Reviewerly/exHarmony huggingface dataset:
A mini-review of face alignment - classical method versus deep learning approach / Nabilah Hamzah, Fadhlan Hafizhelmi Kamaru Zaman and Nooritawati Md Tahir

Face alignment is one of the vital research areas to be explored specifically face tasks like face recognition, face verification, face reconstruction, and facial expression analysis. Hence, the need for robust face alignment is still in demand. Numerous classic methods have used the 2D image for the detection of facial landmarks but this task is challenging due to several reasons, for instance, large poses, semi-frontal images, and facial expression. Abundant techniques have been established to mitigate all these challenges but there are far from being solved. Hence this mini-review discussed the face alignment methods based on the classic method to the state-of-the-art that includes the 2D-face alignment along with the 3D-face alignment approach. Based on the review done, the 3D model could combat large poses, facial expressions, and semi-frontal images however some of the facial landmarks are not visible and stack together for occluded face images. Hence, this will be the research area to be explored further in ensuring robustness and better accuracy in the face alignment area.
KOMBINASI CAESAR CIPHER DAN REVERSE CIPHER BERDASARKAN CIPHER BLOCK CHAINING

Communication in the current era of globalization is very developed. Many applications that can be used to facilitate communication. However, because of this convenience, the security of the information contained in it will be more easily hacked by irresponsible people. Cryptography is the science or art for security message. In cryptography there are two important processes, namely encryption and decryption. The sender's job is to encrypt the message and the receiver's job is to decrypt the message. The key used for this cryptographic process is the Cipher Block Chaining (CBC) operation mode. CBC mode is a very simple operation mode, so additional techniques are needed to make it more secure. The plaintext will be replaced with new plaintext resulting from a combination of Caesar Cipher and Reverse Cipher techniques. The results obtained indicate that the application of plaintext modifications to CBC can improve message security because the keys used are increasingly complex.
LibGuides: BUS 301 - Business in Action: Cite Your Sources

The guide to to assist researchers in finding relevant resources for their experiential learning projects. HBS Citation Guide
Research of the Data Mining Engine Based on Big Data

With the rapid development of Internet technology, people are accumulating more and more data, and the scale of data has risen from the previous GB level to IB or even PB.In order to discover the potential value in the data, it is common practice to flexibly use various data mining algorithms according to the actual situation.Although data mining has been fully utilized and developed on traditional small data sets, proving its value and guiding significance, on large data sets, the implementation of data mining algorithms faces execution efficiency, algorithm parallelism, and easy platform Usability challenges.In order to solve the problems of data mining in big data, the paper researches the data mining engine under big data, using Spark as the core engine, and based on Spark's memory computing operators, a number of traditional data mining The parallel computing of the algorithm enables the traditional data mining algorithms to run in parallel in a cluster environment, and thus is well applied in big data.Then, through the system layering method, the data mining system is designed in layers to realize a complete big data mining platform.
Application for 3D Laser Scanning During Construction Stage of Nuclear Power Project

Abstract 3D laser scanning technology overcomes the limitation of single point measurement in traditional measurement methods, which can convert the 3D information of objects and site environmental into data processed by computers. The 3D laser scanning technology is usually called restoration of real scenes technology, which has been widely used in automobile, architecture, terrain exploration, petro and other industries. During the construction stage of nuclear power project, the 3D laser scanning technology can be used to get the real environment information on site. Through comparative analysis of the real environment information and the design model environment, risks can be easily identified in advance and mitigation measures can be performed in time, thus effectively avoiding the rework and saving the cost of the project.
Using Personal Vocabulary Notes (PVN) Technique to Develop the Students Vocabulary

