Reviewerly/exHarmony huggingface dataset:
Is Everything a Challenge for Multiple Sclerosis patients? Nonverbal Semantic Memory Performance in Iranian Relapsing-Remitting Multiple Sclerosis Patients

Objectives: The objective of the current study was to evaluate the nonverbal semantic memory performance of MS patients and compare it with their healthy counterparts.&#x0D; Materials and methods: In this study, 70 patients with definite relapsing-remitting multiple sclerosis(15 men and 55 women) and 70 healthy individuals of comparable demographics (age, gender, and education) from patients’ relatives and family members were selected based on convenient sampling. The patients recruited for this study were divided into two groups based on their Montreal Cognitive Assessment (MoCA) scores. The first group of patients (MS1) with MoCA scores of 18-25, and the MoCA scores of the second group (MS2) ranged from 10 -17. All of the participants were right-handed, originally born in Mashhad, Iran, and native speakers of Persian. To assess the nonverbal semantic memory performance of the participants, the picture version of The Camel and Cactus Test (CCT) was selected and administered from the Cambridge Semantic Memory battery test.&#x0D; Results: The results revealed that there was no significant difference between the MS1 and the Healthy Controls group in living and man-made variables, while MS 2 performed significantly different compared to other groups in these variables. The results also showed that all three groups of participants performed significantly different from each other in reaction time variable.&#x0D; Conclusion: The findings showed that cognitive impairment in multiple sclerosis patients did not affect their nonverbal semantic memory performance, however, it had an impact on their reaction time.&#x0D; Bangladesh Journal of Medical Science Vol.20(2) 2021 p.390-395
Audit Tata Kelola Sistem Informasi Manajemen Kepegawaian Perguruan Tinggi dan Proses Investasinya Menggunakan Standard Framework COBIT

POLBAN has implemented a Personnel Management Information System which is used to assist management in managing, monitoring and recapitulating personnel data reports. However, the IT governance process is still not optimal and there are still many shortcomings. The purpose of this research is to know the processes and procedures for the management of SIMPEG POLBAN, IT Risk, IT Control, IT investment processes and measurement maturity levels of IT Governanceusing COBIT 4.1.measurement is Maturity level based on four domains in COBIT, namely Planning and Organize, Acquire and Implementation, Delivery and Support, and Monitor and Evaluate. The results of research conducted at SIMPEG POLBAN, obtained a level of maturity at level 2, namely Repeatable but Intuitive. This means that IT activities are still carried out according to custom without any clearly written procedures. The results of measuring the level of maturity are expected to become input in POLBAN's future strategic development plans.).
Continuous-time Dynamic Network Node Classification Algorithm Based on Autoencoder

Node classification is an important issue in network researches. Existing methods lay more emphasis on the classification of static network nodes, while there are insufficient researches on network dynamic characteristics. At the same time, the existing adjacency matrix representation cannot reflect the potential relationship of indirectly connected nodes. To better describe the network structure and utilize network time information, the author proposes a new Node Classification Algorithm based on Autoencoder, namely NCAA. It adopts the random walk in limited spatio-temporal and the matrix representation of node relationship. The low-dimensional representation vector of the node is generated by the autoencoder model, and the LogicRegression classifier is used to classify the representation vectors, thereby achieving node classification. Experiments show that, compared to some classic algorithms, NCAA can better represent the network, and its two-dimensional visualization of node vectors has a superior effect. Under the same conditions, the F1 value of the classification result is significantly higher than that of baseline algorithms.
Digital Literacy: An Investigation of English Teacher at SMPN 2 Tayu, Pati in 2018/2019 Academic Year

