Reviewerly/exHarmony huggingface dataset:
Ethical Leadership and Knowledge Management Behaviors: Role of Organizational Citizenship Behavior and Procedural Justice

A growing body of literature is focused on analyzing the impact of leadership styles on various organizational behaviors. Although in knowledge management literature studies have shown a statistically significant impact of any leadership style on knowledge sharing but the literature on hiding is still scarce. This study is an attempt to bridge this gap in literature by focusing on ethical leadership and the impact it has on the knowledge sharing and knowledge hiding of the employees. Organizational citizenship behavior is included as mediator in the study as it is observed from past literature that employees like to emulate the behavior of their supervisor. The model of the research study also suggests for the moderation effects of procedural justice. Ethicality of the leader results in higher organizational citizenship behavior which in turn enhances the knowledge sharing and hinders the knowledge hiding behavior of the employees. It was also found that procedural justice moderates the relationship.
Shaw University Library Guides: Remote Services & Access: Databases & eArticles

This guide describes the services the library offers that can be utilized remotely and how to access them.
Motivation of Students in the Learning English through Audio Visual Media

This study aims to determine the motivation of students in learning English through audio visual media in the eleventh grade at MA Al Amiriyyah Blokagung Banyuwangi then describe how motivation is used in learning English by using audio Audio Visual Media in the form of video. Furthermore, this study also aims to determine whether it is true that it maximally motivates students by using audio visual media. This research uses a descriptive method with a qualitative design, to collect data, the researcher uses several instruments, among others; (1) Observation, (2) Questionnaire, (3) Interview. The subjects of this research were 15 eleventh grade students at MA Al Amiriyyah Blokagung Banyuwangi where these class students were placed in a special dormitory in the form of the Syafa�atul Qur�an dormitory. The results showed that (1) student motivation can be said to be in a good category, according to the results of all these findings the researcher concluded that the motivation to learn English is 80.00% of the questionnaire results which can be said to be in "good motivation". Besides, from the results of the interview, the researcher concluded that student motivation in learning English was quite good. Students' motivation to learn in English is because the atmosphere is pleasant, the teacher delivers the material well and the material is easy to understand, (2) the factors behind the motivation to learn English besides liking the atmosphere in the English classroom, the teacher also combines methods and media in carrying out the learning process, so that students felt confident that it would be easy to understand and learn the material even though they are not yet speak properly due to very minimal vocabulary,
Fourh Industrial Revolution Technology and Human Rights Protection - Focusing on the Use of Blockchain Technology in Humanitarian Activities

Not enough attention has been given to the positive potential of Fourth Industrial Revolution technology to protect and promote human rights. The purpose of this article is to examine the bright side of this technology through the specific example of its use in humanitarian activities using the case of the World Food Programme’s Building Blocks Project. A blockchain is a form of Distributed Ledger Technology that records data in multiple nodes simultaneously. This decentralization feature enables reducing transaction costs by eliminating intermediaries such as financial institutions, and increases security through the transparency of transactions and consensual mechanisms. The features of decentralization, transparency, and security together increase the efficiency of humanitarian assistance while providing an opportunity to establish digital identity. This is important because digital identity would ultimately serve as the basis for realizing the rights of forcibly displaced people, including refugees, who have been prevented from accessing basic rights because they lack proof of identity. However, like all other new technologies, blockchain has met with reproach as well as reverence. There are concerns such as conflict with the principle of privacy protection, the interest of the tech developer, insecurity of decentralized digital currency, as well as the criticism leveled against blockchain technology itself that it lacks energy efficiency. Such concerns are prima facie based on the uncertainty inherent in new technologies. Therefore, realization of the possibilities and limitations of blockchain technology will largely depend on its further development and use.
ROAD SIGN RECOGNITION AND ANNOUNCEMENT USING MACHINE LEARNING

The main purpose of the project is to create a road sign detection system which detects road signs anddisplays and announces it to the driver. In order to solve the concerns over road and transportation safety, roadsign detection and recognition system is required. The system should detect and recognize road signs from andwithin images captured by cameras or imaging sensors. In adverse road conditions, the driver may not notice roadsigns, which may cause accidents. In such scenarios, the system comes into action and recognizes the signs andannounces it to the driver.
ENT 530 Social Media Portfolio / Nur Zahirah Na'im

