Reviewerly/exHarmony huggingface dataset:
Students’ Performance in Writing English Exposition Text of the Eleventh Graders of SMAN 13 Jakarta

This article analyzed the understanding of eleventh graders' students at SMAN 13 Jakarta regarding the exposition text. The purpose of this paper was to find out to what extent the comprehension of eleventh graders of students of exposition text through the levels in the Blake Education rubric. The analysis table developed by Blake Education (1998) was used for the essay text analysis process. From the four main indicators studied, the results of this study indicated that (1) the average student was already at level 2, which could be categorized as an understanding of the exposition text; (2) although the average in both the Natural Sciences Program and Social Sciences Program was at level 2, the data showed that the students of Natural Science Program understood the exposition text better than the students of Social Science Program did. This paper also provided evidence regarding the difficulties of students in writing exposition texts. These findings showed that the ability of students to write exposition texts was in the middle or average level.&#x0D; &#x0D;
The quality of e-learning outcomes for money in Palestinian universities in light of international quality standards

The research aimed to identify the standards of quality for money, and the indicators that universities have followed to achieve the quality of infrastructure and software in e-learning. Data were collected using interviews (from January, 1 to August, 8) during the 2021/2022 academic year. The interviews included a number of questions within the quality-for-money standard. The study population consisted of e-learning departments in a number of Palestinian universities and 6 employees in e-learning departments participated in the research. The researchers adopted a qualitative-descriptive approach, and data analysis was conducted using inductive objective analysis. The results of the current study showed that the infrastructure that constitutes the core basis of e-learning has not reached a reasonable level in Palestinian universities due to obstacles beyond control; the results also showed that the Internet has become an essential partner for educational institutions in their educational function because the education sector is not isolated from the digital revolution that swept the world. Therefore, it is considered a long-term investment if it is linked to the sources of economic growth in any country. In order to achieve the goals of e-learning, improve it and apply it in the best way, it must be subject to the principles and quality standards through which the obstacles that prevent the achievement of its goals are identified.
A Security Algorithm for Images Based on 2D Logistic Map Using Bit-level and Pixel-level Image Encryption Approaches

This paper presents a new chaos-based image encryption method using a hybrid effect of bit-level and pixel-level image encryption principles to form an encrypted digital image.In the proposed encryption scheme, the 2D logistic map generates two pseudo-random chaotic streams that are employed in an efficacious way to use the bit-level and pixel-level ideologies to encrypt the plain image.The two chaotic sequences produced by the 2D logistic map are used to create two LSB-based bit-matrices to form a bit-level perspective that helps in the scrambling of the image.Furthermore, the same two chaotic streams of the 2D logistic map are used in a cross manner at the pixel level to diffuse the image and finally form a strong cipher image.The experimental numerical results, standard reference value tests, and comparative analysis with the existing encryption methods support and validate the reliability and robustness of the proposed encryption approach.
A Segmentation based Classification Model for Primary User Detection Using Deep Learning Techniques

Designing wireless communication systems with an aim to improve the utilization of the existing frequency bands involves the novel idea of cognitive radio (CR).CR allows sharing of licensed spectral band of primary users (PU) with the secondary users (SU) if and only if the licensed user is not subject to harmful interference.To sense the availability of PU spectrum, spectrum sensing is employed as a primary task of CR.Traditional signal processing techniques for spectrum sensing have the problem of false alarm or missed detection and may cause interference to PU.Thus, to further expand the ability of learning for CRs and to support an efficient PU sensing, artificial intelligence, machine learning or deep learning techniques can be applied.This paper proposes an efficient and well performing segmentation cum classification algorithm based on deep learning techniques for PU sensing.The spectrogram of the PU's transmission signal pattern for different scenarios was classified using Res-Net 50 model.To further improve the accuracy, a region proposal-based Res-Net50 model is proposed.The performance evaluations validate the effectiveness of the proposed model.
Workshop On Open Citations And Open Scholarly Metadata 2020 talk

I'm giving a short talk at the Workshop On Open Citations And Open Scholarly Metadata 2020, which will be held online on September 9th.
Chapter 10. Impact of word alignment on word translation entropy and other metrics

Many of the findings from studies using the Center for Research and Innovation in Translation and Translation Technology (CRITT) Translation Process Research Database (TPR-DB) framework rely on word(s)-to-word(s) alignments of the source text and target text. However, little research has been done on the impacts different alignment methods have on these findings. This study compares two different manual word alignment methods and four automatic word alignment methods on the basis of one English-Spanish TPR-DB study that has been used extensively (the BML12 dataset). We replicate past findings from the BML12 dataset using these different alignments in order to determine the impact of alignment, and we present qualitative/quantitative analyses of the different word-alignment methods.
Shotgun Semantics

