Reviewerly/exHarmony huggingface dataset:
Multiple Impossible Differential Attacks for ForkAES

To yield a highly efficient authentication encryption design for very short messages, the tweakable forkcipher is proposed, which is a tweakable block cipher that uses forking construction to produce two output blocks. The designers also presented ForkAES, a forkcipher that is based on the round function of AES and the tweakable variant of KIASU. Therefore, the security of ForkAES is found on the block ciphers AES and KIASU. However, from the perspective of new forking construction, attackers may obtain some unique properties. Impossible differential attacks are widely used on block ciphers. This paper studies the security of ForkAES against multiple impossible differential cryptanalysis. Based on the property of the forking construction, two types of impossible differential distinguishers have been constructed. We first use the tweak with different truncated differences to build more attack trails. Then, we first propose the multiple impossible differential attack for ForkAES- <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <mi>∗</mi> </math> -5-4. Thus, only a single round would remain as a security margin. Utilizing multiple attack trails, our attack scenario obtains more subkey bytes and enhances the subkey’s sieving efficiency without increasing complexity. Furthermore, we carefully consider the process of recovering the master key, which can efficiently reject wrong candidate keys. In reconstruction queries, our attack reaches the longest number of rounds for ForkAES in impossible differential analysis, with <math xmlns="http://www.w3.org/1998/Math/MathML" id="M2"> <msup> <mrow> <mn>2</mn> </mrow> <mrow> <mn>100.8</mn> </mrow> </msup> </math> lookups, <math xmlns="http://www.w3.org/1998/Math/MathML" id="M3"> <msup> <mrow> <mn>2</mn> </mrow> <mrow> <mn>85.8</mn> </mrow> </msup> </math> chosen ciphertexts, and <math xmlns="http://www.w3.org/1998/Math/MathML" id="M4"> <msup> <mrow> <mn>2</mn> </mrow> <mrow> <mn>92.7</mn> </mrow> </msup> </math> memory blocks to store AES states. In encryption queries, we improve the previous attacks on ForkAES by attacking one more round (i.e., ForkAES- <math xmlns="http://www.w3.org/1998/Math/MathML" id="M5"> <mi>∗</mi> </math> -5-4), with <math xmlns="http://www.w3.org/1998/Math/MathML" id="M6"> <msup> <mrow> <mn>2</mn> </mrow> <mrow> <mn>118.2</mn> </mrow> </msup> </math> lookups, <math xmlns="http://www.w3.org/1998/Math/MathML" id="M7"> <msup> <mrow> <mn>2</mn> </mrow> <mrow> <mn>111.4</mn> </mrow> </msup> </math> plaintexts, and <math xmlns="http://www.w3.org/1998/Math/MathML" id="M8"> <msup> <mrow> <mn>2</mn> </mrow> <mrow> <mn>92.7</mn> </mrow> </msup> </math> memory blocks to store AES states.
Blockchain-Based Security Solutions for Big Data and IoT Applications

For any distributed system, consensus plays a pivotal role in holding together the whole system. This is true not just for any blockchain (BC) peer-to-peer (P2P) Network but also for Cloud Computing where the Leader Election Problem is solved by the use of various consensus algorithms. No “one” consensus algorithm is universal or perfect. Depending upon the type of BC employed and the use case of the BC, there may be a consensus algorithm that would help the system reach optimum functioning without compromising the integrity of the system. While proof of work (PoW) [2] became the first Consensus Mechanism to be used in BC, there have been many consensus algorithms to date. These are mechanisms which help the P2P network of a BC arrive at a decision. The decision taken most often is who is going to add the next block on the BC. This decision is crucial because if there exists a malicious entity in the network who gets in charge of the chain, then it would be detrimental to the overall functioning of the network. The chapter discusses the following consensus algorithms-PoW [2], proof of stake, delegated proof of stake, Byzantine fault tolerance (BFT), Crash Fault Tolerance, Hashgraph Consensus Algorithm, Proof of Elapsed Time, and Proof of Authority (PoA). The pros of the consensus algorithms and main drawbacks against implementation such as low throughput and excessive consumption of bandwidth have been discussed as well. A comparative analysis of the aforementioned algorithms with a major focus on use cases has been done to help understand how such mechanisms may be used for designing solutions which surpass the initial application of cryptocurrency and delve into real-world solutions in the fields including but not limited to the Internet of Things (IoT) and big data.
Research on key frame extraction algorithm based on deep convolutional neural network in video catalogue

With the gradual improvement of space launch sites image communication system construction, Visual command is increasingly demanding video image retrieval. The previous keyword retrieval method can not meet the requirements of new generation space mission network communication, content-based retrieval need to be developed. In view of the problem that video information is unstructured and cannot be quickly previewed, this paper studies the video key frame extraction algorithm and propose a video key frame extraction algorithm based on convolutional neural network.
Application of Blockchain Technology to Make Smart Cities Smarter