This study discusses the digital literacy of an English teacher, specially the teacher’s perspective the digital literacy. In this research, the researcher investigates how digital literacy is perceived by the teacher at SMPN 2 Tayu, Pati. This type of research is descriptive qualitative. The subject if this study an the teacher who has digital literacy experiences in the classroom teaching and learning process and other activities that use digital. The object of this research is the perception of the teacher at SMPN 2 Tayu. Data collection is interview. The researcher used interview to get data from the teacher because the researcher wants to know the perception by the teacher and interview is the right technique for collecting data. The result of this study shows that: 1. Digital literacy is inevitable for teaching; 2. Digital literacy helps teacher to teach better; 3. Learning digital literacy relatively takes less time.
A Multi-fusion Acoustic Feature Generation Method for Identity Authentication Based on Speaker Verification

The traditional speaker verification method has inefficient performance in confirming the speaker identity and the text contents. In addition, there is an urgent need for the authentication system to understand the text contents concisely and comprehensively. To address above problems, a multi-fusion acoustic feature generation method is proposed for the Speaker identity Verification system. First, a Bidirectional Long Short Term Memory (BLSTM) network is trained as an acoustic feature extractor to extract spliced MFCC - TANDEM acoustic features, and then a multi-fusion BLSTM network is further trained to obtain more robust multi-fusion deep feature, and the Probabilistic Linear Discriminant Analysis (PLDA) probability is employed as a back-end classifier to deal with this feature, then all these acoustic features are trained in the Gaussian Mixture Model-Universal Background Model (GMM - UBM) framework. This experiment was evaluated on the RSR2015 data corpus. And the results show that the system using the multi-fusion acoustic feature has about a 35% reduction in the EER compared to the system using the spliced MFCC-TANDEM features. This shows that the multi-fusion acoustic features are more discrimination. Moreover, the system that used the multi-fusion acoustic features shows significant performance improvements over the baseline system, with Equal Error Rate (EER) reductions of about 40%.
LibGuides: Finding Books to Read for Fun!: Home

This workshop will introduce participants to useful online resources for finding book recommendations and tools for keeping track of what you've read
Impact Of Specialized Help And Trust On The Selection Of Electronic Human Asset Executives: Evidence From Developing Nations

The motivation behind the investigation is to examining those elements that are affecting upon the reception of E-HAE(Electronic Human Asset Executives). The respondents of the examination were 288 workers from the colleges. Analyst has embraced the survey through the writing and taken the reactions sufficiently from the representatives of University. This exploration model has been planned with regards to acknowledgment and decides the adjustment in conduct towards embracing the EHAE in Universities alongside the effect of expanded specialized help and trust on EHAE in Universities. This model is useful in deciding the effect of various highlights, for example, convenience, value, trust and specialized help on conduct towards the EHAE in Universities. The external components of the model are Technical help or help and trust. This examination broadens the Technology Acceptance Model. The investigation results recommend that two elements are significant that are specialized help and trust affecting upon the convenience and helpfulness; alongside this effect of usability and handiness is upon the mentality and the effect of demeanor is upon the reception of E-HAEin colleges. The examination additionally talks about the specific limtations and gives suggestion to the partners.
Model-based Navigation in Environments with Novel Layouts Using Abstract 2-D Maps

Efficiently training agents with planning capabilities has long been one of the major challenges in decision-making. In this work, we focus on zero-shot navigation ability on a given abstract 2-D occupancy map, like human navigation by reading a paper map, by treating it as an image. To learn this ability, we need to efficiently train an agent on environments with a small proportion of training maps and share knowledge effectively across the environments. We hypothesize that model-based navigation can better adapt an agent's behaviors to a task, since it disentangles the variations in map layout and goal location and enables longer-term planning ability on novel locations compared to reactive policies. We propose to learn a hypermodel that can understand patterns from a limited number of abstract maps and goal locations, to maximize alignment between the hypermodel predictions and real trajectories to extract information from multi-task off-policy experiences, and to construct denser feedback for planners by n-step goal relabelling. We train our approach on DeepMind Lab environments with layouts from different maps, and demonstrate superior performance on zero-shot transfer to novel maps and goals.
PENGOLAHAN CITRA UNTUK IDENTIFIKASI KEMATANGAN BUAH JERUK DENGAN MENGGUNAKAN METODE BACKPROPAGATION BERDASARKAN NILAI HSV