Developers often resort to shotgun parsing: scattering data checks and fallback values in various places throughout the system’s main logic.1 The habit of scattering parser-like behaviour throughout an application’s code and the resulting inconsistencies in data handling can often lead not just to annoying complications and bugs, but also security vulnerabilities.2 This is about reading data. What about when writing data, when setting the foundations for how it will ultimately...
Tracking and using heart rate data in live performance: reflections on ‘The Hairs of Your Head Are Numbered’

Click to increase image sizeClick to decrease image size Disclosure statementNo potential conflict of interest was reported by the author.Additional informationNotes on contributorsChris KondekChris Kondek has been making video for theater for over 25 years. He started in New York in the beginning of the 90's creating video for the multimedia performance company The Wooster Group. In the middle of the 90's he started a long collaboration with Laurie Anderson co-creating visuals for and touring with her performance pieces “Stories from the Nerve Bible” and “Songs and Stories from Moby Dick”. In the end of 90's he created video for the New York multimedia performance group, “The Builder's Association”. In 1999 Chris Kondek re-located to Berlin where he has been continually active in the German Theater and Opera scene.Starting in 2003, working with longtime collaborator Christiane Kuehl, Chris Kondek has been making theater works in the independent scene. The first work “Dead Cat Bounce” created in 2004 used the audience's money to trade stocks live during the performance on the New York Stock exchange. This piece, along with the follow up work “Money: It Came from Outer Space” 2007 were both invited to the “Festival Politik im Freien Theater.” Both works were awarded the jury prize of the Goethe institute.In 2014 Kondek and Kuehl re-branded forming the multimedia/multi format artist group doublelucky productions. doublelucky concentrates on creating works that put focus on current technological trends in society in order to make visible our invisible digital infrastructures.Most recently Kondek and doublelucky productions have been investigating the use of Augmented Reality to question the meaning of “real” experience in our digital world.
Experimental Proposal for Validation of W-state Protocol for Qubits and Qudits

This paper presents an experimental scheme to validate W-state encoding, a passive linear optics error-correction scheme for qubits and qudits. We use the orbital angular momentum of photons to realize qubits and qudits.
The Effect of Economic Factors on Property Crime Rates

This research is motivated because the number of property crimes on the island of Sumatera is the highest in Indonesia during the 2014-2019 period. This study aims to examine the economic factors that influence property crime on the island of Sumatera. The type of data used is secondary data. The type of data used is panel data which is a combination of cross-section data from 10 provinces on the island of Sumatera and time series data for 2014-2019. The analytical method used is panel data regression analysis. The best model chosen is the Fixed Effect Model (FEM). The results of this study indicate that GRDP growth and unemployment have no significant effect, while poverty, income inequality, and per capita expenditure have a significant positive effect on property crime. The value of R2 is 0.9521, meaning that the independent variable can explain the dependent variable by 95.21%.&#x0D; Penelitian ini dilatarbelakangi karena jumlah kejahatan harta benda di Pulau Sumatera terbanyak di Indonesia selama periode 2014-2019. Penelitian ini bertujuan untuk meneliti faktor-faktor ekonomi yang mempengaruhi kejahatan harta benda di Pulau Sumatera. Jenis data yang digunakan adalah data sekunder. Tipe data yang digunakan adalah data panel yang merupakan kombinasi data cross section 10 Provinsi di Pulau Sumatera dan data time series tahun 2014-2019. Metode analisis yang digunakan adalah analisis regresi data panel. Model terbaik yang terpilih adalah Fixed Effect Model (FEM). Hasil penelitian ini menunjukkan bahwa Pertumbuhan PDRB dan pengangguran tidak berpengaruh signifikan, sedangkan kemiskinan, ketimpangan pendapatan dan pengeluaran per kapita berpengaruh positif signifikan terhadap kejahatan harta benda. Nilai R2 sebesar 0,9521, artinya variabel independen dapat menjelaskan variabel dependen sebesar 95,21%.
Conceptual Palettes as Sites of Creative Negotiation in Leah Asher’s TRAPPIST-1

In this paper, I consider the creation and performance of Leah Asher’s TRAPPIST-1 (2017), a solo piano work in graphic notation that I commissioned and premiered. Musical works that utilize open notations often have a complex relationship to the work-concept and, in turn, an elusive ontology. I consider the role of conceptual palettes as significant sites in the creative process where ontological boundaries are delineated. I analyze four sites in the creation of TRAPPIST-1—from project proposal to premiere performance—where conceptual palettes play a dynamic role in narrowing, restricting, and guiding the identity of the work. Using Jakobson’s notion of the poetic function and Harkness’s concept of qualic transitivity, I show that conceptual palettes facilitate performance as highly cu­rated acts of translation not just of open notations but also of intangible concepts.
Classification of Malicious URLs Using Naive Bayes and Genetic Algorithm