The purpose of this study is: To find out whether Personal Vocabulary Notes (PVN) can increase student vocabulary in Papi Enrekang MTs. The method used in this study is a quantitative method and research design is a pre-experimental study. The sampling technique used in this study is cluster sampling. Researchers took one class as the subject of this study. Researchers have compiled the pretest score before treatment is provided and after treatment is provided. The results obtained are statistical analysis for 0.05 significance level with degrees of freedom (DF) = N-1, where (n) = 21, DF = 17. The probability value is smaller than
Decentralizing Multi-Authority Attribute-based Data Sharing Scheme in Cloud computing

To maintain data integrity on the cloud, Attribute-based Encryption (ABE) with Key Policy Attribute-based Encryption (KP-ABE) and Ciphertext-Policy Attribute-based Encryption (CP-ABE) can be used with access control implementation for cloud computing. CP-ABE is a promising cryptographic primitive for secure data sharing in cloud computing. A data owner is the only charge of to define the access policy associated with his data which to be shared. In CP-ABE, each user's secret keys are associated with a set of attributes and data are encrypted with access policy on attributes. A user can decrypt a ciphertext if and only if his attributes satisfy the ciphertext access policy. In CP-ABE, the secret keys of users have to be issued by a trusted key authority that leads to key escrow problem. Besides, most of the existing CP-ABE schemes cannot support attribute with an arbitrary state. In this paper, weighted-attribute data sharing scheme is proposed to solve the key escrow problem and also improve the expressiveness of attribute, so that the resulting scheme is friendlier to cloud computing applications. An improved two-party key issuing protocol guarantees that neither key authority nor cloud service provider can compromise the whole secret key of a user individually. The concept of weighted-attribute not only enhance the expression of an attribute binary to arbitrary but also reduce the complexity of access policy, so that storage cost of ciphertext and time cost in encryption can be reduced.
Federated Learning in Robotic and Autonomous Systems

Autonomous systems are becoming inherently ubiquitous with the advancementsof computing and communication solutions enabling low-latency offloading andreal-time collaboration of distributed devices. Decentralized technologies withblockchain and distributed ledger technologies (DLTs) are playing a key role.At the same time, advances in deep learning (DL) have significantly raised thedegree of autonomy and level of intelligence of robotic and autonomous systems.While these technological revolutions were taking place, raising concerns interms of data security and end-user privacy has become an inescapable researchconsideration. Federated learning (FL) is a promising solution toprivacy-preserving DL at the edge, with an inherently distributed nature bylearning on isolated data islands and communicating only model updates.However, FL by itself does not provide the levels of security and robustnessrequired by today's standards in distributed autonomous systems. This surveycovers applications of FL to autonomous robots, analyzes the role of DLT and FLfor these systems, and introduces the key background concepts andconsiderations in current research.
تمایز یادگیری آنلاین با آموزش اضطراری از راه دور

چکیده. نوشته حاضر ترجمه مقاله زیر است: The Difference Between Emergency Remote Teaching and online Learning EDUCAUSE (2020) 1-22,چکیده. نوشته حاضر ترجمه مقاله زیر است: The Difference Between Emergency Remote Teaching and online Learning EDUCAUSE (2020) 1-22,چکیده. نوشته حاضر ترجمه مقاله زیر است: The Difference Between Emergency Remote Teaching and online Learning EDUCAUSE (2020) 1-22,چکیده. نوشته حاضر ترجمه مقاله زیر است: The Difference Between Emergency Remote Teaching and online Learning EDUCAUSE (2020) 1-22,
System identification of a solar maximum power point tracking system for dual axis / Thomas Davion, Noorazlina Mohamid Salih and Mohd Shahrizan Mohd Said

