Reviewerly/exHarmony huggingface dataset:
Gye, William Ewart - Biographical entry - Index to the AMA archive

Gye, William Ewart - Biographical entry - Index to the AMA archive - NAME is a biographical, bibliographical and archival database of SUBJECT with links to related articles and images. ADD MORE DESCRIPTION AS REQUIRED
Graduates Perception on Job Search: A Critical Review

Background:The impact of the increased popularity of the internet as a platform to search for jobs may benefit every job seeker as an alternative to generate employment opportunities. Graduates that emphasize on general skills have a higher likelihood of disparitywhile searching for jobs.&#x0D; Objectives:This paper explores graduates’ perceptionson the knowledge of how to search for jobs from relevant sourcesr.&#x0D; Methods:The theoretical review focuses on job search strategies, job choices and job accessibility through different sources, highlights the usefulness of job portals for job seekers to find the right job as per their skills and requirements. The existing literature has observed that many job search behaviors through different sourceshas been performed and these behaviors indicate that awareness level affects job seekers’ intentions to apply for jobs. Empirical studies indicate that thechoice of job search by graduates match between a worker’s education and job offered.General skills have a higher likelihood of mismatch at job searches in different countries.&#x0D; Findings:Still in many developing countries, due to lack of awareness of job portals, people are not getting the right jobs and alternatives of their current jobs by different sources.&#x0D; Conclusions:A comprehensive study on applicability of the internet job search is useful for employers, considering the introduction of new graduate recruitment programmers. It is also useful for those wishing to improve their existing ones as well as for institutions of higher education, to reconsider the type of knowledge and skills they provide in order to prepare their students for the real world of work.&#x0D; Implications: Graduates require proper awareness on job search sites and the concerned industry should focus on it as well.
LibGuides: Language and Literacy Education: News & Magazines

This guide is for the subject Language and Literacy Education. It contains resources available in the NCU Library.
Quantifying the Effects of Recommendation Systems

Recommendation systems today exert a strong influence on consumer behavior and individual perceptions of the world. By using collaborative filtering (CF) methods to create recommendations, it generates a continuous feedback loop in which user behavior becomes magnified in the algorithmic system. Popular items get recommended more frequently, creating the bias that affects and alters user preferences. In order to visualize and compare the different biases, we will analyze the effects of recommendation systems and quantify the inequalities resulting from them.
Information needs and sources on food and nutrition security among farmers in Chamwino District, Tanzania

This study has investigated information needs and source on food and nutrition security in Chamwino District, Tanzania. The study employed a descriptive research design in which a mixed research approach has been followed to collect data using questionnaires and Focus Group Discussions (FGDs) from a sample of 84 respondents. The study employed a stratified random sampling to collect data from farmers. In general, the study’s findings reveal that crops processing, storage, and preservation and climate change are the areas on which farmers need information most. The findings further signify that friends, radio, and mobile phones are sources of food and nutrition security information considered effective by respondents. The study’s findings further indicate that access to food and nutrition security information in the study area is affected by various factors including income and education levels. Based on its results, the study recommends employing mechanisms that suit the population in the area when providing information. Apart from that, it is recommended that farmers receive information literacy lessons to enable them to more effectively seek and use information.
The Use of Make A Match Method to Increase Mechanical Engineering Student’s Vocabulary

The low understanding of machine student Vocabulary on machining terms in English requires an appropriate method to overcome them. This study aims to apply the use of Make A Match method to improve students learning outcomes in mastering Vocabulary. The subject in this study is students of Mechanical Engineering Study Program of Politeknik Harapan Bersama Tegal, about 30 students. The determination of this sample is based on the results of preliminary research on the class to be studied and the results of referrals from lecturers. While the object of this research is the effect of using the Make A Match learning method in Vocabulary mastery to increase student learning outcomes in English subjects. The implementation of the stages of activities carried out in 2 cycles. The research was carried out in the odd semester of the 2019/2020 academic year from November to December 2019. The first cycle was conducted in the third and fourth weeks of November while the second cycle was carried out in the fifth week of November and the first Sunday in January. This research is CAR consisting of two cycles with stages of planning, action, observation, and reflection. Both cycles use the application of the Make A Match learning model. Before the first cycle of learning is implemented to describe the initial conditions of students before getting action after the implementation of activities that end with evaluation activities through written tests for each cycle. The results of the research show that the initial ability of students before getting an action scores an average of 65 and a percentage of completeness of 60%. In cycle 1 there was an increase in the average value to 69 with a percentage of completeness of 75%. In cycle 2 there was an increase in the average score to 75 and the completeness reached 87%. And the results of the study showed an increase in achievement in English courses which was very significant, that is 87% of 30 students scored 70 in accordance with the specified minimum value. And student responses to the learning process are in the positive category.
What Changed Your Mind: The Roles of Dynamic Topics and Discourse in Argumentation Process

