Reviewerly/exHarmony huggingface dataset:
A Closer Look at the Adversarial Robustness of Information Bottleneck Models

We study the adversarial robustness of information bottleneck models for classification. Previous works showed that the robustness of models trained with information bottlenecks can improve upon adversarial training. Our evaluation under a diverse range of white-box $l_{\infty}$ attacks suggests that information bottlenecks alone are not a strong defense strategy, and that previous results were likely influenced by gradient obfuscation.
Security Authentication using 3D Password

The number of digital users around the world is increasing day by day. For uniqueness and privacy, authentication is required. Providing authentication means providing security to the system from unauthorized and illegal access. The most common authentication technique is textual-based authentication where the user has unique identification and password. Users generally use passwords taken from the dictionary which are vulnerable and easier to crack. Other available authentication techniques are biometrics, smart cards, etc. Each of them is having its own drawbacks and limitations.3D password is introduced to solve these problems. It is a multi-factor authentication technique that can combine all the available authentication techniques into a single 3D virtual environment. The virtual environment contains various real-life objects. The user has to interact with those virtual objects and the password is generated with the help of the sequence of the interactions. It is easier for the user to remember the sequence and it will be unique as different users’ sequences of interaction will be different based on their interest
The Disclosure of the Content of Sustainability Reports and its Impact in Investors Decisions in Jordanian Industrial Public Share Holding Companies

The study aimed to identify the extent of the impact of sustainability reports indicators (economic, environmental and social performance) investors decisions in Jordanian industrial public share holding companies. The study population consisted of all the Jordanian industrial companies listed on the Amman Stock Exchange and registered in the stock market at the time of the study, the study sample consisted of 15 companies where the study tool was distributed to portfolio managers and financial analysts in these companies. Data collected were analyzed using descriptive and analytical approach such as multiple linear regression to test the hypotheses of the study. The results of the study revealed that there is a statistically significant impact of the indicators of sustainability reports collectively and separately on the decisions of investors, and the study recommended the need for Jordanian industrial companies to pay attention to the disclosure of indicators of sustainability reports.
Enrichment of Linking Structure for the Web of Data

Most of today’s web applications represent pure casts of (X)HTML tags organized as documents. The linking process between such documents is done solely through hypertext references which allow only unidirectional linking. In this paper, an extension of the linking process in the web of data is presented with the use of XML Linking Technologies (XLink) applied to web documents or other resources. With this process, the link structure of web documents can be substantially enriched and as a result, the access to more resources is achieved. The approach makes the data on the web machine-processable as well as humanreadable. The experimental results also indicate that by using the proposed approach, a substantial improvement and increase of linking process between web resources is evident.
Physics-Informed Graph Learning for Robust Fault Location in Distribution Systems.

The rapid growth of distributed energy resources potentially increases power grid instability. One promising strategy is to employ data in power grids to efficiently respond to abnormal events (e.g., faults) by detection and location. Unfortunately, most existing works lack physical interpretation and are vulnerable to the practical challenges: sparse observation, insufficient labeled datasets, and stochastic environment. We propose a physics-informed graph learning framework of two stages to handle these challenges when locating faults. Stage- I focuses on informing a graph neural network (GNN) with the geometrical structure of power grids; stage-II employs the physical similarity of labeled and unlabeled data samples to improve the location accuracy. We provide a random walk-based the underpinning of designing our GNNs to address the challenge of sparse observation and augment the correct prediction probability. We compare our approach with three baselines in the IEEE 123-node benchmark system, showing that the proposed method outperforms the others by significant margins, especially when label rates are low. Also, we validate the robustness of our algorithms to out-of-distribution-data (ODD) due to topology changes and load variations. Additionally, we adapt our graph learning framework to the IEEE 37-node test feeder and show high location performance with the proposed training strategy.
support.iii.com: Sierra Test: Patron Services

This LibGuide provides access to Sierra training documentation for specific functionality. Patron services training resources.
Measuring Corruption and Comparison of Corruption Indices - Focused on CPI, CCI and IPI -

