Reviewerly/exHarmony huggingface dataset:
A Survey on Sign Language Recognition

The modern day applications are more user experience-oriented. Every application tends to gather information specific to each person’s operation and then provide customized features. The methods used to achieve such feats are a product of Machine Learning (ML) and Artificial Intelligence (AI) techniques. Using these techniques, real-time applications are reaching new heights in interacting with humans almost seamlessly. When living in such times, we can use these methods effectively to explore ways to overcome challenging problems. One such problem that we are taking upon is Sign Language Recognition (SLR). The project aims at bridging the communication gap with voice and hearing-impaired people, helping them to converse with the world more fluently. Using hand gestures as the primary input, we convert those into understandable language.
Mobile Chat Application with High-Level Messaging API based on Decentralized Networks

The main purpose of this project is to develop a system that is able to send messages via decentralized network. This allows for messages to be sent and received even in conditions where Internet connection is unfavorable or unavailable as well as sending messages to users outside or LAN connection area via public servers or ‘pub’.The system, named Echo, includes a high-level API as well as an accompanying Android mobile application as a frontend. The proposed high-level API will make use of SSB to provide flexibility and extensibility. The high-level API also allows for client applications to easily expand to other platforms. The two modules for this project are the Chatting Module and the Contact Management Module.Echo will be developed based on agile methodology. The Agile Crystal method is implemented due to the low number of developers.The testing criterias are based on the main functionalities of the main modules. Echo must be able to fulfil the main functionalities correctly and consistently. Testing will be conducted throughout the development to ensure each part of the functionalities are working as intended.Echo has the capability of solving the Internet access issues in terms of sending messages. It is able to reduce costs of mainstream chat applications such as Whatsapp or Wechat. Aside from that, Echo improves security and privacy of the users. Due to the use of decentralized network in SSB protocol, there is no central points of data that may be compromised and leaking large amount of user data. The current downside of Echo is the lack of additional functionalities of other matured chat applications, such video call and voice call. For this project, only an Android frontend will be developed.
Ensemble Based Feature Selection With Hybrid Model

In this study, a new mathematical model established with an ensemble-based approach, is proposed and applied to a large-scale data set consisting of three classes, whose features were extracted, obtained from birthday tweets. In this model, bagging method, which is one of the data variation methods, was applied first, and then a hybrid model combining the two approaches was created by applying the function variation approach obtained by using more than one feature selection method together. The resulting hybrid ensemble was first classified with the multi-class Support Vector Machines (SVM) algorithm, and then pruned with the ensemble pruning approach we propose in this study. By comparing the prediction success of the proposed model with the studies in the literature, it is observed that higher estimation success is obtained in comparison to those studies.
The Relationship of Principal Technology Leadership in Curriculum Management and Teacher’s Self-Efficacy

This study aimed at identify the influence of principal technology leadership in curriculum management towards teachers’ self-efficacy in secondary school district of Kota Kinabalu, Sabah. This is a quantitative research using questionnaire as an instrument and is analyzed using SPSS 25.0. Data was collected through a set of adapted questionnaires administered to 306 teachers. Descriptive and inferential statistics such as percentage, mean, standard deviation, t test, and Pearson correlation were used to analyze the data to answer the research questions. Descriptive analysis principal technology leadership in curriculum management and teachers’ self-efficacy being practised at a high level. Findings of the study showed that there is no significant difference in the min score of principal technology leadership in curriculum management and teachers’ self-efficacy according to gender t(306) = 0.001, k< .05, with mean of principal technology leadership in curriculum management for male (M = 4.349) and female (M = 4.348). While, mean of teachers’ self-efficacy for male (mean =4.342) and female (mean = 4.376). Pearson correlation test indicated a high positive linear relationship for principal technology leadership in curriculum management with teachers’ self-efficacy (r= .460, k< 0.05). The implications and suggestions for further study are also discussed.
System Level Design and Conception of a System-on-a-Chip (SoC) for Cognitive Robotics

In this work, a system level design and conception of a System-on-a-Chip (SoC) for the execution of cognitive agents in robotics will be presented. The cognitive model of the Concurrent Autonomous Agent (CAA), which was already successfully applied in several robotics applications, is used as a reference for the development of the hardware architecture. This cognitive model comprises three levels that run concurrently, namely the reactive level (perception-action cycle that executes predefined behaviours), the instinctive level (receives goals from cognitive level and uses a knowledge based system for selecting behaviours in the reactive level) and the cognitive level (planning). For the development of such system level hardware model, the C++ library SystemC with Transaction Level Modelling (TLM) 2.0 will be used. A system model of a module that executes a knowledge based system is presented, followed by a system level description of a processor dedicated to the execution of the Graphplan planning algorithm. The buses interconnecting these modules are modelled by the TLM generic payload. Results from simulated experiments with complex knowledge bases for solving planning problems in different robotics contexts demonstrate the correctness of the proposed architecture. Finally, a discussion on performance gains takes place in the end.
LibGuides: ENG 060 - Diversity - Fall 2019: Start Here