Tanah Karo is one of the mountainous areas that has very cool air, so Tanah Karo is a producer of citrus fruits that produce citrus fruits of good quality. But unfortunately the citrus farmers in the area still use conventional (manual) methods or by seeing with the human eye's eyes in selecting citrus fruits of suitable maturity and service without special knowledge and only from their experience. However, human vision has the limitation that the human eye will experience fatigue. Harvesting unripe citrus fruits results in inappropriate quality of citrus fruit being marketed and if you harvest too ripe citrus fruits, it will cause the citrus fruits to rot quickly when they are distributed to agents or buyers in the market. From the input pattern / image of citrus fruits as training data and training targets, it can identify the ripeness of citrus fruits using the backpropagation method. Based on the citrus fruit image data, it can recognize the pattern of citrus fruit that has a maturity level that matches the digital image using the backpropagation method, with the accuracy of training and testing data being 100%.
Computational Cost Reduction of Transaction Signing in Blockchain

Nowadays, Blockchain is a disruptive technology, particularly in the financial context. Moreover, Blockchain is behind the success of cryptocurrencies, e.g., Bitcoin and Ethereum. Unlike traditional currencies, cryptocurrencies are entirely virtual. There is no physical money, but it can directly make payments in digital currency from one person to another without intermediaries. Moreover, Hashing's cryptographic algorithm makes Blockchain resist tampering from any transacting participants because the submitted block cannot be altered or re-engineered. However, another big problem is how users of cryptocurrencies stop somebody from adding or editing a transaction that spends someone else's money to them. To do this, Blockchain needs another cryptosystem called Public/Private Keys, a primitive asymmetric cryptosystem, e.g., the RSA encryption, to sign the transactions for proving the authenticity of the ownership without revealing the signed secret information. The generated public key is regarded as a ledger account number or digital wallet of the sender and the recipient. Simultaneously, the paired private keys are used to identify whether the digital wallets' owners are authentic. As growing network entities and propagated Blockchain transactions, computing millions of replicated tokens in the blocks to sign and verify the digital wallet's ownership is computationally expensive. However, a certain of chosen arithmetical transformations that can simplify mathematical cost can significantly reduce computational complexity. This research's main contribution is developing a protocol that can reduce the complexity and mathematical cost in generating the digital wallet and verifying its authenticity of ownership. Finally, performance analyses of the RSA algorithm for the protocol have been measured and visualized using Python.
An empirical study of a pruning mechanism

Many methods aim to prune neural network to the maximum extent. However, there are few studies that investigate the pruning mechanism. In this work, we empirically investigate a standard framework for network pruning: pretraining large network and then pruning and retraining it. The framework has been commonly used based on heuristics, i.e., finding a good minima with a large network (pretraining phase) and retaining it with careful pruning and retraining (pruning and retraining phase). For the pretraining phase, the reason for which the large network is required to achieve good performance is examined. We hypothesize that this might come from the network relying on only a portion of its weights when trained from scratch. This way of weight utilization is referred to as imbalanced utility. The measures for weight utility and utility imbalance are proposed. We investigate the cause of the utility imbalance and the characteristics of the weight utility. For the pruning and retraining phase, whether the pruned-and-retrained network benefits from the pretrained network indded is examined. We visualize the accuracy surface of the pretrained, pruned and retrained networks and investigate the relation between them. The validation accuracy is also interpreted in association with the surface.
Homologous Sockpuppet Accounts Detection Based on Comment Behavior Features

