Reviewerly/exHarmony huggingface dataset:
Optimizing Investments in Cyber Hygiene for Protecting Healthcare Users

Cyber hygiene measures are often recommended for strengthening an organization's security posture, especially for protecting against social engineering attacks that target the human element. However, the related recommendations are typically the same for all organizations and their employees, regardless of the nature and the level of risk for different groups of users. Building upon an existing cybersecurity investment model, this paper presents a tool for optimal selection of cyber hygiene safeguards, which we refer as the Optimal Safeguards Tool. The model combines game theory and combinatorial optimization taking into account the probability of each user group to being attacked, the value of assets accessible by each group, and the efficacy of each control for a particular group. The model considers indirect cost as the time employees could require for learning and training against an implemented control. Utilizing a game-theoretic framework to support the Knapsack optimization problem permits us to optimally select safeguards' application levels minimizing the aggregated expected damage within a security investment budget. We evaluate OST in a healthcare domain use case. The Critical Internet Security Control group 17 for implementing security awareness and training programs for employees belonging to the ICT, clinical and administration personnel of a hospital. We compare the strategies implemented by OST against alternative common-sense defending approaches for three different types of attackers: Nash, Weighted and Opportunistic. Nash defending strategies are consistently better than the competing strategies for all attacker types with a minor exception where the Nash defending strategy performs at least as good as other common-sense approaches.
El espacio como estrategia en la biblioteca del siglo XXI

In the digital age, when everything seems to fade away and become bit streams, when digital relationships are built on anonymity; libraries around the world are opening their doors and inviting community members inside. Becoming a true connector to their communities. A new philosophy of the public building as a democratic space of law and coexistence that contributes to the modern concept of the intelligent city (Mersand et al. 2018). Today's library is both a physical and virtual place, but it is still the physical presence of the library that anchors it most firmly to the community (Garmer 2014). Research and experience show that geography and place still matter. The new libraries are the most striking example of the change that is taking place in public buildings, with cafeterias, stages, cozy seating areas and multipurpose spaces designed to accommodate creative spaces, dance and fitness classes, or public art exhibitions featuring contemporary works by the region's artists.
Design IP legislation in the UK

This paper constitutes a critical and detailed review of an investigation into design right infringement in the UK. The original mixed-method study was commissioned by the UK IPO in 2015/2016 and led by the author throughout the first three of four project stages. This paper focuses specifically on the results obtained in relation to registered design right infringement. The paper comprises the following points:&#x0D; &#x0D; A discussion of older studies in the area&#x0D; An outline of the research methodology deployed for the design right infringement survey&#x0D; A discussion and analysis of key research findings&#x0D; &#x0D; The conclusions drawn provide insight not only into how design rights are used and enforced in the UK. They also help to establish clarity about the level of robustness of design-related IP options. The paper provides orientation to designers and design IP stakeholders. It culminates in a range of ideas of how the IP system surrounding designs can be enhanced in the UK and in comparable countries.
Smart Data based Ensemble for Imbalanced Big Data Classification

Big Data scenarios pose a new challenge to traditional data mining algorithms, since they are not prepared to work with such amount of data. Smart Data refers to data of enough quality to improve the outcome from a data mining algorithm. Existing data mining algorithms unability to handle Big Datasets prevents the transition from Big to Smart Data. Automation in data acquisition that characterizes Big Data also brings some problems, such as differences in data size per class. This will lead classifiers to lean towards the most represented classes. This problem is known as imbalanced data distribution, where one class is underrepresented in the dataset. Ensembles of classifiers are machine learning methods that improve the performance of a single base classifier by the combination of several of them. Ensembles are not exempt from the imbalanced classification problem. To deal with this issue, the ensemble method have to be designed specifically. In this paper, a data preprocessing ensemble for imbalanced Big Data classification is presented, with focus on two-class problems. Experiments carried out in 21 Big Datasets have proved that our ensemble classifier outperforms classic machine learning models with an added data balancing method, such as Random Forests.
The Implementation of Teaching English Speaking Skill to Autism Students (A Case Study at The English Teaching Process at SKh Yayasan Karya Dharma Wanita 01 Tangerang)