In our world with full of uncertainty, debates and argumentation contribute to the progress of science and society. Despite of the increasing attention to characterize human arguments, most progress made so far focus on the debate outcome, largely ignoring the dynamic patterns in argumentation processes. This paper presents a study that automatically analyzes the key factors in argument persuasiveness, beyond simply predicting who will persuade whom. Specifically, we propose a novel neural model that is able to dynamically track the changes of latent topics and discourse in argumentative conversations, allowing the investigation of their roles in influencing the outcomes of persuasion. Extensive experiments have been conducted on argumentative conversations on both social media and supreme court. The results show that our model outperforms state-of-the-art models in identifying persuasive arguments via explicitly exploring dynamic factors of topic and discourse. We further analyze the effects of topics and discourse on persuasiveness, and find that they are both useful - topics provide concrete evidence while superior discourse styles may bias participants, especially in social media arguments. In addition, we draw some findings from our empirical results, which will help people better engage in future persuasive conversations.
THE USE OF TWO STAY – TWO STRAY THROUGH MANGA ON THE STUDENTS’ ACHIEVEMENT IN READING COMPREHENSION

This study dealt with the use of two stay – two stay through manga on the students’ achievement in reading comprehension. This study was conducted at  SMP Negeri 1 Gebang on Jalan Medan – Pangkalan Berandan  Kecamatan Gebang Kabupaten Langkat at eighth grade. The sample ware taken by using random sampling technique. The number of sample were 34 students. The method of research applied classroom action research. It was applied to figure out the students’ activity during the use of two stay – two stray through manga on students in reading comprehension. The instruments of this research were observation sheet and a reading comprehension test which consisted of 10 questions Multiple choice test. The researcher conducted two cycles in this research, there were three meetings in cycle 1 and 1 meeting in cycle 2. The quantitative data showed that the mean score in cycle 1 was 45.00, the mean score in cycle 2 was 86.76, the students who got score more than 70 in cycle 1 were 6 students and the percentage was 17.64%, the students who got score more than 70 in cycle 2 were 34 students and the percentage was 100%. The qualitative data got from observation sheet in every cycle showed that the improvement of teacher and students’ behaviour. Based on finding of the results from data the use of two stay – two stray method improved the students’ achievement in reading comprehension. Keywords : Two Stay – Two Stray , Reading, Manga, Narrative Text
Crimean War - Subject - Index to the AMA archive

Crimean War - Subject - Index to the AMA archive - NAME is a biographical, bibliographical and archival database of SUBJECT with links to related articles and images. ADD MORE DESCRIPTION AS REQUIRED
Models for hyper-converged cloud computing infrastructures planning

The Data Centre concept has evolved, mainly due to the need to reduce expenses with the required physical space to store, provide and maintain large computational infrastructures. The Software-Defined Data Centre (SDDC) is a result of this evolution. Through SDDC, any service can be hosted by virtualising more reliable and easier-to-keep hardware resources. Nowadays, many services and resources can be provided in a single rack, or even a single machine, with similar availability, considering the deployment costs of silo-based environments. One of the ways to apply the SDDC into a data centre is through hyper-convergence. Among the main contributions of this paper are the behavioural models developed for availability and capacity-oriented availability evaluation of silo-based, converged and hyper-converged cloud computing infrastructures. The obtained results may help stakeholders to select between converged and hyper-converged environments, due to their similar availability but with the particularity of having lower deployment costs.
Pelatihan desain busana berbasis Adobe Photoshop

The partner of this Community Partnership Stimulus Program (PKMS) was The teachers fashion city of Makassar. The problem is lack of knowledge and skills of the teachers and based in design and adobe photoshop.Methods used is: lectures, demonstration, discussion, demonstration and practices directly.Achieved results is ( 1 ) partners have knowledge with design and use application adobe phtoshop, ( 2 ) participants in the jump join the is characterized by the number of participants accordance with the target planned.
Pendampingan Pemanfaatan Duolingo melalui Smartphone Sebagai Alat Pengajaran dan Pembelajaran Bahasa Inggris Bagi Masyarakat