Since sockpuppet accounts are usually controlled by illegal owner to do harmful behaviors, homologous sockpuppet accounts detection is of great significance. However, traditional detecting methods based on register profile information and writing features are not effective. In order to solve this problem, a homologous sockpuppet accounts detection algorithm is proposed based on the comment behavior features. Firstly, frequent binary itemset mining is performed to build the ego-network of designated sockpuppet account. The comment co-occurrence frequency between neighbor accounts is then analyzed through the multi-granularity sliding window model. Meanwhile, the weight of each edge in the ego-network is calculated based on the Certainty Factor Theory. Finally, considering the triangle structure in the ego-network, we obtain the comprehensive possibility whether designated account and its multi-level neighbor accounts belong to the same owner. The experimental results show that our proposed method can detect homologous sockpuppet accounts effectively.
PENDIDIKAN KELUARGA DALAM PENGUATAN LITERASI DASAR PADA ANAK

This study is motivated by the low basic literacy problem of children. Based on news from Republika (Darma, 2020) states that the ability to process information through literacy or literacy culture in Indonesian society is very low. Chairman of the Indonesian Literacy Culture Development Forum Satria Darma said, based on research results from international institutions, the literacy culture of the Indonesian people is very low compared to other countries in the world. The reading position of Indonesian students ranks 57th out of the 65 countries studied (PISA). "PISA said, the literacy results of students in Indonesia are below level three and one, only 0.4% have literacy level four," he said. Based on these problems the researchers were moved to conduct a study about family education in strengthening basic literacy in children. in order to contribute to knowledge about how family education is to strengthen basic literacy in children. This study uses a qualitative descriptive approach, the problems in this study are described clearly based on the theory of family education in strengthening literacy in children so that they become provisions in educating children. from this research, it produces knowledge and ways to educate families to strengthen basic literacy in children.
Penerapan Data Mining Algoritma FP-Growth Untuk Persediaan Sparepart Pada Bengkel Motor (Study Kasus Bengkel Sinar Service)

The strategy used by motorcycle workshop management is through software applications with information systems to obtain a new innovation. In the process of selling goods, it is expected to provide benefits for those who use information technology because it can improve sales quality by providing services and recommendations to sellers and buyers. can even provide promotions. For this reason, the application of the association rules analysis application was developed in finding patterns of the combination of relationships between item-sets and for processing data on the accumulation of sales of workshop tools so far unknown for use so that the accumulated data was mined and information extracted and extracted information which is useful or called data mining is then extracted and interpreted by the pattern of sales trend of tools to improve services that are often sold using the FP-Growth algorithm. FP-Growth is an alternative algorithm that can be used to determine the set of data that most often appears (Frequent Item Set) in a set of data and uses the concept of building trees in the search for Frequent Item Sets. This research was conducted by observing the variable data of equipment repairing equipment to improve service.
PENINGKATAN KEKERASAN PISAU SADAP KARET PRODUK PANDAI BESI DENGAN PROSES HARDENING DAN QUENCHING ( VARIASI TEMPERATUR DAN MEDIA PENDINGIN )

Often the rubber tapping knives produced by blacksmiths have cracks and chipped and even broken on their blades, so rubber farmers must often replace them with new knives. Thus the product cannot be used for a long time and has reduced economic value. The cause of this rubber tapping knives made by blacksmiths is easily damaged because the gilding method on the product is not done properly. So the product was produced have a relatively low level of hardness. This study aims to determine the effect of the hardening and quenching process on the hardness of rubber tapping knives made by blacksmiths. Data of test were analyzed using ANOVA with full factorial level design , main effect model design, and 3 replications assisted with Design-Expert software. At a temperature of 800℃, the maximum hardness value of 62,8 HRC obtained from the quenching results using a water cooling media, while the minimum hardness value of 62,2 HRC was obtained from oil cooling media.  At a temperature of 850℃ the maximum hardness value of 60,4 HRC obtained from the quenching results using water cooling media, and the minimum hardness value obtained from the oil cooling media is 59,1 HRC.Keywords: Spring leaf, Hardening , Quenching ; ANOVA; Full Factorial;Rubber tapping knives
Time Series Counterfactual Inference with Hidden Confounders