부패지수 혹은 부패통제 지수는 부패인식 제고나 반부패 정책 수립 등 다양한 목적을 위하여 사용된다. 이런 목적을 달성하기 위하여 부패지수의 속성이나 구성에 대해서 정확한 이해가 필요하다. 이 논문에서 CCI, CPI, IPI 부패지수의 작성원리와 속성을 비교 검토하여 각 지표의 장단점을 알아보았다. 모든 부패지수가 다수의 개별 자료나 지수를 활용하여 작성된 복합지수이고 개별 자료들은 인식지수를 포함하고 있다. 각 지수는 개별자료의 선택, 자료의 표준화, 합산 그리고 새로운 지수의 생성 과정을 거쳐서 만들어지는데 통계적으로 오차를 줄이기 위해서 노력하고 있지만, 지수 작성과정에서 다양한 편의(bias)가 존재한다. 좋은 부패지수를 만들기 위해서는 타당성 있고 신뢰할만한 개별자료를 확보하는 것이 중요하다. 부패 현상이나 거버넌스 자체가 측정이 어렵기 때문에 경험자료든 인식자료든 모두 고유한 편의를 가진다. 100개 이상의 국가를 대상으로 발표되는 부패지수는 모든 나라가 동일한 개별자료를 사용하는 것이 아니기 때문에도 편의가 발생한다. 기초자료의 유사성을 고려하면 경제발전의 정도가 비슷한 국가 사이의 부패지수 비교는 상당히 타당도가 높고 한 국가의 부패지수 변화 역시 일관성을 갖추고 있는 것으로 판단된다. 그러나 경제발전의 정도 다른 국가의 부패지수를 비교하는 것은 주의가 필요하다.The purpose of this study is to investigate the property of various corruption measures such as the corruption perception index(CPI) of Transparency International, the control of corruption index(CCI) of the World Bank and the index of public integrity(IPI) of The European Research Centre for Anti-Corruption and State-Building to better understand the meaning of corruption measure indexes. All three corruption indices are built following four steps:selection of source data, rescaling source data, aggregating the rescaled data and then reporting a measure for uncertainty. Although each organization is cautious to minimize errors and biases related to the steps. there exist several biases. To construct a good corruption index, a good quality resource data should be secured first. Due to the difficulties of measuring corruption or governance, all corruption measures exhibit some biases regardless of experience-based or perception-based measures. Because all corruption indexes do not use the same data source, we should be cautious interpreting the corruption index of a country. It is safe to compare indices of countries when the countries are in similar economic development level.
Digital Skipping Rope / Nurul Akmar Zairul Anuar

Nowadays, people are to attend towards something those easy and more flexible multi-function things. I would like to introduce those things. This digital skipping rope will be used as the platform for the consumer or the person use it aware and alert after use this skipping rope. It will drives to easier and effective ways of receiving the limit time by the timer that will be apply at the skipping rope. The consumer will easily access how long they had been used the skipping rope. The concept of company product is Digital Skipping Rope make all the easy and relevant, which help an athlete, and non-athletes to improve and enhance their performance during sport. Thus, it also can cut of time rather than use the old skipping rope. In today's highly competitive environment, it is becoming increasingly difficult to compete with new technology things that provides auto services. Especially when it comes to sports technology. It is because people nowadays want to lose weight but not in-complicated ways and equipment use. Therefore, this situation provide good opportunities for us to expand our business and gain more profit by proper manipulating this situation. Customer will feel more convenience to use our machine because they have the privacy in counting jump and took care of their own timing without any other devices. Our main priority for this business is about distribution our machine to another potential customer and location.
Knowledge Modeling of Airborne Missile Management System Based on Multi-dimensional Fuzzy Ontology

Abstract Health management system of airborne missiles has a large amount and variety of knowledge, but such technical documents are lack of effective management in the knowledge level. According to the technical characteristics of knowledge in the field of airborne missile health management, a HTA analysis model (Hierarchy, time, and activity analysis model) based on multi-dimensional fuzzy ontology in the health management field of airborne missiles is constructed, and ontology description language OWL is introduced to express knowledge. It provides a theoretical and methodological basis for the dynamic management of health knowledge in the field of condition monitoring, prediction and evaluation, fault diagnosis, technical service.
LibGuides: Maker Kits: Makey Makey

Maker Kits are part of the loanable equipment available at the OSU Valley Library. These kits can be used to invent, create, and develop new skils.
Infogeological modeling of the geological environment of the military activity territories

Summary The main methodological instrument of informational support of research and works on the treatment of the geological environment by territories of military activity is information modeling. Methods developed on this paradigm&apos;s principles aim to eliminate the consequences of military activity and restore the territories of the military conflicts. Ground research was developed using conceptual models, particularly checking main components of these models that aim at determined by them indetermination. To identify the influence of the military activity sources, we used the Leopold Matrix and Sorensen Level Diagram, network diagram, method of the combined analysis of maps, and factor analysis. The evaluation of the spread of factors of military and technogenic load of chemical origin in the functional zones and subzones of the military polygon was carried out based on the complex approach to the ecological evaluation of the contamination of the territories of intensive military and technogenic load using the landscape profiling and imitating modeling taking into account geochemical and hydrometeorological conditions.
LibGuides: Studio: Video/Audio Editing

The UWF Libraries' Audio, Video, Photography studio is located on the 1st floor of the John C. Pace library on UWF's main campus.
Model of Academic Achievement through Learning Interest in the Pandemic Covid 19: E-Learning and Motivation (Case Study at Student of Universitas Gunadarma Jakarta)