Alpiyah Mufidah. 152301822. 2019. The Implementation of Teaching English Speaking Skill to Autism Students (A Case Study at The English Teaching Process at SKh Yayasan Karya Dharma Wanita 01 Tangerang) This research investigated on the implementation of teaching English speaking skill to autism students at SKh Yayasan Karya Dharma Wanita 01 Tangerang. The formulation of the research problems in this study were how does the teacher teaches speaking skill to autism students and what is the teacher’s difficulty in teaching English speaking skill to autism students. Thus, the purpose of this study were to identify teaching English speaking process and teacher’s difficulty. The research designed of this study was case study research with qualitative approach. The respondent of this study was one English teacher at SKh Yayasan Karya Dharma Wanita 01 Tangerang. The research instruments were observation, interview, and documentation. The research finding of this study that autism students were lack of comprehension and focus. The English teacher used strategies, approaches, methods, and media in teaching English speaking skill to autism students. The teacher used repetitive instruction, praise, and appreciation as strategies, the teacher used direct trial method, the teacher used picture and concrete object as media, the teacher used individual approach such as used one communication, staring eyes, hold the hand, and clear instruction. The teacher felt difficult when teaches autism students, it appeared when there was an autistic student fight and self-injury in learning process. The internal factors of teacher’s difficulties were the characteristics of autism students who difficult in comprhension and focus, the teacher must had ways own in teaching English. The external factors were nothing book and modules for special need students especially for autistic students. This problem made the teacher changed the material more simplifier and easier appropriate with students need. Key words: autism student and teaching speaking.
Distributed Accounting Resource Sharing Method Based on Internet

As the Internet enters thousands of households, it has spawned emerging network technologies such as big data and cloud computing, constantly shaping people’s lifestyles and changing the way people work. This paper analyzes the construction of accounting information resource sharing platform for enterprises in the Internet era, and discusses the positive effects and potential risks brought by enterprise accounting information sharing. The construction of accounting information resource sharing platform can provide enterprises with more advantageous resources, improve the efficiency of accounting information processing, and also expose enterprises to many risks at the technical level, information security level and personnel management level. Based on the distributed algorithm and centralized joint allocation algorithm, the game results of shared information resources are deducted. Based on this, a series of countermeasures and suggestions are proposed for how to prevent the outstanding risks in the construction of accounting information sharing and promote the construction of resource sharing platform. Therefore, the results of this study show that in order to improve the office efficiency of the accounting industry by using network data resources and platforms in the Internet era, it is necessary to start from cultivating human resources, improving relevant laws and regulations, corporate attention and policy support.
Research Guides: *Primary Sources: A Guide: Personal & Family Papers

A guide to identifying and locating primary sources for conducting research in history. Tips for using personal, or non-public, papers as primary sources, with links to collections of such papers online and in the FSU Special Collections.
Agile-Based Product Line Tool Development

The product line domain and agile software development created a well-received product line concept with complex toolchains and the agile development idea that fosters a rather pragmatic development style with less documentation. Both parts have been included in two student projects targeting the development of a configurator product line. This paper presents requirements for configurator product lines and evaluates the two projects towards these requirements. The positive results of the projects lead to the proposal to broaden the support and acceptance of special project types in the product line domain where the source code and structure is enough to understand and maintain the project. We even propose this to be the better solution.
Gamification –Doing Things With Fun: A Broader Perspective

Games are known to be one of the best source of entertainment and when it comes to improve the effectiveness and productivity in different functional areas, the induction of games in these arears play a significant role. Gamification is a pioneering approach thathas proven to be the best sought after technology today and is widely being adoptedin diverse domains across various sectors or disciplines. The sole purpose of Gamification is to add fun and joy to make different types of processes and practices more effective and more productive that include education,healthcare systems, tourism, business, etc. The present article intends to shed light on the findings and analysis of the literature review on gamification being explored by sundry researchers in different disciplines and in different contexts. The findings of this study introduce the concepts of gamification, gaming aspects, and different application domains where gamified scenarios are being explored by adding fun in order to achieve specified goals. Apart from that, the paper also highlights the recent trends and further research pointers to prospective researchers keen to pursue their research in the area of gamification.
The Effects of Openness to Experiences and Perception of Errors towards Perceived Creative Behavior, Creative Self-Efficacy, and Creative Identity