Today, most of the population has started migrating to urban areas. Quick urbanization centers around circumstances introduced by this urban change to make rising urban areas that go about as amazing and comprehensive advancement devices. A smart city utilizes data innovation to coordinate and oversee physical, social, and business frameworks so as to offer better types of assistance to its occupants while guaranteeing productive and ideal use of accessible assets. The reason for this report is to comprehend one of the new innovation achievements to be specific blockchain and break down how it tends to be used for making urban areas smarter. It will consider different regions of a smart city and distinguish those zones where block-chain advancement can be utilized to improve our urban communities and give better livability and financial improvement.
3D Digital Model of Folk Dance Based on Few-Shot Learning and Gesture Recognition

Folk dance is a very unique local culture in China, and dances in different regions have different characteristics. With the development of 3D digital technology and human gesture recognition technology, how to apply it in folk dance is a question worth thinking about. So, this paper recognizes and collects dance movements through human body detection and tracking technology in human gesture recognition technology. Then, this paper writes the data into the AAM model for 3D digital modeling and retains the information by integrating the manifold ordering. Finally, this paper designs a folk dance learning method combined with the Few-Shot learning method. This paper also designs a data set test experiment, an algorithm data set comparison experiment, and a target matching algorithm comparison experiment to optimize the learning method designed in this paper. The final results show that the Few-Shot learning method based on gesture recognition 3D digital modeling of folk dances designed in this paper reduces the learning time by 17% compared with the traditional folk dance learning methods. And the Few-Shot learning method designed in this paper improves the dance action score by 14% compared with the traditional learning method.
Tone error detection of continuous Mandarin speech for L2 learners based on TAM-BLSTM

To effectively help second language (L2) Chinese learners to produce tones correctly in computer assisted language learning (CALL), tone recognition of continuous speech is necessary. Because of the complex tone variation in continuous speech, this paper proposed TAM-BLSTM tone recognition model. Firstly, the generation model, target approximation model (TAM) is used to simulate fundamental frequency (f0) from original f0 contour in the unit of prosodic words, and the TAM parameters for each Chinese character are derived. Then BLSTM model with attention mechanism is set up with input feature of the TAM parameters and basic acoustic features, such as statistical f0 parameters, vowel duration, to solve the problem of tone detection of Mandarin continuous speech. Finally, the trained tone detection model is applied to the tone error detection of the L2 learners. The experimental results with Biaobei corpus show that the accuracy of the feature set combined with TAM parameters is 2.3% higher than that of using basic acoustic features alone, and the overall accuracy of ATT-BLSTM network model is higher than that based on ATT-LSTM.
Penerapan Metode SMOTE CHAID dalam Klasifikasi Tuberkulosis Relapse

DKI Jakarta Province is one of the provinces with the highest tuberculosis cases, and a person's chance of contracting tuberculosis is the greatest among other provinces. Tuberculosis can be cured with regular treatment within a certain period of time, but after recovering, some tuberculosis sufferers may relapse so that it can cause new problems. This study aims to build a classification model and determine which factors influence tuberculosis relapse using the CHAID method. SMOTE with majority undersampling is applied as a solution to deal with the problem of patient categories (relapse and non-relapse) who have an unbalanced number of observations. Based on the CHAID classification tree, the results show that the factors that influence relapse in tuberculosis patients include the type of diagnosis, age, gender, and place of residence. In addition, the application of SMOTE can improve the performance of the CHAID classification tree in classifying patients based on their categories. These results were indicated by an increase in the values of accuracy, sensitivity, and specificity to 76,153; 26,667; and 82,608 compared to the performance of CHAID without SMOTE. Based on these results, the SMOTE CHAID classification model has better performance than CHAID
Geochemical Fractal Characteristics of Deep-Sea REE-Rich Sediments in the Western Pacific

At present, the challenge for geochemical prospecting of deep-sea, rare, earth-rich sediments is the selection of exploration sites. Because of the unpredictability of offshore operations, the distribution and selection of survey line stations face great challenges. In this paper, we study the fact that the concentration distribution of geochemistry in space may be a part of a special complex process, which is called the multifractal. It requires a large number of indexes to characterize its scale characteristics. Based on the multifractal spectrum, 38 geochemical indices in the Pigafetta Basin region of the western Pacific Ocean are divided into three categories. The three indexes are distinguished by the multifractal parameters. The results of multifractals are in good agreement with those of the cluster analysis and principal component analysis. In addition, on the basis of principal component analysis, we further used the multifractal filtering method to extract element anomalies and delineate element enrichment regions. The first principal component clearly represents the potential element enrichment area. The spatial analysis technique and multifractal method proposed in the paper provide a new idea for geochemical prospecting of deep-sea, rare, earth-rich sediments.
Literacy Culture Assistance on Children Through Rumah Belajar Ilalang in Tahunan, Jepara

