they did not fully utilize the potential of the language model. Recent studies have introduced a two-stage framework that allows the second-stage model to re-rank the candidate summary generated by the first-stage model, to resolve these limitations. In this study, we point out that the supervision method performed in the existing re-ranking model of the two-stage abstractive summarization framework cannot learn detailed and complex information of the data. In addition, we present the problem of positional bias in the existing encoder–decoder-based re-ranking model. To address these two limitations, this study proposes a hierarchical supervision method that jointly performs summary and sentence-level supervision. For sentence-level supervision, we designed two sentence-level loss functions: intra- and inter-intra-sentence ranking losses. Compared to the existing abstractive summarization model, the proposed method exhibited a performance improvement for both the CNN/DM and XSum datasets. The proposed model outperformed the baseline model under a few-shot setting.
Implementasi Algoritma C4.5 Untuk Mengukur Tingkat Kepuasan Mahasiswa yang Berlangganan Wifi Indihome

The urgency of research on satisfaction levels is closely related to the success and desires of a business or organization. Without a good understanding of customer satisfaction, a company or organization may lose market share, face declining sales, or even face failure. Therefore, this research must be carried out regularly and continuously. The purpose of this research is to determine the level of customer satisfaction and to determine the dominant service quality that influences the quality of service provided by PT Telkom Indihome to customers. In this research, researchers used the C4.5 Algorithm data mining technique. The research data source used was by making observations and distributing questionnaires to customers of PT Telkom Pematangsiantar City. In this case, researchers used assessment attributes, namely service quality, accessibility and product quality. This research is expected to provide information and input to PT Telkom Indihome in the form of evaluations in improving network quality. The results of the research conducted by the author obtained the following conclusion, namely that Data Mining with the C4.5 Algorithm can classify the measurement of satisfaction levels of STIKOM Tunas Bangsa students who subscribe to Indihome WiFi. The accuracy results obtained by this research were 75.00% with the average student who subscribed to Indihome WiFi stating that they were satisfied.
Perbandingan Algoritma Decision Tree dan Support Vector Machine Dalam Pemilihan Calon Mahasiswa Penerima KIP-K

KIP Kuliah is tuition assistance from the government for high school / equivalent graduates who have good academic potential but have economic limitations. There are many things that should be considered by universities before selecting prospective students who receive KIP Lecture so that selection can be done using machine learning and classification algorithms. In this research, two machine learning algorithms will be used including: Decision Tree and Support Vector Machine (SVM). Furthermore, these two algorithms will be tested and compared the final results. Both algorithms have different results. The highest level of accuracy, precision, recall, and F1 score is 100%. This value can be achieved by the Decision Tree algorithm because the dataset used is suitable for it to solve. Therefore, the Decision Tree algorithm is recommended to be used in selecting KIP College student candidates.
Is it Possible to use Artificial Intelligence Technology in Judicial Protection of Copyright and Related Rights?

Digital technologies penetrate into many spheres of human activity. The accumulation of a large amount of information in digital form has given impetus to the development of technologies for its processing and analysis, including through artificial intelligence technology. Technical solutions are being created using artificial intelligence and for use in judicial activities. The introduction of digital technologies gives rise to additional questions and risks associated with the objectivity of the result, its fairness. It seems that the use of digital technologies can be initially tested on certain categories of cases and procedural actions.
On Development of English Reading Teaching in China: A Literature Review (2003-2023)

Reading is the foundation of mastering a language as well as a primary instrument to obtain information. Reading teaching has always been a hot topic in English language teaching (ELT). The present study sought to trace the characteristics of existing studies on English reading teaching in China. Based on research articles in the CNKI database collected by Chinese core journals and CSSCI in the past two decades, 603 studies on English reading teaching were selected and analyzed. Firstly, the Cite Space software is used to visualize the annual number of published papers, research hotspots and research trends. Subsequently, a detailed content analysis was conducted to distil and summarise the predominant research foci in English reading instruction in China over the past twenty years. The results show that the number of published papers on reading teaching research in China increases first and then fluctuates. The evolution of research topics is discerned to encompass three distinct stages and was influenced by prevailing educational policies. The research foci mainly include three aspects: English reading teaching modes, English reading teaching strategies and English reading ability. This comprehensive review aims to map out the current research landscape, shedding light on future scholarly inquiry in English reading teaching
Comparative Analysis of Chinese Language Proficiency Assessment: A Case Study of AP and IGCSE Examinations

With the growing global interest in learning Chinese, the proliferation of Chinese language exams by various institutions has become evident. This paper delves into a comparative analysis of the assessment systems of the College Board's AP Chinese Language and Culture Examination and the Cambridge IGCSE Chinese Examination across five dimensions: score categorization, paper composition, assessment methods, exam syllabus arrangement, and evaluation principles. The study aims to identify similarities and differences between the two exams and draw insights for language testing and assessment practices. The findings reveal that both exams provide valuable educational experiences and insights. Recommendations include refining assessment systems to comprehensively evaluate candidates' language proficiency, integrating cultural elements into examination materials, and leveraging modern technological means to enhance fairness in language testing and assessment processes.
IMPROVEMENT OF DATABASE PROTECTION SYSTEM FROM UNAUTHORIZED MODIFICATION BASED ON BLOCKCHAIN TECHNOLOGY AND PROOF-OF-WORK CONSENSUS ALGORITHM