본 연구는 개인의 개방성과 실수에 대한 인식이 자신의 창의성에 대해 형성한 자기 인식에 미치는 영향을 확인하는 데에 목적이 있다. 창의적인 자기에 대한 인식은 자신의 행동, 자기효능감, 정체감 등 여러 측면에 대하여 형성될 수 있으며, 그 수준에 따라 향후 창의적 수행을 예측할 수 있다. 특히, 시행착오가 빈번하게 발생하는 창의성 발현 과정에서 개방성이 높은 성격과 실수에 대한 긍정적 인식은 창의적인 자기를 인식하는 데에 영향을 미칠 수 있다. 이에 본 연구에서는 대학생을 대상으로 개방성과 실수 인식이 세 가지 유형의 창의적인 자기 인식(창의적 행동, 창의적 자기효능감, 창의적 정체감)에 미치는 효과를 확인하였다. 연구 결과, 개방성과 실수 인식은 자신의 창의적 행동, 창의적 자기효능감, 창의적 정체감에 정적으로 유의한 영향을 미쳤다. 특히 창의적 정체감의 경우, 개방성과 실수 인식의 하위 요소 중 실수에 대한 도전과의 상호작용 효과가 확인되었다. 즉, 개방성이 낮은 경우 실수에 대한 도전 수준이 높을수록 창의적 정체감 수준이 높았다. 이러한 결과는 성격 특성 이외에 실수에 대한 인식이 창의적인 자기 인식의 형성에 유의한 설명력을 가지므로 실수 인식의 변화를 통해 창의적 수행을 이끌 수 있을 것이라는 시사점을 제시한다. 연구 결과와 함께 창의성 교육의 방향과 추후 연구에 대한 제언을 제시하였다.Creative processes with extensive trial and error, openness to experiences and a positive perception of errors and failures can influence creativity. In addition, the perception of personal creative behavior, ability, and identity can help to explain creative achievements. Therefore, the current study investigated relationships among openness to experience, perception of error, and perception of creativity (creative behavior, creative self-efficacy, and creative identity). Using a sample of 208 college students, a hierarchical regression analysis was performed in order to examine the relationships pertaining to openness to experiences, perception of errors, creative behavior, creative identity and creative self-efficacy. The results exhibited that students with high levels of openness to experiences perceived their creative behavior, creative identity, and creative self-efficacy more positively. Also, interaction effects between openness to experience and error risk taking were shown through creative identity. These findings suggest that it is necessary to change a students’ perception of error, and encourage students to pursue a more positive perception of their own creativity, which can finally lead to creative achievement.
Evaluation of Object Detectors in Online Videos

Object detectors based on deep convolutional networks generally have problems such as large amount of calculation, accuracy and speed of object detecor cannot have both, and it is difficult to achieve real-time object detection on embedded and mobile devices for online videos. Therefore, evaluating existing object detectors is an important issue that needs to be faced by a wide range of object detection applications. This paper proposes an evaluation method for object detectors in online video scenes. The method comprehensively considers the factors of the law of appeared objects, camera parameters, accuracy and speed of object detectors, and uses a combination of mathematical analysis and simulation experiments. On the Nvidia Jetson TX2 platform, the current major objects detectors have been analyzed and evaluated in detail using our evaluation method. The main evaluation results show that the YOLOv3 family is better than other object detectors and their variants such as SSD and RetinaNet, although it has not the highest accuracy, its fastest speed helps to occupy an advantage in the (different) object detection rate.
THE EFFECTS OF FACEBOOK UTILIZATION ON WRITING ACHIEVEMENT AND INTRINSIC MOTIVATION OF MUHAMMADIYAH UNIVERSITY’S UNDERGRADUATE STUDENTS

Facebook is one of the instances of web 2.0. It provides the opportunity to the user of that social media to develop writing skills by means of synchronous and asynchronous communication tools. The objectives of this study are three-fold: (1) to examine the effect of giving feedback through Facebook group on students’ writing achievement. (2) to scrutinize possible changes in students’ intrinsic motivation as a result of using facebook, and (3) to gauge students’ perceptions of using Facebook group in writing class. This study was conducted in Muhammadiyah University involving 120 students of English Study Program registered in academic years of 2014/2015. Purposive sampling technique was employed in recruiting the participants. This study was conducted using mixed method. Quantitave data originated from test scores & questionnaires. Qualitative data are obtained from in-depth interviews with sample participants. The researcher used thematic analysis in analyzing the results of the interview. In-depth interviews with sample students indicate that Facebook is perceived to be effective in improving their writing skills. Paired samples t-test shows that post-test scores are significantly higher than pre-test scores, -4.637 (31) 0.000 < 0.05 which in turn suggests that use of Facebook has resulted in improved writing skills. By the same token, students’ intrinsic motivation too undergoes a significant increase, -2.250 (31) 0.032 < 0.05.
Effects of data ambiguity and cognitive biases on the interpretability of machine learning models in humanitarian decision making

The effectiveness of machine learning algorithms depends on the quality and amount of data and the operationalization and interpretation by the human analyst. In humanitarian response, data is often lacking or overburdening, thus ambiguous, and the time-scarce, volatile, insecure environments of humanitarian activities are likely to inflict cognitive biases. This paper proposes to research the effects of data ambiguity and cognitive biases on the interpretability of machine learning algorithms in humanitarian decision making.
Genetic Algorithm for Virtual Machine Allocation using Server Power Profile

A Virtual Machine allocation problem is one of the interesting topics in cloud computing. The cloud service providers allocate computing infrastructure, such as a virtual machine which is configured with CPU, memory, bandwidth and storage capabilities. More than one virtual machines can run on a host and different types of hosts have varying efficiency in energy consumption. To reduce energy consumption, this paper proposes a Genetic Algorithm which is a search heuristic to find the order of hosts to be utilized so that energy consumption in cloud data center is minimized. Our technique is based on a formulated problem of resource allocation which consider energy consumption from the CPU of VMs and hosts. The simulation focuses on power profile for each type of hosts including genetic algorithm. The experimental results show that the proposed algorithm of two-point crossover performed well when hosts are similar, while the one-point crossover performed well when hosts are a mix of high and low idle power.
Morpho-Syntactic Analysis of NP Modifiers in Korean