This study aims to see the effect of e-learning and learning motivation on student interest in learning and academic achievement, and also to see the effect of interest in learning on student achievement in Gunadarma Jakarta. Where the samples used in this study were students of Gunadarma University Jakarta with a total of 100 students. The approach in this study uses a quantitative approach with survey methods and uses path analysis with the Statistical Package for Social Science (SPSS) 21.0 for windows. The results showed that e-learning and learning motivation had a positive and significant influence on student interest in learning and academic achievement, as well as interest in learning also had a positive and significant effect on student achievement at Gunadarma University Jakarta.
Cloud gaming dataset - PC gameplay video traces annotated with video metrics

Large and openly available dataset of 225 different gameplay videos recorded across 25 different games and annotated with objective video metrics.
자원봉사활동을 통한 북동아시아에서의 평화와 번영

Recent times have witnessed a gradual shift in the perspective of volunteering to one where volunteerism is expressed increasingly as a two-way process with benefits generally accruing to the person doing the volunteering, as well as to the person on whose behalf the volunteer act is undertaken. Now we are at the stage to expand the scope of volunteer campaign into global level beyond Korea. We think that active volunteer exchange at private levels is the best way for neighboring countries to pursue common prosperity and realize true global cooperation. Although Korea, Japan and China are sometimes competing or pitted against each other for national interest, we are still near neighbors in historical, cultural and geopolitical aspects. As shown from the disasters like earthquake and tsunami at 5. August last year in Bali, natural disaster is never limited to one country, which implies that neighboring countries as well as all human beings shall help each other. Recently, Northeast Asia is facing a serious diplomatic crisis due to the North Korean nuclear issue. It is a time when a peaceful relationship is required more than ever. In this paper, we discussed how to develop peace and common prosperity of the Northeast Asia, and suggest several solution which based on volunteering.
Keep silence for yourself: The protection of the right to silence in the Italian criminal justice system

The present article aims to discuss the protection of the right to silence in the Italian criminal justice system for an international audience. In Italy, the right to silence is a right that stems directly from the protection offered by the Constitution to the right of defence. Much debate revolves around the extent to which the right deserves to be safeguarded. Although the majority of scholarship favours the broadest extension of the right possible, this view is not endorsed unanimously. The legislature has introduced some limits, the most important being that which confines the right to silence to the facts concerning one’s own responsibility, save for exceptions. The courts, in turn, have taken a softer approach in the protection of the right to silence, which may allow the possibility of using the suspect’s silence to draw adverse consequences. Although the Italian system offers comparatively strong protection to the right to silence, it nonetheless leaves some openings that undermine the effectiveness of the right. This article therefore argues that compensating for the possible side effects of the rules on cooperation, removing some negative consequences of silence and the strengthening of remedies are the main fronts where the Italian system can still improve the protection of the right to silence.
Effect of Number of Face Images based on Illumination Variation in the Training Process on Face Recognition Results

The research is related to face recognition which is influenced by illumination factor. The method used is the Robust Regression, which has a better performance than many other methods. The empirical experiment, which uses Yale Face Database B Cropped, is conducted to determine the effect of number of face images in the training process on face recognition perfomance. The hypothesis proposed in this research is the greater number of face images will result in higher facial recognition performance. The empirical experiment was conducted on this research to prove the hypothesis. Based on experiments that have been done, in general, the process of data training with many images will result in high performance of face recognition. But, this trend only occurs in images in the similar illumination condition. Illumination variation of face images also have significant impact on face recognition results. The process of training data with images of illumination variations (from several subsets of the face database) results in better face recognition performance than the process of training data with images of similar illumination conditions (from a subset of the face database). By using 19 images from subset 5 of the face database, face recognition accuracy is obtained at 95.11%. Whereas by only using 5 images from several subsets, obtained face recognition accuracy up to 96.10%. Even by using 7 images from several subsets, the accuracy obtained is up to 99.47%. Keywords: Face Recognition Performance, Robust Regression, Data Training
Power-Aware Path Planning for Vehicle-Assisted Multi-UAVs in Mobile Crowd Sensing

UAVs’ high mobility and extensive coverage make them widely used as task performers in mobile crowd sensing (MCS). However, due to the limitation of the battery capacity, the flying distance of UAVs is limited, thus they cannot be continuously used in a wide area. In response to this problem, the ground vehicle can be used to transport, release, and recycle UAVs. Large-scale data collection can be achieved through the combined use of the ground vehicle and UAVs, where the route planning of vehicle-assisted UAVs is a key problem. The existing algorithms assume that the power of UAVs is unlimited or the charging time is negligible, which is impractical in real scenarios. In order to solve the above problems, we formalize a vehicle-assisted multi-UAVs path planning model based on the power of UAVs and propose an efficient and power-aware path planning algorithm for vehicle-assisted multi-UAVs(VMUPA). In VMUPA, we take genetic algorithm (GA) to plan flight paths of multi-UAVs under multiple constraints and obtain the power required at each parking spot. Then we optimize the driving route of the ground vehicle according to the remaining power of UAVs to minimize the overall time. Finally, performance evaluation is presented to demonstrate that VMUPA reduces the task completion time by 15% compared to existing algorithms in most cases.
Automation in Academic Libraries - A Study of TTD College Libraries.