This guide provides help on using the library and resources for the diversity research assignment in ENG 060, Academic English for Non-native Speakers II.
Knowledge management and web 2.0-a perspective of libraries in India

The library management has now seen a transformation in the digital era. The present study made an introspection regarding the digital plate forms and how they could be used by the librarians especially in the colleges to transmit the knowledge. The Knowledge management and library in the educational institutions provide a learning environment that would optimize the library management system. The review of literature comprehensively covers the knowledge management perspectives in the libraries.
Collective Argumentation: The Case of Aggregating Support-Relations of Bipolar Argumentation Frameworks.

In many real-life situations that involve exchanges of arguments, individuals may differ on their assessment of which supports between the arguments are in fact justified, i.e., they put forward different support-relations. When confronted with such situations, we may wish to aggregate individuals' argumentation views on support-relations into a collective view, which is acceptable to the group. In this paper, we assume that under bipolar argumentation frameworks, individuals are equipped with a set of arguments and a set of attacks between arguments, but with possibly different support-relations. Using the methodology in social choice theory, we analyze what semantic properties of bipolar argumentation frameworks can be preserved by aggregation rules during the aggregation of support-relations.
ANALYSIS OF CATEGORICAL VARIABLES USING R

The article presents basic algorithms categorical data analysis using R package. Algorithms for the analysis of independent and non-independent nominal and ordinal data are presented.
RETRACTED ARTICLE: Analysis of drought climate ecology and college students’ entrepreneurial ability based on an ant colony optimization model

This paper first proposes an ant colony optimization model. The model defines the probability that acts on the number of average branch nodes, which always maintains the balance between “exploration” and “use”, so that the algorithm maintains a higher search capability while avoiding mistakes. According to this, the relationship between the drought climate development and the ecological impact of the grassland has summarized the accumulation mechanism of grassland ecological effects by studying the combination characteristics of grassland and ecological effects and the comprehensive response to important ecological elements. The entire life cycle of the arid climate can summarize the initial, developmental acceleration period, stable development period, and the end of development. Its integrated ecological effects of grasslands have time accumulation, spatial extension, and aggregation source, and also have characteristics such as hidden and dominant properties, threshold sensitivity, and ecological recovery. Finally, this paper creates a system for evaluating students’ entrepreneurial capacity. According to the elements collected, the index is obtained by theoretical analysis, and three-level indicators of entrepreneurial quality, entrepreneurial capacity, and entrepreneurship knowledge are extracted. Through professional communication and group exchange, the entrepreneurial capacity elements are classified. Through the questionnaire survey and causal analysis, we are able to check the entrepreneurial capacity index, improve the indicator system, and finally obtain an indicator of evaluating students’ entrepreneurial capacity evaluation, including level III indicators, level 9 II indicators, and 32-level III-level indicators and use them. The method will be described. We also calculated the weight and determined the assessment model by the level process. This paper uses a comprehensive fuzzy evaluation method as an evaluation method to establish an evaluation system to ensure its rationality and availability.
Design and Build Applications in Total Forecasting New Students in School by Applying Non Linear Trend Method

SMA Muhammadiyah 1 Bengkulu City is one of the schools located in Bengkulu City, where several data processing systems still use manual systems, one of which is new student registration. Every new school year, the officer fills out the sheet of students enrolled in the school one by one in the registration book. This takes a long time when the officer wants to make a report of students registered, because they have to retype the data in the registration book into the computer. In addition, after conducting interviews, it was found that the students at SMA Muhammadiyah 1 Bengkulu City experienced a decline every academic year. The application of forecasting the number of new students at SMA Muhammadiyah 1 Bengkulu City can be used to predict the number of new students in the next academic year based on the results of the analysis on old historical data. This forecasting process is carried out through the Non-Linear Trend Method approach, so that the final forecasting result is obtained from the stages of the process that occur. It was made using the VB.Net programming language and SQL Server database which can assist the school in managing school quality assurance, in order to attract interest from prospective students to enroll in SMA Muhammadiyah 1 Bengkulu City, and can arrange school promotion strategies for prospective students. Based on the tests that have been carried out, it can be concluded that the functional application of forecasting the number of new students at SMA Muhammadiyah 1 Bengkulu City has been running properly and the application for forecasting the number of new students at the school which is able to display forecasting results in the next academic year.
Impact of training on cybersecurity awareness / Zuriani Ahmad Zukarnain ... [et al].