The financial losses of vulnerable and insecure websites are increasing day by day. The proposed system in this research presents a strategy based on factor analysis of website categories and accurate identification of unknown information to classify safe and dangerous websites and protect users from the previous one. Probability calculations based on Naive Bayes and other powerful approaches are used throughout the website classification procedure to evaluate and train the website classification model. According to our study, the Naive Bayes approach was benign and showed successful results compared to other tests. This strategy is best optimized to solve the problem of distinguishing secure websites from unsafe ones. The vulnerability data categorization training model included in this datasheet had a better degree of precision. In this study, the best accuracy probability of 96% was achieved in Naive Bayes' NSL-KDD data set categorization
Towards Continuous Fiber Birefringence Compensation with Single-Photon-Level Light

We propose a method for continuously compensating for the polarization state change of photons propagating in fibers. This technique operates at a single-photon-level intensity and therefore imposes minimal noise on the quantum channel.
Hybrid Quantum-Classical Computing - A Fusion of Classical And Quantum Computational Substrates

Through harnessing quantum mechanical phenomena, quantum computing substrates yields the promise of transcending new frontiers in confronting the world’s most intractable computational challenges requiring exponential computational power that exceeds that of today’s most powerful super-computers. The choreography of such quantum mechanical phenomena has catalysed accelerated advances in the emergence of a quantum computational substrate paradigm that yields the potential to solve some of humanities most complex problems through quantum speedup: in environment, agriculture, health, energy, climate, materials science, precision medicine, autonomous vehicles in smart cities, renewable energy and problems humanity has not yet even imagined. However, the manifestation of a practical quantum advantage across several of these areas is unlikely through the exclusive application of a quantum computational substrate. Quantum computational substrates will not replace classical computational substrates, instead, both technologies will synergistically complement each other where quantum computational substrate accelerators functions as a specialised co-processor to a classical computational substrate in computing workloads best suited for the quantum computer, in a heterogenous computational substrate ecosystem comprising other accelerators. This paper reviewed novel new frontiers at the fusion of quantum-classical computational substrates, and findings reveal that practical applications and research remain limited. The opportunity exists, in considering a heterogenous computational substrate ecosystem comprising other accelerators, for practical quantum advantage across a broader set of complex problem domains to be realised sooner.
GAPS IN A SUMSET OF A POLYNOMIAL WITH ITSELF

In this note, we give some lower and upper bounds for the gaps between consecutive elements of an integer sequence whose elements are expressible in the form P(m) + P(n), where P is a degree d polynomial with integer coefficients, and m, n are nonnegative
Prediction of Heavy Metals Values for South-East of Baghdad Study Area

Soil, water and air are the main components of the environment. The presence of old and modern factories that emit pollutant materials such as steam and smoke polluting the air and soil, as well as dumping solid and liquid wastes for these industries on the lands and in the adjacent water channels, and all these pollutants will negatively affect the environment surrounding the industrial sites. The factories are located south-east of the capital, Baghdad. This study aims to estimate the damage and seriousness of heavy metals pollution in the soil surrounding these factories. Soil samples are taken at three depths (0-10) (10-30) (30-50) cm with nine different sites. The necessary tests are carried out to find the concentrations of heavy metals such as copper (Cu), iron (Fe), cadmium (Cd), nickel (Ni), zinc (Zn), and lead (Pb), as well as phosphate (PO4) and PH. These tests values can be used in statistical program to obtain the analysis of variance tables for a significant level less than 0.05 in f-test. The least square difference method is used to find the significant difference among tests in one layer. The results show that, the second layer of soil is the worst where Mean square error is 24.432 with Mean Absolut error is 1.164 and Mean Absolut percentage error is 96.21. Using Minitab program to predict heavy metal values for the second layer and these values are not exceeding the permissible limits. In this study, the concentrations of heavy metals for the second layer of soil and for the nine sites starting from the first site are as follows Pb (3.05-11) mg/kg prediction values to Pb (3.15-17.35) mg/kg. Concentration of Cd (0.05-0.2) mg/kg while prediction values of Cd (0.09-0.31) mg/kg. Concentrations of Ni in second layer of soil (3-35) mg/kg; Prediction values Ni (4.41-37.08) mg/kg. Zn concentrations (0.6-22.5) mg/kg; Prediction concentration Zn (0.9-24.1) mg/kg. Concentrations Cu (0.35-8.55) mg/kg while predictions Cu (0.62-10.21) mg/kg. Concentrations of Fe (2.8-7.1) mg/kg. Prediction concentrations Fe (3.61-9.22) mg/kg. The benefits of prediction concentration of heavy metals in soil is crucial to finding solutions to contaminated soil in simple ways with primary treatment and acceptable measures for recycle waste factories. Loss of food security in the event of aggravated soil contamination with heavy metals.
Analyzing the syntax and salience of causal links embedded within semantic links in concept maps: Implications for temporal flow and learning transfer