We present augmented counterfactual ordinary differential equations (ACODEs), a new approach to counterfactual inference on time series data with a focus on healthcare applications. ACODEs model interventions in continuous time with differential equations, augmented by auxiliary confounding variables to reduce inference bias. Experiments on tumor growth simulation and sepsis patient treatment response show that ACODEs outperform other methods like counterfactual Gaussian processes, recurrent marginal structural networks, and time series deconfounders in the accuracy of counterfactual inference. The learned auxiliary variables also reveal new insights into causal interventions and hidden confounders.
Tight Quantum Time-Space Tradeoffs for Function Inversion.

In function inversion, we are given a function $f:[N]\rightarrow[N]$ , and want to prepare some advice of size $S$ , such that we can efficiently invert any image in time $T$ . This is a well studied problem with profound connections to cryptography, data structures, communication complexity, and circuit lower bounds. Investigation of this problem in the quantum setting was initiated by Nayebi, Aaronson, Belovs, and Trevisan (2015), who proved a lower bound of $ST^{2}=\tilde{\Omega}(N)$ for random permutations against classical advice, leaving open an intriguing possibility that Grover's search can be sped up to time $\tilde{O}(\sqrt{N/S})$ . Recent works by Hhan, Xagawa, and Yamakawa (2019), and Chung, Liao, and Qian (2019) extended the argument for random functions and quantum advice, but the lower bound remains $ST^{2}=\tilde{\Omega}(N)$ . In this work, we prove that even with quantum advice, $ST+ T^{2}=\tilde{\Omega}(N)$ , is required for an algorithm to invert random functions. This demonstrates that Grover's search is optimal for $S=\tilde{O}(\sqrt{N})$ , ruling out any substantial speed-up for Grover's search even with quantum advice. Further improvements to our bounds would imply new classical circuit lower bounds, as shown by Corrigan-Gibbs and Kogan (2019). To prove this result, we develop a general framework for establishing quantum time-space lower bounds. We further demonstrate the power of our framework by proving the following results. •Yao's box problem: We prove a tight quantum time-space lower bound for classical advice. For quantum advice, we prove a first time-space lower bound using shadow tomography. These results resolve two open problems posted by Nayebi et al (2015). •Salted cryptography: We show that “salting generically provably defeats preprocessing,” a result shown by Coretti, Dodis, Guo, and Steinberger (2018), also holds in the quantum setting. In particular, we prove quantum time-space lower bounds for a wide class of salted cryptographic primitives in the quantum random oracle model. This yields the first quantum time-space lower bound for salted collision-finding, which in turn implies that $\text{PWPP}^{\mathcal{O}} \nsubseteq \text{FBQP}^{\mathcal{O}}/\text{qpoly}$ relative to a random oracle $\mathcal{O}$ .
Students’ Views of Business English Implementation In Management Department, University of Bina Bangsa

It is an undeniable fact that English has become the lingua franca. Teaching English faces the challenge of being able to provide knowledge for a specific purpose. Acquiring language skills in the specialized area of Business English is essential for future managers, entrepreneurs, and anyone who is about to get into the business world. The purpose of this research was to determine students' views on the implementation of Business English in management department. In answering the research questions above, the researcher applied a descriptive qualitative approach. The data collection method was carried out through semi-structured interviews using open-ended questions and analyzing them employing an interpretive analysis approach. From the results of data analysis, it was found that 1) the material were employed had connected to the learning needs of students where the material provided included words related to Business English, Grammar structures, and practical language teaching. However, students considered the design or appearance of the book less attractive so that they were less interested in using the book; 2) students showed various perceptions about the teaching strategies of their lecturers, found themes that showed teaching strategies that students like are supportive, create fun learning, provide games, be disciplined and assertive but feel not pressured, have an active professional knowledge components. Keywords: Students’ views, Business English; teaching materials; teaching strategy