The assignment is the study on how to run a business by using the social media. I have chosen a business to be run by me which is a business of selling many flavor of cakes such as brownies, red velvet, carrot, pastry fruit and chocolate 'berhantu' . By doing this business, I have learned on how to control and promote our products by using social media which is Facebook. Facebook is a social networking and e-commerce site that makes it a strategic platform for entrepreneurs to market their products or services. While doing this assignment, I have learned on how to create sale postings by using teaser, and hard sell. Actually, an entrepreneur has to be proficient when closing sales using effective soft sell to anwers customer's enquiries. Moreover, I have learned on how to attract our customers and introduce our product to the customers. We need to set our customers target in oder to make sure that our business running smoothly. We must know what customers want. We also need to know how to handle the upcoming problems.
The Application of Action Oriented Teaching Method in the Computer Teaching Reform of Colleges and Universities

In the computer teaching reform of colleges and universities, teachers combine their different learning characteristics with the teaching materials structure of National University, and create a variety of teaching situations for students by means of modern simulation teaching method, and stimulate students' interest in computer science and technology research. Then, the teaching methods of task, project and brainstorming are taken as action guidance to guide students to explore the relationship between computer operating system and scientific and technological work in various forms of teaching activities, so that they can find more scientific and technological knowledge in the process of computer operation exercise and accumulate more computer operation experience in the ocean of scientific and technological knowledge. It is not only conducive to improve the students' communication ability of cooperation with people, to train the students' computer practical operation ability, but also to cultivate students' self-study consciousness, to develop good learning habits, and to consolidate their comprehensive ability.
Class Specific Interpretability in CNN Using Causal Analysis

A singular problem that mars the wide applicability of machine learning (ML) models is the lack of generalizability and interpretability. The ML community is increasingly working on bridging this gap. Prominent among them are methods that study causal significance of features, with techniques such as Average Causal Effect (ACE). In this paper, our objective is to utilize the causal analysis framework to measure the significance level of the features in binary classification task. Towards this, we propose a novel ACE-based metric called “Absolute area under ACE (A-ACE)” which computes the area of the absolute value of the ACE across different permissible levels of intervention. The performance of the proposed metric is illustrated on (i) ILSVRC (Imagenet) dataset and (ii) MNIST data set $(\sim 42000$ images) by considering pair-wise binary classification problem. Encouraging results have been observed on these two datasets. The computed metric values are found to be higher - peak performance of 10x higher than other for ILSVRC dataset and 50% higher than others for MNIST dataset - at precisely those locations that human intuition would mark as distinguishing regions. The method helps to capture the quantifiable metric which represents the distinction between the classes learnt by the model. This metric aids in visual explanation of the model’s prediction and thus, makes the model more trustworthy.
Lars Lyberg, (1944–2021)

Lars was born near Stockholm on 1 December 1944 and passed away on 9 March 2021 after a long battle with pancreatic cancer. He spent much of his early life in Stockholm where he studied statistics at Stockholm University, gaining a Doctorate under the supervision of Tore Dalenius. Like most Swedes, he had a stint of military service. He started his professional work career at Statistics Sweden in 1966 and spent the next 44 years there, culminating in his appointment as head of the Research and Development Department. After retiring from Statistics Sweden, he worked as a consultant in survey methods and quality management. Since 2003, he taught at Stockholm University with professorial status in recognition of his past contributions. He had many interests besides statistics especially sport where he had encyclopaedic knowledge not just about Sweden. He was an excellent tennis player in his younger days. Although modest by nature, he was generous of his time especially to young survey researchers. He was always a careful listener, often leaving his contribution to discussions to the end after hearing what others had to say. I first met Lars in 1983 while visiting Statistics Sweden and connected immediately. We exchanged knowledge on statistical methods gained through work in our respective statistical organisations and met regularly after this first meeting, enjoying watching live sporting contests as well as televised matches over a few beers. Lars is survived by his partner Lilli Japec, a fellow statistician at Statistics Sweden, who became head of Research and Development subsequent to Lars’s retirement. He had two adult sons, adopted from Bolivia during his first marriage. Lars was tall and blonde, whereas his sons were short and dark. It made for interesting discussions at immigration posts when travelling with his sons.
Sistem Informasi Distribusi Bank Sampah Berbasis Website With Oil Counter Pada Bank Sampah Melati Bersih Tangerang Selatan

Waste bank in principle operates like a bank in general, in the process customers come saving garbage and at a predetermined time can withdraw money from the waste that has been saved by the customer. Waste is waste material produced from household waste, offices and others. Then it needs to be handled in addressing problems caused by garbage, one of which is with the existence of waste banks. Processed waste in the form of organic waste such as, plastic waste, paper, metal and others. The waste is processed into various handicrafts or sold to other parties to be used as raw materials. In the processing of data in the waste bank is still done by manual that is written on the general ledger or agenda book. The officer must record every time a transaction occurs. Therefore we are interested to create a waste bank distribution information system with oil counter that can help officers in the transaction process and customers check the balance independently
Fake online videos growing corporate threat: Cybersecurity expert