In today's digital world, there is an active use of databases, and the relevance of protecting them is growing every day. After all, databases can contain a wide range of confidential information (personal, financial, government, commercial, etc.), unauthorized access to which will lead to irreversible negative consequences, including material damage, reputational losses, and even legal problems. In addition, the number and complexity of cyberattacks is growing every day. Attackers use various methods to gain unauthorized access to databases, such as the use of software vulnerabilities, social engineering methods, brute force attacks, etc. Therefore, the problem of increasing the security of databases against unauthorized modification is of great importance. In this regard, this paper proposes to address this issue by using blockchain technology in combination with the Proof-Of-Work consensus algorithm, which ensures the security and integrity of the system, and helps prevent fraud and abuse by using cryptographic methods to protect the blockchain from unauthorized access and modification. It is also worth noting that the Proof-of-Work algorithm has a number of other advantages, such as decentralization, transparency, and data immutability after it is added. Thus, to achieve the goal, the subject area was analyzed, the known methods on which the operation of database security systems is based were investigated, the architecture and algorithm of the security module were created, which allows for decentralized data storage and, accordingly, increases the level of their security by using a special consensus protocol to coordinate the contents of the registry, as well as cryptographic hashing algorithms and electronic digital signatures to ensure the integrity of the parameter transfer transaction.
A Privacy-Enhanced Scheme Within The Public Key Infrastructure For The Internet Of Things, Employing Elliptic Curve Diffie-Hellman (ECDH)

The Public Key Infrastructure (PKI) serves as the foundation for online security, particularly within the realm of the Internet of Things (IoT). It operates based on certified public keys that remain permanent but can be revoked when necessary, such as in the case of a change in ownership, compromise of the private key, or malicious activities. Although this method ensures secure key utilization with traceability, it also introduces a potential privacy risk due to the traceability and utilization of identity-based certificates. This approach is considered an innovative strategy for ensuring user confidentiality, integrity, authentication, and privacy in the context of the Internet of Things. The proposed solution integrates elliptic curves (ECDH) and traditional PKI to safeguard user privacy. It introduces two types of elliptic curve keys: long-term identity-based certified keys and dynamically generated temporary anonymous aliases. These aliases are seamlessly recorded by the certification authority, which maintains distinct directories for long-term and temporary keys. This dual-key approach enhances security while addressing the specific requirements of the Internet of Things.
DESIGN OF SPACE TIME TRELLIS CODED OFDM

Space Time Trellis Code (STTC) is a technique that can be used to improve the performance ofthe Orthogonal Frequency Division Multiplexing (OFDM) system over wireless channels byproviding both coding gain and diversity gain. STTC is combined from two codes, Trellis CodeModulation (TCM) as an inner code and Space Time Block Code (STBC) as an outer code. TCMwhich combines the choice of a modulation scheme with that of a convolutional code provides thecoding gain, and the other code provides the diversity gain. Simulation is done over flat fading andfrequency selective Rayleigh fading channel for Eight Phase Shift Keying (8-PSK) TCM. It foundthat the best results are obtained for the case of two transmitters and three receivers which have again of about 18dB over that without STBC.
Near-squares in binary recurrence sequences

International Journal of Number TheoryAccepted Papers Free AccessNear-squares in binary recurrence sequencesNikos Tzanakis and Paul VoutierNikos Tzanakis and Paul Voutier Search for more papers by this author https://doi.org/10.1142/S1793042124500787Cited by:0 (Source: Crossref) PreviousNext AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail Remember to check out the Most Cited Articles! Check out new Number Theory books in our Mathematics 2021 catalogue FiguresReferencesRelatedDetails Recommended Accepted Papers Metrics History Received 21 September 2022 Accepted 31 October 2023 PDF download
Piercing All Translates of a Set of Axis-Parallel Rectangles

For a given shape $S$ in the plane, one can ask what is the lowest possible density of a point set $P$ that pierces ("intersects", "hits") all translates of $S$. This is equivalent to determining the covering density of $S$ and as such is well studied. Here we study the analogous question for families of shapes where the connection to covering is altered. That is, we require that a single point set $P$ simultaneously pierces each translate of each shape from some family $\mathcal{F}$. We denote the lowest possible density of such an $\mathcal{F}$-piercing point set by $\pi_T(\mathcal{F})$. Specifically, we focus on families $\mathcal{F}$ consisting of axis-parallel rectangles. When $|\mathcal{F}|=2$ we exactly solve the case when one rectangle is more squarish than $2\times 1$, and give bounds (within $10\,\%$ of each other) for the remaining case when one rectangle is wide and the other one is tall. When $|\mathcal{F}|\ge 2$ we present a linear-time constant-factor approximation algorithm for computing $\pi_T(\mathcal{F})$ (with ratio $1.895$).