The project is on Maximum efficiency of a solar panel. As the sun is not constant at one place and by fixing the solar array at a place, maximum power generation is not possible. This project develops a solar power generation system using maximum power point tracking system to gain more direct sun light on Photovoltaic (PV) modules leads to enhanced energy yield. Therefore, tracking systems are implemented to improve the performance of PV system by tracking sun trajectory. The current design of Maximum Power Point Tracking (MPPT) trackers are more efficient than conventional single state solar power generation. Then by comparing two designs initially produced, Maximum Power Point Tracking (MPPT) tracking devices are found to be at better efficiency than static models. The system locates maximum- power generating point using an MPPT controller. The base line results of this study were obtained via physical implementation of simulated system to analyze the various parameters. The system then uses a quadratic-equation based algorithm that calculates the quadratic function corresponding to the maximum power generation point. With the advent of different applications of PV solar power, system planners have been implementing different strategies and techniques to maximize the output of solar system with commonly available technology in market. Additionally, various mathematical techniques were utilized to analyze the results gathered from the physical implementation. The results of this study are based on two types of analysis. The comparison of static Photovoltaic output graphs with real time measured values for the systems and a Dynamic Photovoltaic Maximum power point Solar Tracker (MPPT) system. Both PV systems were implemented practically to get appropriate results and mainly all the equipment and services utilized in installation are widely available in local market.
An Analysis of the Importance of English Language and Literature to the Cultivation of Students’ Language Ability

As the most widely used language in the world, English has become a compulsory course for students. Since ancient times, most of the English teaching methods used by educators have been based on the traditional mode. The oral knowledge instillation type of teaching method ignores the cultivation of students’ language ability, which has a negative impact on students’ English learning. On the surface of practice, English language and literature plays an important role in promoting students’ language ability. It can not only help students have a strong interest in English learning, but also improve their English learning ability. Based on the current situation of English teaching, this paper analyzes the importance of English language and literature to the cultivation of students’ language ability for reference.
If You Cannot Measure It, You Cannot Manage It: Assessing Cybersecurity Risk Factors through Textual Imagification

The destructive nature of cybersecurity threats makes it crucial for stakeholders to understand the related risks that any given firm faces. In order to map a firm’s known cybersecurity risks and identify its specific risks as compared to its industry peers, we utilize text mining techniques to extract and analyze risk factor disclosures that firms report on Form 10-K. Since a comparison of firms’ cybersecurity risks through textual analysis is statistically infeasible, we introduce a new approach, textual imagification. This methodology enables analysts to provide a measurable and comparable image of a firm’s cybersecurity risks based on data extracted from Form 10-K. This imagification of cybersecurity risks factors can facilitate stakeholders’ decision-making processes by enabling such risks to be easily accessible and comparable.
Fighting terrorism in Africa when existing terrorism levels matter

This study examines policy tools in the fight against terrorism when existing levels of terrorism matter in 53 African countries for the period 1998-2012. The empirical evidence is based on contemporary, non-contemporary and Instrumental Variable Quantile regressions (QR) which enable the investigation throughout the conditional distributions of domestic, transnational and total terrorism dynamics. The following findings are established. First, counterterrorism policy instruments of inclusive human development and military expenditure further fuel terrorim. Second, political stability negatively affects terrorism with a negative threshold effect. Political stability estimates are consistently significant with increasing negative magnitudes throughout the conditional distributions of domestic and total terrorism. Policy implications are discussed.
The classification of actual pronunciation of Quranic alphabets for non-Arab speaker

Each Quranic alphabet has its unique sounds produced by uttering the Arabic language at their point of articulation (Makharij) and their characteristics (Sifaat), which is called Tajweed. Much research has been done related to the Tajweed, but there are limited sources associated with the analysis of Quranic pronunciation of non-Arab speakers from signal processing perspective with respect to both Makhraj and Sifaat. Therefore, this research focus on the identification and classification of the actual pronunciation of the Quranic alphabets on the audio signal obtained from non-Arab speakers. In this research, the features were best identified by the combinations of four formant frequencies (f1, f2, f3, f4), and three power spectral density (psd1, psd2, psd3) extracted from the sukoon pronunciation of the alphabets’ audio data. All features were combined and classified using both Linear and Quadratic Discriminant Analysis (LDA and QDA) to represent the actual pronunciation of each alphabet for both Arab and Non-Arab speaker categories. The findings indicate that there are 25 alphabets were correctly classified more than 83% threshold value thus indicates the correct pronunciation, where the other three alphabets which are أ ض, أ غ and أ ف are falling under misclassified vector. Later, the Graphical User Interface (GUI) was developed using the training data of 25 alphabets to evaluate the percentage of accuracy (%) with the new audio dataset. The results show that the developed GUI has managed to record, analyze, and evaluate the pronunciation interactively.
An Improved Multitracker Optimization Algorithm and Multiple Subpopulations