A cyber security expert says U.S. corporations may becoming more susceptible to the threat and harm caused by bogus online videos.
Survey On Advanced Biometric Systems For User Authentication

The world is now more connected than ever before thanks to advances in web technology. However, the internet's deep roots necessitate the development of foolproof cybersecurity methods. The most commonly used authentication method during this time is something the individual knows such as pin's, passwords, or something the individual possesses such as Smartcards. However, in these cases an adversary is capable of guessing a password or borrowing the device. There’s a chance for customer to forget the password or misplace the device. Adding to this there is humongous cost of managing the distribution of these devices and securing the passwords from various attacks. To overcome these issues something the individual” Biometric authentication has been introduced. A biometric authentication authenticates an individual primarily based on their particular biological characteristics and we see that this has been widely accepted in today's world. In this paper, we have mentioned, few of the advanced biometric technologies and their working and their performance. We also discuss the challenges associated with this system and various schemes to overcome them.
Implementation of Embedded Unspecific Continuous English Speech Recognition Based on HMM

Background: To improve the usage of computers, a very important role is played by the Human-computer interaction through Natural Language Conversational Interfaces. Speech recognition technology allows the machine to understand human language. To achieve this function, a speech recognition algorithm is used. Methods: In order to realize the embedded speech recognition function based on HMM under the ARM platform, this paper, mainly based on the basic theoretical research of speech signals, establishes the HMM model, uses speech collection, recognition and other methods, simulates on MATLAB, and integrates the recognition system ported to ARM for debugging and running. Results: The research results show that the accuracy of HMM model experimental recognition can reach 98%, and the speed of speech recognition simulation on ARM is faster than speech recognition. The innovation of this paper is to make a comprehensive system introduction to embedded speech recognition from the perspective of embedded systems, and perform speech recognition simulation on MATLAB. Conclusion: The conclusion shows that the HMM-based embedded unspecific continuous English speech recognition system has high recognition accuracy and fast speed.
Probability and statistics in the physical sciences, 3rd edition

"Probability and statistics in the physical sciences, 3rd edition." Contemporary Physics, 62(1), pp. 63–64
Clausal Arguments and Peripheries in ASD-STE100

One of the main objectives of Natural Language Processing is the simulation of natural language understanding. Within its applications, ARTEMIS (Automatically Representing TExt Meaning via an Interlingua-Based System) is theoretically grounded in RRG, whose linking algorithm lies at the basis of our interlingua-based system. A fundamental component of ARTEMIS is the GDE module, where feature-based production rules and AVMs are stored to allow the generation of natural language expressions. Production rules for phrasal constituents, simple sentences and adverbial subordinates have already been described, but it is now turn to delve into other types of complex structures and generally contribute to the enhancement of parsing rules for clausal subordination in ARTEMIS. Bearing in mind the validation process these production rules should undergo, as well as the common problems that may arise in such parsing applications, our research will concentrate, precisely, on the analysis of these subordinate structures as found in a CNL like ASD-STE100
Effect Handlers, Evidently

Algebraic effect handlers are a powerful way to incorporate effects in a programming language. Sometimes perhaps even _too_ powerful. In this article we define a restriction of general effect handlers with _scoped resumptions_. We argue one can still express all important effects, while improving reasoning about effect handlers. Using the newly gained guarantees, we define a sound and coherent evidence translation for effect handlers, which directly passes the handlers as evidence to each operation. We prove full soundness and coherence of the translation into plain lambda calculus. The evidence in turn enables efficient implementations of effect operations; in particular, we show we can execute tail-resumptive operations _in place_ (without needing to capture the evaluation context), and how we can replace the runtime search for a handler by indexing with a constant offset.
Using speech technology in the translation process workflow in international organizations: A quantitative and qualitative study