Including causal links in concept maps enables learners to meaningfully relate concepts to a larger context or problem in terms of how and where concepts apply within the chains of causal events that lead to a given goal or outcome. Given that higher quality maps are produced when students link and sequence events to flow temporally and sequentially in a consistent direction towards a target outcome in a map, it is highly plausible that students can improve learning transfer (the ability to apply concepts to diagnose and solve problems) by including and making more salient the sequences of causal links nestled in the semantic links in concept maps. To lay the groundwork to empirically test this proposition in future research, this study: 1) analyzes 16 concept maps presented in the Proceedings of the 8th Int. Conference on Concept Mapping to codify the diverse and sometimes incongruent syntaxes used to convey causal relationships; 2) examines how the causal link syntaxes combined with semantic links work jointly (or against each other) to create temporal flow; and 3) explore how causal and semantic links can be integrated to increase the saliency and quality of the causal networks connecting concepts to outcomes. A better understanding of how causal links are expressed, integrated, and made more salient in concept maps can reveal ways to help students create concept maps that are more accurate, meaningful, and effective in improving the ability to apply concepts to solve complex problems.
IDENTIFIKASI STATUS PERLINDUNGAN ANAK MENGGUNAKAN ALGORITMA KLASIFIKASI K-NEAREST NEIGHBORS

The United Nations Children's Fund (UNICEF) has defined the child protection system as “certain formal and informal structures, functions and capacities that have been pooled to prevent and respond to violence, abuse, neglect and exploitation of children”. Problems identified by the Sulawesi Community Foundation group (CSF) is the absence of digital records that accommodate the results of direct interviews with children in terms of measuring experiences or actions that have been experienced by a child as a source of information that can be used for decision-making needs. The KNN algorithm is one of the most popular data mining algorithms. It has been widely and successfully applied to data analysis applications across various research topics in computer science. Based on the value of Classification Y, obtained as much as 1 data Category = Unprotected, and 3 data Category = Protected, then the resulting decision is that the identification of child protection status in an area is based on attribute values ​​X1=5, X2=3, X3=50 and X4 = Does not result in a decision that the majority of children have guaranteed protection status. The decisions made are in accordance with the facts, therefore the Sulawesi Community Foundation NGO can apply the results of analysis and testing into an integrated system so that it can become a valid source of information in digital format.
Job autonomy, organizational citizenship behavior through affective commitment, and intrinsic motivation of employees in universities in Ho Chi Minh City

The study examines the impact of job autonomy on organizational citizenship behavior through the perception of affective commitment, and intrinsic motivation of administrative staff at universities in Ho Chi Minh City. Job autonomy is considered simultaneously by three aspects: autonomy in planning, autonomy in working methods, and autonomy in making decisions. Partial Least Squares Structural Equation Modeling (PLS-SEM) was applied with 300 observed samples. Research results show that the hypotheses are consistent with reality. Research has shown that job autonomy by the three aspects mentioned above has a positive influence on organizational citizenship behavior through mediating factors such as: affective commitment and intrinsic motivation. Specifically: Of the three job autonomy aspects, autonomy in planning has the strongest impact on affective commitment; autonomy in the method of most positive impact on intrinsic motivation; and affective commitment has the strongest impact on organizational citizenship behavior. Job autonomy has an important meaning in human resource management, affecting the emotions, motivation and organizational citizenship behavior of employees. Then, The study discussed the theoretical implications and proposal to managerial implications for universities in Vietnam.
Exploiting the Potential of Seq2Seq Models as Robust Few-Shot Learners

In-context learning, which offers substantial advantages over fine-tuning, is predominantly observed in decoder-only models, while encoder-decoder (i.e., seq2seq) models excel in methods that rely on weight updates. Recently, a few studies have demonstrated the feasibility of few-shot learning with seq2seq models; however, this has been limited to tasks that align well with the seq2seq architecture, such as summarization and translation. Inspired by these initial studies, we provide a first-ever extensive experiment comparing the in-context few-shot learning capabilities of decoder-only and encoder-decoder models on a broad range of tasks. Furthermore, we propose two methods to more effectively elicit in-context learning ability in seq2seq models: objective-aligned prompting and a fusion-based approach. Remarkably, our approach outperforms a decoder-only model that is six times larger and exhibits significant performance improvements compared to conventional seq2seq models across a variety of settings. We posit that, with the right configuration and prompt design, seq2seq models can be highly effective few-shot learners for a wide spectrum of applications.