This paper examines that distributional properties of three categories of NP modifiers –color, nationality, and material- in Koren and suggests that these NP modifiers show the peculiar behaviors in the domain of modification depending on their morphology. On a par with Watanabe’s (2012) analysis, in particular, I propose in this paper that the class of adjectives that express nationality and material is absent in Korean and that modifiers that are used as nationality and material adjectives are nouns like Japanese. Regarding color adjectives, also, uniquely they can be divided into two types in their modifier form: one is the type affixed with RRC (Reduced Relative Clause) marker –n and the other is the nominal form like nationality and material modifiers. Under morpho-syntactic perspective, more significantly, I address the intriguing issue that morphological variants of these NP modifiers combined with certain morphemes have a great effect on word order restriction, and this phenomenon is discussed in relation to Pronoun-Noun Constructions (PNCs). Building on the fact verified and supported by a great deal of empirical evidence, I argue that word order restriction of Korean NP modifiers can be flexible depending on the absence/presence of their morphological variation.
Design of fractal spiral inductor for wireless applications

This paper presents a fractal based spiral inductor for wireless applications. The proposed fractal inductor is having 12 to 52% improvement in Inductance value (L) over reported standard inductors with moderate Quality factor (Q). The simulation results obtained from HFSS are validated experimentally on fabricated Printed Circuit Board (PCB) using Network Analyzer in the frequency range (130–500 MHz). The experimental results are almost matches with simulation results.
Stitching Partial 3D Models with an Application to Modelling Stone Flakes

The construction of 3D models from images is a common task in Computer Vision. Mutli-view stereo and structure-from-motion methods have advanced to the point where 3D models of many types of objects can be easily made from images captured with consumer-grade cameras. Some objects, however, are hard to image in their entirety. In this paper we consider flat objects – those with one dimension much smaller than their other two. Such objects are easy to model from either side, but creating a full 3D model is challenging. Our approach projects the two half-models into two dimensions, finds their convex hulls, and then aligns them to merge the two shapes. We demonstrate this method on an archaeological application – modelling the waste flakes produced during stone tool manufacture. We show that our method can create complete 3D models from images captured of the ventral and dorsal (front and back) sides of the flakes. Comparing these models to reference laser scans we find that whole flakes can be reconstructed with between 0.5 and 1.5mm average reconstruction error.
Predicting Mortality in Elders After Acute MI

One third of patients who suffer myocardial infarctions (MIs) are older than 75, but risk prediction models have not incorporated functional
Structured GANs.

We present Generative Adversarial Networks (GANs), in which the symmetric property of the generated images is controlled. This is obtained through the generator network's architecture, while the training procedure and the loss remain the same. The symmetric GANs are applied to face image synthesis in order to generate novel faces with a varying amount of symmetry. We also present an unsupervised face rotation capability, which is based on the novel notion of one-shot fine tuning.
Have your say about campus security

You can still have your say about campus security as we seek to further improve our services.
중등영어교사 임용시험 출제 경향 분석: 2015~2019학년도 영어교육 문항을 중심으로

The purpose of this study is to examine the test items from the written component of the secondary school English teacher recruitment exam. Focused on...
Bilgi Saklama Süreçlerinde Yapay Zekâ Sistemlerinin Kullanımına Yönelik Risk Değerlendirmesi

The capacities of permanent information storage environments have been increasing year by year due to the increasing amount of information. The difficulties posed by the increase in the amount of information processed and stored accelerate the search for the automation of these processes. In this context, it is observed that interest in the use of artificial intelligence systems related to information selection and retention processes has been increased in recent years. Artificial intelligence systems, unlike other information processing for automation, are also effective in decision-making processes. Artificial intelligence makes it possible to take decisions much faster and move services to a personalized level. It is possible to make less biased and more ethical decisions through artificial intelligence as long as they are trained properly and right data sources are used. However, it is necessary to be prepared for the irreversible results of decision-making and retention processes automated by artificial intelligence. In virtualized information storage environments, technical problems related to the ensuring the integrity of information, which is the most important proof of the firsthand information, are also valid in use of artificial intelligence. In addition, adverse effects of artificial intelligence systems on information retention processes are not yet explicable on legal basis. In this context, in this study the effects of artificial intelligence systems on information retention processes and the information integrity in permanent storage environments are examined. By drawing attention to the legal responsibility of artificial intelligence systems that independently decide and implement, suggestions for the use of artificial intelligence systems that are able to be limited, checked and controlled are presented within the study.