Recently, a population-based optimization algorithm called the multitracker optimization algorithm (MTOA) was introduced based on the tracker con- cept. This paper proposes a novel variation of the original MTOA called the migration-based MTOA (MTOA1), which employs multiple subpopulations of trackers to achieve superior performance. The proposed algorithm differs from the traditional MTOA in that it splits the initial population into multiple sub- populations to enhance the search process in different areas of the search space. Furthermore, information is exchanged among the subpopulations in an iter- ative and cyclic manner. The best global trackers in the first subpopulation are used to update the global trackers of the second subpopulation, and this updating process continues for all subsequent subpopulations. Exploration and exploitation are balanced in this cyclic approach for multiple populations. The proposed MTOA1 is validated based on the CEC2017 benchmark problems, and an improvement over the original MTOA is observed. Furthermore, MTOA1 is used to solve the classical welded beam design problem and is compared with eight recently proposed optimization algorithms. The results confirm the superiority of the proposed algorithm.
A Context-Free Grammar for Parsing Manipuri Language

Parsing, i.e., identifying the underlying hierarchical structure of natural language expressions is important for several natural language processing applications. In recent times Machine Learning (ML) approaches have been developed for this study for many languages. Most of the effective techniques require an annotated corpus of the language for training and validation. For the Manipuri language of the Tibeto-Burman family, neither such a corpus nor a grammar framework to automatically analyse and represent the structure of sentences exists yet. This study proposes a context-Free Grammar (CFG) that provides the framework to represent the structure of Manipuri sentences. This paves the way for parsing Manipuri sentences using CFG-based parsers for various applications and to conveniently build a Treebank for developing ML-based parsers for Manipuri. The rules of the proposed CFG are handcrafted after extensive analysis of the structure of Manipuri sentences. The grammar covers simple, compound, complex and compound-complex sentences. For evaluation, we induce an Earley’s parser with the proposed CFG and test it over a collection of sentences that covers the possible varieties of structure. A recognition rate of 83.20% achieved in these experiments indicates the effectiveness of the proposed grammar.
Quantum correlation in superconducting Two-Qubit systems

We consider a two-qubit superconducting system. By introducing the two measures of Concurrence and discord, we calculate the value of the correlations of this system and also determine the changes of the correlations of this system with respect to the temperature and the coupling of the circuits.
e-CALLISTO Data Analysis Using Python Scripts

The continuously changing solar wind, geo-magnetic field from the Sun and the plasma flow has high impact on the life of the living organism. The living organism life on the earth is driven by the Sunlight. The climate of the earth is critically sensitive to the solar activities. This impact is very high when sun is following 11-year cycle. Therefore, it becomes necessary to observe and study the solar activities. Many instruments and observatories are watching the solar activities. Compound Astronomical Low-cost Low-frequency Instrument for Spectroscopy and Transportable Observatory (CALLISTO) is portable and low-cost instrument used to detect solar activities. e-CALLISTO network with central hub located at the Switzerland is worldwide network and providing observations from different countries from last several years. The received data is raw with noise and in the Flexible Image Transport System (FITS) file format. This data needs processing by the suitable image processing techniques. There are different methods that can be used to process the generated images. The main aim of the image processing is to remove the background noise from the image. This paper presents the processing of FITs file by python scripts. Python programming language works quickly and integrates systems more effectively. The advantages of python scripts are its flexibility of the command, convenient and short script, fast data processing. The script uses minimum resources and time to process single image. This is useful when large numbers of images are needed to be processed with limited computer resources. Paper represents the radio burst results after Python script processing of images received by e-CALLISTO (Nashik-India) recently.
A Syntactic Analysis of Sinhala Relative Clauses

