Reviewerly/exHarmony huggingface dataset:
Multiscale Anchor-Free Region Proposal Network for Pedestrian Detection

Pedestrian detection based on visual sensors has made significant progress, in which region proposal is the key step. There are two mainstream methods to generate region proposals: anchor-based and anchor-free. However, anchor-based methods need more hyperparameters related to anchors for training compared with anchor-free methods. In this paper, we propose a novel multiscale anchor-free (MSAF) region proposal network to obtain proposals, especially for small-scale pedestrians. It usually has several branches to predict proposals and assigns ground truth according to the height of pedestrian. Each branch consists of two components: one is feature extraction, and the other is detection head. Adapted channel feature fusion (ACFF) is proposed to select features at different levels of the backbone to effectively extract features. The detection head is used to predict the pedestrian center location, center offsets, and height to get bounding boxes. With our classifier, the detection performance can be further improved, especially for small-scale pedestrians. The experiments on the Caltech and CityPersons demonstrate that the MSAF can significantly boost the pedestrian detection performance and the log-average miss rate (MR) on the reasonable setting is 3.97% and 9.5%, respectively. If proposals are reclassified with our classifier, MR is 3.38% and 8.4%. The detection performance can be further improved, especially for small-scale pedestrians.
Analysis of The Effect of Business Strategy on The Quality of Management Accounting Information Systems

Management accounting information system (SIAM) is used as a tool to produce financial and non-financial / management accounting information that is used to assist executive managers or internal parties in planning resource allocation, supervision, evaluation, and performance evaluation, both financial performance and non-financial performance including managerial performance and employee performance. Management accounting information systems refer to normative matters, but when management accounting information systems are implemented it has unexpected or unexpected consequences so that it can affect the satisfaction of users of information systems, this is because in the context of the organization and socially not well understood by users. This research was conducted on general insurance in Bandung where the respondents were operational managers using an explanatory survey method. Testing data using simple regression The results of research on insurance companies in Bandung found that business strategies affect the quality of management accounting information systems
VG4 Cipher: Digital Image Encryption Standard

When it comes to providing security to information systems, encryption emerges as an indispensable tool, as it has been used extensively in the past few decades for securing stationary data as well as data in motion.With the rapid data transmission techniques and multimedia options available for data representation, the field of information security has become very significant.The state-of-art cryptographic technique is DNA encryption, which uses biological principles for safeguarding data.The use of Bio-inspired ciphers is becoming the de-facto safety standard, especially for digital images as they are a key source of extracting crucial information.Hence, image encoding becomes of ultimate importance when there is a need to send them via an insecure communication channel.The purpose of this research paper is to present a DNA-inspired cryptosystem that can be employed in the domain of image encryption that provides superior security with enhanced efficiency.The experimental outcomes prove that this novel cryptographic algorithm not only provides better security but also at a reasonable pace.
“You’re the Puppet”

In primetime US political discourse, across liberal and conservative outlets alike, accusations of puppetry and ventriloquism proliferate. Despite invoking an anachronism, the ventriloquial metaphor furnishes a reliable means of discrediting presidential candidates and presidents-elect by conjuring the figure of the dummy who speaks in a voice not his own. At the same time, the presidential voice’s constant mediation invites material comparisons to the channeling of voices through dummy and human bodies practiced in stage ventriloquism. This chapter examines how technologies of the voice, from microphones to speech aids such as earpieces and teleprompters, have figured into popular framings of the last three US presidents as speaking puppets, arguing that bipartisan charges of ventriloquism reflect twinned national-cultural anxieties about the voice’s constitutive mediation and power’s constitutive decentralization in late capitalism. Through analyses of liberal speculations about George W. Bush’s use of listening devices, conservative claims about Barack Obama’s dependence on teleprompters, and bipartisan responses to Donald Trump’s self-presentation as a leader whose mediated voice remains perpetually unfiltered, the chapter proposes a new theory of the politics of voice that acknowledges the voice’s technicity and power’s distribution.
Contextual Domain Classification with Temporal Representations

Tzu-Hsiang Lin, Yipeng Shi, Chentao Ye, Yang Fan, Weitong Ruan, Emre Barut, Wael Hamza, Chengwei Su. Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Papers. 2021.
Comparison of Bagging Ensemble Combination Rules for Imbalanced Text Sentiment Analysis