The community service activity is aimed at providing a great command of Duolingo application for English teacher and MA Miftahul Ulum Pagendingan students where the application can be utilized as an interesting English teaching and learning tool. The method employed in this activity is training and mentoring regarding the utilization of Duolingo application through Smartphone. The activity of the service is desperately provide pedagogical commands for all participants how to teach or learn English in an interesting way that is by using Duolingo application. The participants consider that educational Duolingo application is extremely beneficial when to be utilized in English teaching and learning process in classroom.
Development of an Efficient Skill-Training Method Focusing on Visual Information

In order to train multi-skilled workers in a limited training period, efficient skill-training is one of the urgent tasks for manufacturing companies and also for vocational training centers. In this paper, we propose a new skill training method, which develops trainee’s understandings with a small amount of daily paper test focusing on visual information. The test is about photos and details of operations at each working scene. Trainee are requested to make scenario of a given task. Trainee’s misunderstandings can be revealed through the test. We applied the proposed training method to machining-skill training course using lathe, milling cutter and NC lathe. It is verified that trainee can acquire higher skills through the proposed method compared to the conventional one.
Language Phenomenon in Classroom Learning Process: A Study at MAN Model State Islamic Senior High School Gorontalo

This present study is devoted to investigating the language phenomenon focusing on spoken communication during the classroom learning at MAN Model State Islamic Senior High School, Gorontalo. Employing a descriptive qualitative method, the data of this study encompassed the utterances of the teacher and students during the classroom learning, specifically in UN (national examination) subjects. The data were generated by a conversation method with its basic techniques, i.e., recording, and note-taking. Furthermore, the data were qualitatively analyzed by (1) transcribing the recording into a written discourse, (2) grouping the data according to the problem statement, (3) examining the data, and (4) summing up. This study successfully identifies four strategies used during the communication process in a classroom learning; the strategies are (1) bald on record, (2) positive politeness, (3) negative politeness, and (4) off record.
Deep Gated Networks: A framework to understand training and generalisation in deep learning

Understanding the role of (stochastic) gradient descent (SGD) in the training and generalisation of deep neural networks (DNNs) with ReLU activation has been the object study in the recent past. In this paper, we make use of deep gated networks (DGNs) as a framework to obtain insights about DNNs with ReLU activation. In DGNs, a single neuronal unit has two components namely the pre-activation input (equal to the inner product the weights of the layer and the previous layer outputs), and a gating value which belongs to $[0,1]$ and the output of the neuronal unit is equal to the multiplication of pre-activation input and the gating value. The standard DNN with ReLU activation, is a special case of the DGNs, wherein the gating value is $1/0$ based on whether or not the pre-activation input is positive or negative. We theoretically analyse and experiment with several variants of DGNs, each variant suited to understand a particular aspect of either training or generalisation in DNNs with ReLU activation. Our theory throws light on two questions namely i) why increasing depth till a point helps in training and ii) why increasing depth beyond a point hurts training? We also present experimental evidence to show that gate adaptation, i.e., the change of gating value through the course of training is key for generalisation.
21st Century Skills; The Effect of Project Based Learning to Financial Literacy on Children Aged 5-6 Years

Financial Literacy has a very significant role in determining a person's level of welfare. Financial literacy education must be given from an early age because at this age children are in the golden period so that children can obtain basic financial knowledge and expertise to manage financial resources effectively and wisely by following future needs. At present financial literacy education is still taboo to be taught to young children so that financial literacy education is rarely done either in the family or school environment. To overcome this problem, this study proposes Project Based Learning as an effort to improve the financial literacy abilities of young children, especially children aged 5-6 years. The effectiveness of the Project Based Learning Model was evaluated by designing learning activities carried out through the financial literacy game with the quasi experiment method in 48 children aged 5-6 years. Two variables: Project Based Learning Model and financial literacy. The results showed that there was an increase in financial literacy children aged 5-6 years by 66.67%.
Mac Lane’s Comparison Theorem for the Kleisli Construction Formalized in Coq

Abstract (co)Monads are used to encapsulate impure operations of a computation. A (co)monad is determined by an adjunction and further determines a specific type of adjunction called the (co)Kleisli adjunction. Mac Lane introduced the comparison theorem which allows comparing these adjunctions bridged by a (co)monad through a unique comparison functor. In this paper we specify the foundations of category theory in Coq and show that the chosen representations are useful by certifying Mac Lane’s comparison theorem and its basic consequences. We also show that the foundations we use are equivalent to the foundations by Timany. The formalization makes use of Coq classes to implement categorical objects and the axiom uniqueness of identity proofs to close the gap between the contextual equality of objects in a categorical setting and the judgmental Leibniz equality of Coq. The theorem is used by Duval and Jacobs in their categorical settings to interpret the state effect in impure programming languages.
Colwell, Alan Rudford - Biographical entry - Index to the AMA archive