Studies show that training is a good alternative to deliver cybersecurity knowledge to children.This paper reports on the findings of a study after conducting awareness training programs.The ultimate goal of the program is to help children to understand issues related tocybersecurity and instill the cybersecurity awareness. Children are now discovering computers,smartphones or tablets at an early age. Even though an internet connection of the computersand mobiles devices can be useful for learning as well as enhancing social relations and keepingthe young users connected to their parents, it can also be a source of danger and concern forparents. Hence, safer browsing habits need to be nurtured earlier among them. Cybersecurityawareness training was conducted to deliver the content to the targeted group. The objectivesof this study are to examine cybersecurity awareness after the participants have gone throughthe training, to improve a better understanding on cybersecurity awareness and finally topromote safer browsing habits. The cybersecurity awareness is important to develop a gooddigital citizenship among the young generation. The content of the training includes topics oncybersecurity threats such as pornography, pedophilia, online games addiction and cyberbully.Pre and post surveys have been conducted during each training session. The results show thatcybersecurity awareness training is one of the significant waysto increase knowledge regardingcybersecurity awareness starting at a young age. Hence, the finding supports that cybersecurityawareness must be encouraged among the young generation to develop a good digital citizen.
The Effectiveness of Metacognitive Strategy on Students’ Reading Comprehension of Narrative Text

Reading is something that is very needed in our lives. By reading we will open the window of the world and if we can take wisdom from what we read, we will become a great and noble human being as exemplified by the Prophet Muhammad. This study aims to determine whether there is a significant influence using metacognitive strategies for students’ reading comprehension in narrative texts. This study used a t-test experiment involving each individual in Grade VIII of SMP NU Panunggalan consisting of 34 students. The results showed that the mean score of the pre-test yielded 40.2941 and the average post-test post-test yielded 92.3529. The mean deviation produces a value of 52.05882, standard deviation produces a value of 21.85065 and produces a t-test of 13.892. T-table 5 %  shows the number 2.032 and t-table 1% shows the number 2.738. Then it can be concluded that 2.032 2.738. These results show significant results from the experiments on the effectiveness of metacognitive strategies on students’ reading comprehension in narrative texts.
ANALYSIS ON PUBLIC AUDIT IN CLOUD COMPUTING STORAGE DATA

The cloud computing in its numerous forms allow users to store information at faraway region and reduce load at neighborhood machine. even though it is an advantage nevertheless disadvantage exists along with far off storage. The principal security troubles in cloud computing including loss of facts control, lack of agree with and multi-tenancy are reviewed. The cloud computing and its service and deployment models are discussed by ways which the existing protection troubles in cloud computing are averted. ensuring cloud facts integrity and privacy seems to be the major difficulty. to conquer unauthorized access of information via cloud provider providers and records customers, verification is done thru depended on 0.33-party auditor. The cloud auditing needs to be executed and data safety also needs to be ensured with out the know-how of the actual data shops at cloud. Researcher suggests eager hobby to offer a cloud framework, which preserves the privateness and ensures the integrity of cloud information. The paper critiques privateness maintaining public audit schemes in cloud computing environment.
Tversky Anonymous Key Authentication Based Blum Goldwasser Cryptography For Cloud Data Access Security

Cloud computing is an advanced technology for secured access with available resources. One of the fundamental security needs of data sharing is to guarantee the cloud server could fully control access to an unauthorized entity. In cloud, achieving flexible access of data and protecting privacy of receivers remains challenging issues. To deal with these challenges, a novel technique called Tversky Anonymous Key Authentication based Pseudo Randomized Blum Goldwasser Cryptographic Secured Data Access technique is introduced. The proposed Secured Data Storage technique includes five different steps such as the Registration phase, Anonymous key generation, Authentication, Encryption, and Decryption. Outcomes of Tversky Anonymous Key Authentication based Pseudo Randomized Blum Goldwasser Cryptographic Secured Data Access technique achieves greater secured data access in cloud than the conventional methods.
UPAYA PENINGKATAN MINAT BACA MELALUI PERINTISAN RUMAH BACA “ABDI” DAN PENDAMPINGAN BELAJAR DARI MAHASISWA UNTUK DESA MENDALO INDAH