In the present Information and Communication Technology Era almost all academic libraries are transforming into automation as it is compulsory according to the UGC norms and to achieve NAAC grade. Automation plays a key role in maintaining the library with effective and efficient services to its users with advanced as well as quick services. This article aimed to study the automation of library in TTD run SGS Arts college using the software.
The Effect of Transactional Strategies instructional (TSI) On Students Writing Skill Recount Text on Grade X at SMK Negeri 3 Rantau Utara

This research aims to know Transactional Strategies Instructional (TSI) On Students Writing Skill Recount Text on Grade X at SMK Negeri 3 Rantau Utara, both validity and partial, the validity test of the number of Students (N) = 31, if the level is significant @ = 0.05 obtained r table = 0.355. While the data is Proleh (validity) of each item whereas the Realization determination of the reusability coefficient with (N) = 31 and the equivalent significance @ = 0.05 is 0.355 whereas r count = 0777. Valuation Criteria If R counts > R table It is said that the whole material becomes the flagship item. Based on the results of analysis by using Test T then obtained the value of t count = 7.916 and known value on t table at the level of α = 0.05 of 1.670. Next by comparing T count with T table to determine the acceptance criteria and rejection Ho, it is known that the value of the coefficients t > T table. Under the previous provisions, it refused Ho and received Ha.
INFORMATION RE-ENGINEERING METHODOLOGIES FOR ECONOMIC GROWTH AND SUSTAINABLE DEVELOPMENT

For several decades, technology engagement in various sectors of the economy has been on the increase and information engineering (IE) is centered on development of information systems (IS). Re-engineering incorporate new computational approach to generate, distribute, process and use information. IS as decision support tools are computer-based infrastructures, which collect, process, store/manage and act on information. Information resource, a critical ingredient for socio-economic development required re-engineering methodologies to combat the menace of humanitarian crises. Though, TVET objectives of sustainable development centered on poverty reduction, production improvement, safety and good health, imminent challenges of hazards, local disasters, life-threatening conflicts had increased peoples’ vulnerability to humanitarian crises. This paper adopts Trajectory Range Query (TRQ) and k Nearest Neighbour (TkNN) algorithms (SpatialHadoop) for analysis and inferencing and the computation implemented shortest routes to query safety points in shortest intervals. Capacity building in ICT technologies via TVET strategy help unlocks greater potentials for greater services when objectively collaborated with STEM agenda. Engaging more women in information re-engineering reduces gender-imbalance problems. Increased women participation in IRE fosters more wisdom-driven analysis/inferencing, which significantly effect rapid talent-growth and skill- boost projections of TVET. Spatial operation and query analysis algorithms are useful for transportation and advance pattern-mining computations. They decisively provide solutions in crises’ handling. More women in STEM-related disciplines as information re-engineering is a focus to revamp TVET objectives and achievable goal of gender-balance is also an indicator of socio-economic growth and development
Fuzzy based Hybrid Genetic Algorithm for Efficient Cloud Job Scheduling

Abstract These days enterprises need to keep up a lot of uses getting to buy a large number of clients everywhere over the world. Keeping up their own foundation, overseeing programming prerequisites, and taking care of exorbitant excessive internet is difficult. This makes them move towards cloud computing. Cloud computing is a service provisioning strategy where clients can lease any assets like equipment, programming, or stage to build up an application. Clients need to pay just for how much the assets were devoured, and can powerfully increase or decrease the asset limit depending on the situation. Since clients are paying for the administrations, they anticipate the nature of administration from the supplier. Giving the nature of administration and pulling in the clients is a difficult issue for the suppliers. If not, clients will move towards other cloud suppliers. Hence, Service Level Agreement (SLA) is made among suppliers and clients that incorporate assistance quality, assets capacity, versatility, commitments, and outcomes in the event of an infringement. Fulfilling SLA is vital and a difficult issue. In this paper, diverse systems and strategies proposed by the various creators for givingthe nature of administration and keeping up SLA are discussed. We propose a cloud service planning model that is alluded to as the Task Scheduling System (TSS). In the client module, the interaction time of each task is as per an overall distribution. In the task scheduling module, we take a weighted amount of makes skillet and stream time as the target capacity and utilize a fluffy-based Genetic Algorithm (GA) to take care of the issue of cloud task planning. Simulation results show that the convergence speed and output performance of fuzzy-based Ant Colony Optimization (F-ACO) are optimal.