The wealth of opinions expressed by users on micro-blogging sites can be beneficial for product manufacturers of service providers, as they can gain insights about certain aspects of their products or services. The most common approach for analyzing text opinion is using machine learning. However. opinion data are often imbalanced, e.g. the number of positive sentiments heavily outnumbered the negative sentiments. Ensemble technique, which combines multiple classification algorithms to make decisions, can be used to tackle imbalanced data to learn from multiple balanced datasets. The decision of ensemble is obtained by combining the decisions of individual classifiers using a certain rule. Therefore, rule selection is an important factor in ensemble design. This research aims to investigate the best decision combination rule for imbalanced text data. Multinomial NaÃ¯ve Bayes, Complement NaÃ¯ve Bayes, Support Vector Machine, and Softmax Regression are used for base classifiers, and max, min, product, sum, vote, and meta-classifier rules are considered for decision combination. The experiment is done on several Twitter datasets. From the experimental results, it is found that the Softmax Regression ensemble with meta-classifier combination rule performs the best in all except in one dataset. However, it is also found that the training of the Softmax Regression ensemble requires intensive computational resources.
INFORMATION IN PROPOSITIONAL PROOFS AND ALGORITHMIC PROOF SEARCH

Abstract We study from the proof complexity perspective the (informal) proof search problem (cf. [17, Sections 1.5 and 21.5]): • Is there an optimal way to search for propositional proofs? We note that, as a consequence of Levin’s universal search, for any fixed proof system there exists a time-optimal proof search algorithm. Using classical proof complexity results about reflection principles we prove that a time-optimal proof search algorithm exists without restricting proof systems iff a p-optimal proof system exists. To characterize precisely the time proof search algorithms need for individual formulas we introduce a new proof complexity measure based on algorithmic information concepts. In particular, to a proof system P we attach information - efficiency function $i_P(\tau )$ assigning to a tautology a natural number, and we show that: • $i_P(\tau )$ characterizes time any P -proof search algorithm has to use on $\tau $ , • for a fixed P there is such an information-optimal algorithm (informally: it finds proofs of minimal information content), • a proof system is information-efficiency optimal (its information-efficiency function is minimal up to a multiplicative constant) iff it is p-optimal, • for non-automatizable systems P there are formulas $\tau $ with short proofs but having large information measure $i_P(\tau )$ . We isolate and motivate the problem to establish unconditional super-logarithmic lower bounds for $i_P(\tau )$ where no super-polynomial size lower bounds are known. We also point out connections of the new measure with some topics in proof complexity other than proof search.
Comparative Study of Persuasive Directive Speech on Printed and Digital Media Advertising

Changes in the form of discourse affect messages on the implicature to be conveyed.In advertising discourse, the implicatures conveyed may have various meanings which are not only dominated by persuasion of the invitation to buy the product or service being offered.The pragmatic viewpoint positions language as a complex message, which contains the message and function of the message.This qualitative research explores information from print and online media which is analyzed, described, and compared as a form of implicature data.Metadata were tabulated and sampling was conducted to identify persuasive directive speech on advertisements that have different characteristics.Directive speech acts in advertisements have different implicatures.The dominant function of the speech act from the results of the analysis includes speech containing requests, speech acts of the command directive, speech acts of the prohibited directive, and the function of the speech act of the requesting directive.Advertising has the main function of being persuasive, but the results of the implicative analysis show that the utterances in the advertisement contain commands, prohibitions, and information.Through the use of good persuasive language, advertisers are able to increase the number of visitors who make purchase decisions through digital media.In general, persuasive sentences in advertisements are conveyed creatively and generally, employed rhymes to attract attention and can be easily remembered.
Mathematical Modelling of Decision-Making: Application to Investment

In this paper, the mathematical modelling of decision-making problems based on probabilistic graphical models is presented. The models, in addition to random variables, also include decision and profit variables. The proposed decision models contain one or more decisions and their purpose is to assist the decision maker in choosing the best decision under conditions of uncertainty. The techniques used include modelling and evaluating decision trees, as well as evaluating, modelling and presenting the algorithm of influence diagrams (as the expansion of the Bayesian networks) to show the communication structure of the problem and thus provide a coherent presentation with an effective evaluation. The limited memory influence diagram and dynamic decision networks (as a dynamic Bayesian network) have also been developed to avoid the limitations of the influence diagram limitation. An application of the exposed models is presented in investment decision-making.
Big Data-Based Transformer Substation Fault Prediction Method