In international organizations, the growing demand for translations has increased the need for post-editing. Different studies show that automatic speech recognition systems have the potential to increase the productivity of the translation process as well as the quality. In this talk, we will explore the possibilities of using speech in the translation process by conducting a post-editing experiment with three professional translators in an international organization. Our experiment consisted of comparing three translation methods: speaking the translation with MT as an inspiration (RESpeaking), post-editing the MT suggestions by typing (PE), and editing the MT suggestion using speech (SPE). BLEU and HTER scores were used to compare the three methods. Our study shows that translators did more edits under condition RES, whereas in SPE, the resulting translations were closer to the reference according to the BLEU score and required less edits. Time taken to translate was the least in SPE followed by PE, RES methods and the translators preferred using speech to typing.These results show the potential of speech when it is coupled with post-editing.To the best of our knowledge, this is the first quantitative study conducted on using post-editing and speech together in large scale international organizations.
OBJECT RECOGNITION FROM VIDEO SEQUENCES IN REAL TIME USING DEEP LEARNING TECHNIQUES

In the field of computer vision, a wide range of applications has been developed for various purposes. Object recognition in images has always been a relevant task in this application domain. Nowadays, new methods have been developed to achieve greater accuracy and efficiency in the process of object detection. In this research, a comparative analysis of the main methods based on deep learning was carried out, which are among the most effective for object detection and classification.  It was proposed an implementation based on the YOLO algorithm for object recognition in video sequences, which uses the library for computer vision OpenCV. Experiments designed to validate the proposed solution were performed on two different computation nodes and the results obtained were analyzed according to the main metrics employed to evaluate the performance of object recognition methods.
Information and Social Networks as Immediate Factors of Migration

The Kembata-Tembaro, Hadiya and Welayta are one of the highly migratory zones in Ethiopia. While they all enjoy similarities along population densities, land holdings, agro-ecologies and employment opportunities; the migration patterns in these areas differ in that, while the first two are known for international migration mainly to the Republic of South Africa, the latter is known for its internal migration with few international migrations. The Migration Network Theory was adopted to assess the role of information and social networks in triggering migration and the role they played in shaping patters of migration from the study area. A descriptive research with mixed methods approach was employed. Results show the importance of information and social networks in triggering migration decisions, serving as immediate causes as opposed to the root causes of migration. This study has concluded that information and social networks have served as factors triggering migration from study area. Accordingly, it calls for separate migration policy responses and interventions at the root cause and immediate levels.
Earthquake Monitoring in Artificial Intelligence Era

Diverse algorithms have been developed for efficient earthquake signal processing and characterization. These algorithms are becoming increasingly important as seismologists strive to extract as much insight as possible from exponentially increasing volumes of continuous seismic data. Deep neural networks have been shown to be promising tools for this. We have developed a number of deep learning tools for more efficient processing and characterizing of earthquake signals. In my presentation, I demonstrate the performance of some of these tools applied to seismic data. AI-based techniques have the potential to improve our monitoring ability and as a result understanding of earthquake processes and hazards.
Geoelectric Investigations with Special Measurement Geometry to Delimit Prehistoric Mining Areas in Hallstatt

Summary The Hallstatt area in Austria has a very long history of salt mining, which was frequently interrupted by large landslides. Landslide material filled the prehistoric underground mining chambers and therefore conserved their dimensions. Within several geoelectric measurement campaigns, data from ground surface measurements and from geoelectric profiles in 2 mining tunnels from the 18th century were collected, resulting in a 3D data set of about 80,000 data points. The aim was to track a mining chamber of the Early Iron Age, which has been filled with landslide material. The already existing reconstruction of this mining chamber is based on several archeological excavation points and an interpolation in between. A collapsed mining shaft known from laser scan data has been confirmed beforehand with surface ERT measurements. Due to the high resistive salt rock and the hardness and dryness of the intruded landslide material, the Early Iron Age mining chamber could not be differentiated sufficiently. Instead, results could pinpoint that the mining chambers are following the area of the highest electrical resistivity, which is determined as “Haselgebirge” in geological maps. Therefore, indications of the location of the Early Iron Age mining chamber, where no archaeological finds exists until now, could be given.
SplitGuard: Detecting and Mitigating Training-Hijacking Attacks in Split Learning

Distributed deep learning frameworks, such as split learning, have recently been proposed to enable a group of participants to collaboratively train a deep neural network without sharing their raw data. Split learning in particular achieves this goal by dividing a neural network between a client and a server so that the client computes the initial set of layers, and the server computes the rest. However, this method introduces a unique attack vector for a malicious server attempting to steal the client's private data: the server can direct the client model towards learning a task of its choice. With a concrete example already proposed, such training-hijacking attacks present a significant risk for the data privacy of split learning clients. In this paper, we propose SplitGuard, a method by which a split learning client can detect whether it is being targeted by a training-hijacking attack or not. We experimentally evaluate its effectiveness, and discuss in detail various points related to its use. We conclude that SplitGuard can effectively detect training-hijacking attacks while minimizing the amount of information recovered by the adversaries.