Reading is a culture that is almost degraded nowadays; even the culture of reading through books has become extinct, replaced by watching gadgets. The revitalization of literacy culture is certainly not easy in the midst of rapidly developing technology. TBM (Community Reading Park) Weed Learning House (RBI) bridges the literacy revitalization process for children in Tahunan, Jepara. The research was carried out through participatory service involving students of UIN Walisongo who were gathered in the Programmed Initiative KKN Mandiri program as a form of student anxiety about the decline in children's interest in reading. The mentoring activities resulted in the realization of reading culture assistance for children through the active RBI TBM by holding Mbelik Mili, Friday Familiar, and Sunday reading. In addition, efforts to improve literacy culture have resulted in the continuous development of RBI assistance because there is an interest in literacy in children by creating a reading culture, continuous development of mentoring in RBI through the government and stakeholders in Jepara, the need for the development of adequate facilities in TBM RBI, the need for stakeholder support holders in the community.
Class Discussions to Improve Students’ Active Participation in A Christian School During Online Learning

The research was inspired by the facts found in online class observations of primary students of Grade V in Tangerang. Some students did not participate in class discussions actively. Therefore, the objectives of this research were to explain the steps of class discussions to help Grade V students to participate more actively in online learning and to explain the impacts of class discussions on students' participation during online learning. This is classroom action research. The data was collected from 23 Grade V students of a Christian school in Tangerang from July 12, 2021, until August 18, 2021, during online learning. The instruments used were the observation form, lesson plan, affective journal checklist, and reflection. The results were class discussions improved students’ responsibility to participate actively, do the assignments, and participate verbally by answering and questioning in class discussions. Another result was there were six steps of class discussions, i.e., dividing the students into small groups, explaining the steps of good discussion, giving the topic or problem to be discussed by each group, facilitating the discussion and guiding the students, listening to groups’ presentation and giving each group feedback, as well as assisting the students to conclude. The conclusion was the class discussions that were prepared well by Christian teachers would improve primary students' active participation during online learning.
Pengembangan Website Paud Terpadu Aisyiyah Kaliwates Jember Menggunakan Blogger dan Bootstrap

Website development research methods Paud Terpadu Aisyiyah Kaliwates his is using the Waterfall model. The development of the Aisyiyah Paud Terpadu website has been successfully built and used for school promotion and can be used to convey school profile information. This website is in accordance with the current 4.0 technological developments and is very much needed for accuracy and speed and convenience for various parties. From what researchers have done, creating a website using blogger and bootstrap is very suitable because the responsive bootstrap technology is used both on the android &amp; desktop.Keywords: Website, blogger and bootstrap
Penggunaan Media Pembelajaran Visual untuk Meningkatkan Hasil Belajar Siswa di Madrasah Ibtidaiyah Negeri (MIN) 4 Desa Tanjung Genting Kabupaten Kerinci

This study was conducted to determine whether visual learning media can improve student learning outcomes in Madrasah Ibtidaiyah Negeri (MIN) 4 Tanjung Genting Village, Kerinci Regency. The type of research used is Classroom Action Research (CAR). The research subjects were students of class V MIN 4 Kerinci. The data collection techniques used in this study include tests, observations, and interviews. While the data analysis technique is carried out in several stages, namely data reduction, data presentation, and verification or drawing conclusions. The results showed that there was an increase in student learning outcomes by using visual learning media. This can be seen from the Minimum Criteria Completeness (KKM) of students in each cycle. In cycle 1, the average score was 56.25. In the second cycle it increased to 66.25. Then in the third cycle obtained an average value of 78.12. Thus, it can be concluded that the use of visual learning media can improve student learning outcomes in Madrasah Aliyah Negeri (MIN) 4 DesaTanjung, Kerinci Regency.
Discovery Learning Model with Animation Based Media on Social Studies Learning Motivation for 5th Grade Students of Elementary School