This paper provides a generative syntactic analysis of the relative clause (RC) construction in Sinhala, the Indo-Aryan isolate spoken in Sri Lanka. The goal is to analyze Sinhala and determine its place in the typology of human languages as characterized by a Minimalist theory of principles and parameters. Thus, while using diagnostics standard in literature on relative clauses from English and head-final languages such as Japanese and Korean, (Cinque, 2020; Fukui & Takano, 2000; Kuno, 1973; Kwon, 2008; Murasugi, 2000; Saito, 1985), we present evidence that favor a non-movement analysis of Sinhala RCs. We propose that the gap in a Sinhala RC, unlike in English, is not a copy/trace left by head movement or operator movement. Rather, it is a null pronominal (pro) base-generated inside the RC and A-bar bound by a null operator base-generated at the specifier of the Complementizer Phrase. Evidence is provided from subjacency, idiom chunks, adjectival modification and case marking. The paper contributes to the discussion on the typology of relative clauses in generative grammar.
Community Question Answering Entity Linking via Leveraging Auxiliary Data

Community Question Answering (CQA) platforms contain plenty of CQA texts (i.e., questions and answers corresponding to the question) where named entities appear ubiquitously. In this paper, we define a new task of CQA entity linking (CQAEL) as linking the textual entity mentions detected from CQA texts with their corresponding entities in a knowledge base. This task can facilitate many downstream applications including expert finding and knowledge base enrichment. Traditional entity linking methods mainly focus on linking entities in news documents, and are suboptimal over this new task of CQAEL since they cannot effectively leverage various informative auxiliary data involved in the CQA platform to aid entity linking, such as parallel answers and two types of meta-data (i.e., topic tags and users). To remedy this crucial issue, we propose a novel transformer-based framework to effectively harness the knowledge delivered by different kinds of auxiliary data to promote the linking performance. We validate the superiority of our framework through extensive experiments over a newly released CQAEL data set against state-of-the-art entity linking methods.
Freedom of expression in Zambia revisited

The right to freedom of expression is at the core of democracy. It means the right not to be prevented from speaking or not to be punished for speaking, based on the alleged unacceptability of an idea. It grants protection no matter the content of the message, because the exchange of ideas is valuable for reasons other than the substantive qualities of what is said and worthy of protection. However, the proliferation of social media has brought with it various challenges, such as “fake news” and increased levels of defamation. This has led to calls for certain social media sites to be regulated. This chapter focuses on the situation in Zambia. It aims to demonstrate that there is no need for regulation, as the laws of Zambia are already restrictive enough on freedom of expression. There is no need to introduce additional measures, such as banning social media or further restricting the press. The chapter examines freedom of expression in Zambia, its necessity in a functional democracy, and the manner in which it is restricted. It challenges the creeping excision of citizens’ rights to freedom of expression.
PENINGKATAN KEMAMPUAN KONSEP BILANGAN ANAK MENGGUNAKAN PERMAINAN CONGKLAK SELAMA MASA PEMBELAJARAN JARAK JAUH DI KECAMATAN ARCAMANIK

This research is regarding numbering concept ability for children in Arcamanik sub-disctrict. Some children have experienced difficulty in mentioning randomized number symbol and to use the number symbol in calculation, addition and subtraction . This research aims to increase the ability of children's number concepts by using the traditional game of congklak. The method used is action research with the Pelton model. Data is gathered through using observation and field notes. The results of this study indicate that there is an increase in the ability of the concept of numbers after the children play the congklak game.