Transformer substations play a major role in power systems. The fault of a transformer substation will jeopardize the safety and effective operation of the power system. The fault signal of a transformer substation includes the fault status and fault occurrence time. In this paper, we propose a transformer substation fault prediction method based on big data analysis. Thus, a new transformer substation fault prediction method is developed by combining the advantages of decision tree algorithms and grey system theory to predict the fault status and occurrence time with high accuracy. As a case study, the transformer substation fault signals obtained from a region in the southwest of China are analyzed using the proposed method based on big data. The experimental results confirm that the proposed method achieves high-accuracy fault prediction.
Integrating Mobile-Assisted Language Learning: Teacher Beliefs in Japanese EFL Higher Education

Internet-enabled mobile devices, such as tablets and smartphones have become an integral part of our lives.They are widely used for a variety of different purposes, and in many countries the majority of university students arrive to classes with devices and are familiar with how they operate.Although mobile technology is viewed to be a useful tool in language learning, there are a number of barriers to successful integration in classrooms.One of the critical factors when considering technology adoption is teacher attitudes and beliefs.However, despite the strong correlation of teacher attitudes and successful technology integration, the dominating interest of mobile-assisted language learning (MALL) research is on its relative effectiveness, or analyzes its adoption from the perspective of students.There is a lack of empirical studies that investigate variables related to teacher beliefs that affect mobile integration in the EFL context.This study explored teacher attitudes towards the implementation of mobile-assisted language instruction in higher education in Japan.100 in-service teachers were given a questionnaire based heavily on the study by MacCallum, Jeffrey, & Kinshuk (2014) that included extensions to the Technology Acceptance Model (TAM).The survey was adapted to include cultural variables related to English instructors teaching in an EFL context.The findings provide crucial insights into the cultural implications of teachers' perceptions towards the successful adoption of MALL for instruction.Implications for classroom practice in other contexts and professional development are discussed.
Transformation Of Higher Education: From State Diagnostics To Management Decisions

The current stage of the society's socio-economic development is characterized by the soaring pace of digital transformation, which has been radically changing the landscape of all spheres of life: production, consumption, education, etc.In Russia, the formation of the labor and innovation markets has been changing and, consequently, the higher education is changing as well.Specialists with new unique digital competencies are required.To ensure the graduation of such specialists, a systematic change in the management of higher education at the state level is required.The research of dynamic changes in the system of educational organizations of the Russia in the period from 2013 to 2019 revealed significant changes in segment: the quantitative compression of the educational organizations and the qualitative growth of the educational system as a whole.The study of dynamic changes made it possible to forecast the development trend of higher education.The territorial differentiation of the educational landscape is assessed.The qualitative study of the funding aspect of students' admission was carried out.One of the innovative elements of managing the higher education system is the introduction of a strategic academic mobility program.This program provides for the allocation of substantial state funding to universities applying for the status of national research or national flagship universities on the basis of competitive selection.Individual educational tracks will allow graduating the specialists of a new formation.Increasing the number of educational platforms with high-quality online content gives rise to the academic mobility of students within individual educational tracks.
Understanding digital trends in marketing agribusiness products: critical analysis of international publications

This review study aims to gain an in-depth understanding of the extent to which digital trends in marketing agribusiness products are under the needs of farmers who live and farm in today's digital era. We chose to analyze national and international publications to understand the objectives of the study quickly. So our step is to look for study evidence data through electronic searches on Google Scholar-based data published between 2010 and 2021 to get the latest data. Furthermore, our data analysis involves data coding, evaluation, and in-depth interpretation to obtain valid and reliable findings as expected in the study findings. Because this study was conducted during the pandemic, we tried to get secondary data and follow descriptive qualitative data experts' directions. As a result, we can conclude another way that digital marketing in marketing agricultural products is a technique that is becoming trendy in many places. The digital trend is chosen by many people because of its easy and cheap principles so that both farmers and buyers will be lucky because marketing operations have been trimmed. Thus the results of this study are helpful for many parties.
Implementasi Blended Learning Selama Masa Pandemi Covid-19 Untuk Menumbuhkan Kemandirin Siswa Pada Mata Pelajaran Matematika di SD YP Nasional Surabaya

Blended Learning strategy is considered capable of fostering student independence and achievement in learning. This learning combines online and face-to-face learning. The implementation of Blended Learning enables students to learn effectively and efficiently, more easily access teaching materials, and in the end increases student learning independence because learning is done independently. Learning mathematics is one of the content in thematic learning in elementary schools. Therefore students must always participate in learning. As an effort of educational institutions to expand the reach of learning, implementation, cost efficiency, optimal results, adjusting to various student needs, and increasing the attractiveness of learning. The results showed that the implementation of blended learning during the pandemic in mathematics was very helpful for teachers in delivering material to students, as well as increasing student independence in learning.
The post-pandemic blended university in the time of digitisation