Colwell, Alan Rudford - Biographical entry - Index to the AMA archive - NAME is a biographical, bibliographical and archival database of SUBJECT with links to related articles and images. ADD MORE DESCRIPTION AS REQUIRED
MacGillicudy, Daniel Florance - Biographical entry - Index to the AMA archive

MacGillicudy, Daniel Florance - Biographical entry - Index to the AMA archive - NAME is a biographical, bibliographical and archival database of SUBJECT with links to related articles and images. ADD MORE DESCRIPTION AS REQUIRED
Accumulated Polar Feature-based Deep Learning for Efficient and Lightweight Automatic Modulation Classification with Channel Compensation Mechanism

In next-generation communications, massive machine-type communications (mMTC) induce severe burden on base stations. To address such an issue, automatic modulation classification (AMC) can help to reduce signaling overhead by blindly recognizing the modulation types without handshaking. Thus, it plays an important role in future intelligent modems. The emerging deep learning (DL) technique stores intelligence in the network, resulting in superior performance over traditional approaches. However, conventional DL-based approaches suffer from heavy training overhead, memory overhead, and computational complexity, which severely hinder practical applications for resource-limited scenarios, such as Vehicle-to-Everything (V2X) applications. Furthermore, the overhead of online retraining under time-varying fading channels has not been studied in the prior arts. In this work, an accumulated polar feature-based DL with a channel compensation mechanism is proposed to cope with the aforementioned issues. Firstly, the simulation results show that learning features from the polar domain with historical data information can approach near-optimal performance while reducing training overhead by 99.8 times. Secondly, the proposed neural network-based channel estimator (NN-CE) can learn the channel response and compensate for the distorted channel with 13% improvement. Moreover, in applying this lightweight NN-CE in a time-varying fading channel, two efficient mechanisms of online retraining are proposed, which can reduce transmission overhead and retraining overhead by 90% and 76%, respectively. Finally, the performance of the proposed approach is evaluated and compared with prior arts on a public dataset to demonstrate its great efficiency and lightness.
Manipulating Reinforcement Learning: Poisoning Attacks on Cost Signals

This chapter studies emerging cyber-attacks on reinforcement learning (RL) and introduces a quantitative approach to analyze the vulnerabilities of RL. Focusing on adversarial manipulation on the cost signals, we analyze the performance degradation of TD($\lambda$) and $Q$-learning algorithms under the manipulation. For TD($\lambda$), the approximation learned from the manipulated costs has an approximation error bound proportional to the magnitude of the attack. The effect of the adversarial attacks on the bound does not depend on the choice of $\lambda$. In $Q$-learning, we show that $Q$-learning algorithms converge under stealthy attacks and bounded falsifications on cost signals. We characterize the relation between the falsified cost and the $Q$-factors as well as the policy learned by the learning agent which provides fundamental limits for feasible offensive and defensive moves. We propose a robust region in terms of the cost within which the adversary can never achieve the targeted policy. We provide conditions on the falsified cost which can mislead the agent to learn an adversary's favored policy. A case study of TD($\lambda$) learning is provided to corroborate the results.
Knowledge Based Image Segmentation with Semantic Concepts

Image processing is an innovative area of research in information processing. Within a short duration to holds are steps in every part of human life. Among them image identification and retrieval is the common task to access the desired image from the image databases. Towards its advanced journey image segmentation is a complex as well as and necessary task in knowledge bases image processing system. It segments or divides an image into regions and the labelling of the regions is a challenging problem. In this paper we have analysed various methods on knowledge based semantic segmentation and labelling of images. In this comparative analysis every methods has the vague and complex process. Such complexity motivates to propose a new light weight model to segment the image with necessary conceptual approaches to obtain a fruitful output. The model to be experimented in future with a adopted labelling and segmentation with semantic features in the generation of semantic codebook. This code book will provide and efficient performance in segmentation and also for other related processing.
Smart Automated Cart

Now a days, world is moving towards the Automation. Each and every field is using automation technologies for efficient work. The proposed methodology which can transfer objects from one place to another in workplaces like offices, hospitals, hotels, airports , etc. automatically. The key point of this proposed system is that only authorized persons will get access to that transferred object using the RFID tag. The proposed system uses the technique of Automated Guided Vehicle (AGV).