Lack of motivation to learn social studies in 5th grade students of SD Inpres Tattakang, so students are less interested and play a lot when learning takes place. The purpose of this study was to determine the effect of the animated media-based Discovery Learning Model on the social studies learning motivation of 5th grade students of SD Inpres Tattakang Pallangga. This type of research is a quasi-experimental non-equivalent control group design experiment. The sampling technique used random sampling. The sample in this study was class 5a which amounted to 27 people as the control class and class 5b which amounted to 28 people as the experimental class. This type of data collection uses a motivational questionnaire to measure learning motivation. The data analysis technique used is the Manova test, which was previously tested for normality and homogeneity. The results of this study showed an increase in social studies learning motivation, the results of the motivation questionnaire Manova test obtained a sig value. 0.00 &lt; 0.05 (smaller than 0.05) with a 95% confidence level, Ho is rejected and Ha is accepted, meaning that there is an influence of the animated media-based Discovery Learning Modelon the learning motivation of 5th graders at SD Inpres Tattakang Pallangga. So, it can be concluded that the learning model of Discovery Learning based on animation media has an influence on the social studies learning motivation of the 5th grade students of SD Inpres Tattakang.
iQMS: IoT-based QMS framework for tracking of quarantined subjects

The outbreak of Coronavirus Disease as a pandemic has resulted in a huge saddle on health infrastructure. Preventive measures such as quarantine, social distancing, isolation, and community containment play a pivotal role to contain the spread of exponentially growing COVID cases. This huge burden permitted authorities for institutional/home quarantine for the suspected persons. The biggest challenge for institutional/home quarantine is to monitor and track the movement of quarantined persons. These suspected cases pose a serious threat in outbreak and transmission of the disease. In this paper, an intelligent-Quarantine Monitoring System (iQMS) has been presented which comprises of a wearable IoT-based wristband, bundled with an android mobile app to track and report the absconding quarantined subjects in near real-time. The iQMS incorporates a cloud-based solution with IoT sensors using a global positioning system (GPS) based tracker for geo-fencing breach. The proposed system will facilitate the authorities in remote monitoring and tracking of identified subjects.
Problems of Machine Translation Systems in Arabic

the human need for language translation has been increasing because of knowledge fields’ expansion and open communications across all countries throughout the world. Accordingly, the traditional translation has become insufficient and machine translation is the best alternative. However, despite its astounding development during the past decades, as an inevitable alternative, machine translation still faces many challenges that make it incomparable with human professional translation. This indicates that machine translation in all its types has to be supported by highly-developed tools that can enhance its effectiveness. This study showed the advantages of machine translation, discussed some of its most common challenges, and accordingly introduced some recommendations that should be taken into account to improve its effectiveness regarding Arabic Language.
Development of Science Research Culture in Basic Education: A Theory Generation

Science research culture in basic education can be associated with science investigatory projects (SIPs). In relation to this, the paper establishes a theory on the development of SIP culture in basic education utilizing theory generation through axiomatic deductive approach based on steps prescribed by R. Padua (personal communication, November 17, 2014) which creates the theory that basic education institutions contribute to high productivity in SIPs. Simply because humans and non-human resources along with quality Science instruction are needed to yield such productivity. These attributes, resources, and Science instruction foster SIP culture. These are crucial aspects as schools capacitate students and teachers, produce the SIPs, and eventually disseminate these projects in science fairs.
National Education Policy 2020: A Historical Perspective

Abstract: India introduced the first education policy in 1968 during the government of former Prime Minister Mrs. Indira Gandhi. Rajiv Gandhi government formulated the second education policy in 1986. Narasimha Rao government made some amendments to this policy in 1992. And finally, after 34 years, the government took the step to introduce the National Education Policy 2020. It is very important to discuss the historical perspectives of NEP 2020. The present study is going to highlight the history of educational policies in India since independence and tries to focus on the important developments made in the field of education starting from the independence towards the revolutionary step made for NEP 2020. The present study describes the stages of development in each national education policies introduced in 1968, 1986 respectively and the lacunas which leads to the continuous change in the education road map of the country and framing a broad design for the national education 2020.
Development of an Effective Bootleg Videos Retrieval System as a Part of Content-Based Video Search Engine

Many research studies in content-based video search engines are concerned with content-based video queries retrieval where a query by example is sent to retrieve a list of visually similar videos. However, minor research is concerned with indexing and searching public video streaming services such as YouTube, where there is a dilemma for misusing copyrighted video materials and detecting bootleg manipulated videos before being uploaded. In this paper, a novel and effective technique for a content-based video search engine with effective detection of bootleg videos is evaluated on a large-scale video index dataset of 1088 video records. A novel feature vector is introduced using video shots temporal and key-object/concept features applying combinational-based matching algorithms, using various similarity metrics for evaluation. The retrieval system was evaluated using more than 200 non-semantic-based video queries evaluating both normal and bootleg videos, with retrieval precision for normal videos of 97.9% and retrieval recall of 100% combined by the F1 measure to be 98.3%. Bootleg videos retrieval precision scored 99.2% and retrieval recall was of 96.7% combined by the F1 measure to be 97.9%. This allows making a conclusion that this technique can help in enhancing both traditional text-based search engines and commonly used bootleg detection techniques.