This paper documents the inevitable emergence of the ‘Global School’, assesses how the COVID-19 pandemic is hastening that transformation, and then focusses upon how these elemental educational developments may apply at the post-school level. Digitisation involves a pivotal leap in human potential as profound as the wheel in terms of development, as significant as the book in relation to information, and as iconoclastic as anything dreamed up by the deepest analyst/therapist in terms of the human psyche. Given that we are moving inexorably and joyfully into the One World One School situation, do we envisage the one global and blended university – where universal access and organisation are intermingled with local needs, cultures and priorities? Are we also progressing towards a blended post- secondary assessment and learning pedagogy in which the digital is dominant? And, if so, how will the pandemic – and the responses to it – pave the way towards that desirable destination?
Analisis Komparasi Algoritma Naïve Bayes dan K-Nearest Neighbor Untuk Memprediksi Kelulusan Mahasiswa Tepat Waktu

Students are one of the important pillars in the life cycle of a university. In the process of developing, a university can be influenced by how many bachelor degree (S1) graduates from the university are. The number of graduations of a college sometimes has a low ratio when compared to the number of students admitted in the same school year. This low passing rate of students can be caused by several factors, such as the number of student activities that are participated in, economic factors, and several other unexpected factors. This makes a university must have a scheme or a formula that can predict whether the student can graduate on time. Normally, a bachelor (S1) student takes 8 semesters of education. But the existence of several factors that have been mentioned can make the time to take S1 education to be more, or even fail to graduate. This study will try to compare the results of the analysis of the two methods in the classification algorithm to predict student graduation. The algorithm used is the K-Nearest Neighbor and Naïve Bayes Algorithm. This study also aims to identify the best algorithm among the two classification algorithm choices. This research concluded that the Naïve Bayes algorithm has the same level of accuracy as the KNN algorithm in predicting the graduation of students in the Medical Education study program, which is 90%
Secure HIGHT Implementation on ARM Processors

Secure and compact designs of HIGHT block cipher on representative ARM microcontrollers are presented in this paper. We present several optimizations for implementations of the HIGHT block cipher, which exploit different parallel approaches, including task parallelism and data parallelism methods, for high-speed and high-throughput implementations. For the efficient parallel implementation of the HIGHT block cipher, the SIMD instructions of ARM architecture are fully utilized. These instructions support four-way 8-bit operations in the parallel way. The length of primitive operations in the HIGHT block cipher is 8-bit-wise in addition–rotation–exclusive-or operations. In the 32-bit word architecture (i.e., the 32-bit ARM architecture), four 8-bit operations are executed at once with the four-way SIMD instruction. By exploiting the SIMD instruction, three parallel HIGHT implementations are presented, including task-parallel, data-parallel, and task/data-parallel implementations. In terms of the secure implementation, we present a fault injection countermeasure for 32-bit ARM microcontrollers. The implementation ensures the fault detection through the representation of intra-instruction redundancy for the data format. In particular, we proposed two fault detection implementations by using parallel implementations. The two-way task/data-parallel based implementation is secure against fault injection models, including chosen bit pair, random bit, and random byte. The alternative four-way data-parallel-based implementation ensures all security features of the aforementioned secure implementations. Moreover, the instruction skip model is also prevented. The implementation of the HIGHT block cipher is further improved by using the constant value of the counter mode of operation. In particular, the 32-bit nonce value is pre-computed and the intermediate result is directly utilized. Finally, the optimized implementation achieved faster execution timing and security features toward the fault attack than previous works.
Total variation cutoff for the flip-transpose top with random shuffle

We consider a random walk on the hyperoctahedral group $B_n$ generated by the signed permutations of the forms $(i,n)$ and $(-i,n)$ for $1\leq i\leq n$. We call this the flip-transpose top with random shuffle on $B_n$. We find the spectrum of the transition probability matrix for this shuffle. We prove that the mixing time for this shuffle is of order $n\log n$. We also show that this shuffle exhibits the cutoff phenomenon. In the appendix, we show that a similar random walk on the demihyperoctahedral group $D_n$ also has a cutoff at $\left(n-\frac{1}{2}\right)\log n$.
Flattening the Curve, Constitutional Crisis and Immigrants' Rights Protections: The Case of Israel

Despite being a small and relatively secluded country, managing the COVID-19 pandemic has so far been quite a challenge for Israel. This contribution seeks to explain how Israel had managed migration and the pandemic amidst a constitutional crisis between February and July 2020.