The pioneering of the ABDI reading house (Asri, Baca and Inspirasi) was based on the low interest in reading students' books. Mendalo Indah Village, which is a village close to Jambi University, does not yet have a reading house. In addition, the Covid-19 pandemic has overwhelmed parents of students to teach their children, especially with relatively low mastery of technology. ABDI Reading House, as a form of student and lecturer concern for the surrounding environment, is here to provide solutions to the problems of reading interest and the needs of parents for their children's learning assistance. This program is implemented by a community service team from the Pharmacy Student Association of the Faculty of Medicine and Health Sciences in collaboration with lecturers. The Village Head of Mendalo Indah provides a house to be used as a reading house and is supported by the provision of reading houses by funding from Jambi University through the Village Development and Empowerment Holistic Program (PHP2D). Learning assistance is carried out every day offline according to community demand by establishing health protocols and learning is carried out interactively with the play while learning method. This dedication has given birth to reading houses with various facilities and an increase in the number of visits to reading houses. The community feels very helped by the presence of the ABDI reading house in Mendalo Indah Village.
Grasp on next generation security operation centre (NGSOC)

With the growing number of cyber security threats affecting the business environment of many organizations, especially the IT environment. With the growing number of cyber security threats affecting the business environment of many organizations, especially the IT environment. Managed protection systems, including SOC, are highly sought after. Managed protection systems, including SOC, are highly sought after. The problem with SOC is that when building up their own SOC or hiring a third-party to provide SOC, organizations are not able to apply adequate criteria or standard frameworks. The aim of the study is to lay the foundations for developing a modern system of systematic operation centers for the next generation (NGSOC) for IIoT climate. This paper contains thorough, qualitative literature survey on the implementation of a Security Operation Centre (SOC). A comparative study is carried out using a variety of previous research sources and a literature review. The findings from the report show that previous research is not adequately guided, especially in the safety and technical aspects of the building block of the SOC. It is hoped that by proposing the framework, cybersecurity threat prevention and identification would be strengthened even further. The success of the NGSOC will ultimately be determined by the integration of individuals, procedure, and technology.
Pre-training and multi-task training for federated keyword extraction

Abstract The generalization ability of supervised model is relatively weak in keyword extraction technology. In order to effectively improve the robustness and accuracy of the model, the key to overcome this problem is collect more data for training process. However, the text as an privacy information, it is harder and harder to collect. To solve this problem, we apply federal learning to use user privacy data locally to improve the keyword extraction performance. In order to integrate the unlabeled user utterances to the semantic parsing model, we proposed a Pre-training and multi-task based federated keyword extraction model. The user models learn local information via unsupervised setting and the core model learns the supervised setting.
Fast Mining of Top-k Frequent Balanced Association Rules

Association rule mining (ARM), as a basic data mining task, aims to find association rules that satisfy predefined parameters from a given database. However, traditional ARM algorithms always generate a huge number of rules in many cases, which will greatly limit the usefulness of the mining results. Considering the unintuitiveness of setting parameters, algorithms have been designed to mine the top-k rules with the highest support that meet a minimum confidence. But it is not comprehensive to evaluate the strength of rules only by support and confidence. In some specific applications, the balance of rules also plays a decisive role in the actual effect. To address this issue, this paper proposes a top-k frequent balanced association rule mining algorithm named TFBRM (Top-k Frequent Balanced Rule Miner), which uses support, kulczynski (kulc) and imbalance ratio (IR) as measures. The algorithm employs three effective pruning strategies to reduce the search space. Experiments were conducted to evaluate the efficiency of TFBRM, and TFBRM has good scalability, which can be used in many applications.
[Analysis of the Continuous Heavy Pollution Process in the Winter of 2016 in Beijing, Tianjin, and Hebei].

From December 16 to 21, 2016, continuous heavy haze occurred in the Beijing-Tianjin-Hebei region of China. To further understand the development mechanism of haze and improve the forecasting of haze events, a variety of data, background circulation, and the meteorological elements of this severe haze process were comprehensively analyzed. The results show that the process lasted for a long time, pollution intensity was high, influence area was wide, visibility was low, and external transport was the main cause. Aerosols were mainly distributed at a height of 600 m, and there was a certain extreme anomaly. The static weather index and air quality index showed a strong correlation. The air in the Beijing-Tianjin-Hebei region is controlled by zonal circulation in front of a high-pressure ridge, which maintains the westerly airflow. Cold-air activity is weak, and downflow is dominant. The water vapor content is low, the cloud cover is limited at high altitudes, and a warm ridge extends northwards at low altitudes. Limited static wind on the ground, high relative humidity, and low mixing-layer height are not conducive to the horizontal and vertical diffusion of pollutants.