Reviewerly/exHarmony huggingface dataset:
User Authentication for Mobile Phones by Pseudo Signature Using CNN

Today, majorityJose, Christy James of theRajasree, M. S. world population has one companion with them always. This companion has all the private information of the person. That companion is the smart phone. Considering the private data its holding, the unauthorized usage by friends, family members and strangers are to be avoided. The traditional way of preventing the unauthorized usage is to lock the device with PIN numbers, graphical patterns, fingerprint sensors and face unlock mechanisms [1]. The last two are available with high-end phones only. Even these mechanisms rely on the first-mentioned methods in case of a sensor failure. Primary authentication mechanisms could be easily breached. In this paper, we are investigating the usage of handwritten signatures as an authentication method. We are suggesting a Pseudo signature, a signature drawn on the touch screen of the phone using the finger tip. We have used convolutional neural network classifiers to classify the genuine user and intruder. Experimental results show our suggestion is promising and it could be used as an easy-to-use user-friendly primary authentication for smart phones.
Design of a Power Randomization Circuit for Block Ciphers

To improve the anti-Power Analysis Attack ability of Block Ciphers, we summarized the research status of anti-attack technology. Starting with Mask Technology, the concept of Random Interleaving is put forward and its key propertie is proved. Based on the basic method of inserting random number, a Power Randomization circuit structure is designed and applied to the AES-128 algorithm circuit as an example. Finally the design of this paper is verified from three aspects. The results show that the algorithm circuit with this structure can correctly complete the encryption function, the ability to resist Power Analysis Attack has been significantly improved, and the circuit performance is good.
Accurate Short-term Forecasting for Photovoltaic Power Method Using RBM Combined LSTM-RNN Structure with Weather Factors Quantification

After the operation of the photovoltaic system, there is a problem in grid connection and power sales which is the prediction of photovoltaic output power. The power forecasting problem of the photovoltaic systems is strongly influenced by the weather factors, and there is continuity of time variation within the input sequence. Most forecasting methods have volatility problems for short-time scale predictions, seldom consider the changes of weather-affecting factors and their influence modeling. When it comes to a newly implemented photovoltaic power plant, the scale of samples is usually not enough to finish the training process. In order to solve the above problems, this paper proposes a predictive network with cascaded network structure, the pre-stage network is used to quantify the weather influence factors, and the post-stage network is used to give the prediction of the photovoltaic power output. The proposed method considers the quantification of weather influencing factors, explores the time series intrinsic links contained in the power output sequence and uses the unique stacked organization of LSTM structure to reduce the dependence on the scale of training datasets. This paper uses a Tianjin local photovoltaic power plant as certain instance, and finally achieve the goal to make an accurate prediction of photovoltaic power output by hourly scale, which verifies the validity of the proposed method.
Parameter Sharing in Coagent Networks

In this paper, we aim to prove the theorem that generalizes the Coagent Network Policy Gradient Theorem (Kostas et. al., 2019) to the context where parameters are shared among the function approximators involved. This provides the theoretical foundation to use any pattern of parameter sharing and leverage the freedom in the graph structure of the network to possibility exploit relational bias in a given task. As another application, we will apply our result to give a more intuitive proof for the Hierarchical Option Critic Policy Gradient Theorem, first shown in (Riemer et. al., 2019).
The Evolution of Bank Lending at Regional Level in Romania

As a result of the economic and financial relapses following the international financial crisis started in 2007, the examination of the way in which the bank lending of the non-financial companies at regional level in Romania evolved is relevant on the one hand, by presenting the transformations suffered by the credit conditions, and, on the other hand through its implications on the level of regional development, the absorption of structural and cohesion funds offered by the European Union, access to financing,as and the use of new financing methods. The approach by which this research is carried out is based on a qualitative method, and considers the collection, analysis and interpretation of the data from 2015 and 2019 included in the surveys and statistical studies carried out by the specialists of the National Bank of Romania and other Romanian institutions. The results of research underline a sustained correlation between the evolution of bank lending and the other aspects mentioned above, highlighting the importance of access to bank financing at territorial level in order to increase the level of regional development in Romania.
Identification and Exploitation of Vulnerabilities in a Large-Scale ITSystem

This thesis presents the results of a vulnerability assessment and exploit development targeting a large-scale IT-system. Penetration testing and threat modelling was used to identify vulnerabiliti ...
Penatalaksanaan Fisioterapi Pada Kasus Post Operasi Medial Collateral Ligament Dekstra dengan Modalitas Ultrasound dan Terapi Latihan di RS PKU Muhammadiyah Karanganyar

Background: Repair Medial Collateral Ligaments (MCL) is a knee reconstruction after a rupture in order to become stable. Reconstruction or replace the MCL can be derived from the parts of the body (autograft) or other people who have died (allograft). The function of the tendon is taken is not interrupted because that is taken from the tendon that is just a small part. Once that is done then the rehab program will be back to normal knee function and gradually be able to do usual activities.Objective: to know how the benefits of Ultrasound and Static Contraction on the case under the Medial Collateral Knee Ligaments surgery Dextra.Results: after 4 treatments, there were changes in pain at rest from T1 : 2 to T4 : 0, tenderness pain from T1 : 5 to T4 : 1, and motion pain from T1 : 6 to T4 : 3, and the pain of motion T1 : 6 to T4 : 3, an increase in the scope of the motion the motion of joints knee dekstra T1 : 110 o to T4 : 125 o d an increase of the flexor muscle power T1 : 3 to T : 4.Conclusion: Ultrasound modality of granting and Static Contraction can reduce pain, increase in muscle and an increase in the scope of the motion of the joints so that it can improve functional.
Forests and Fuzzy Trees Fuzzy

In 1965, Loft A.Zadeh introduced the notion of a fuzzy subset of a set as a method for representing uncertainty.It provoked at first, a strong Abstract Fuzzy Set theory is a paradigm shift that first gained acceptance in the Far East and its successful application has ensured its adoption around the world.
Anomalous Sensor Detection Based on Nonlinear Graph Filter

Detecting anomalous data on IoT sensor network is an essential yet challenging task, especially if anomalies have small deviations from normal data, which would be more difficult in the coming 5G and beyond era due to the explosive growth of data. In this paper, the sensor data, as well as the network structural information, are studied to develop a robust and effective anomaly detection algorithm. The sensor data reconstruction model is built based on the recently developed nonlinear polynomial graph filter (NPGF), which involves the adjacency matrix of the sensor network and hence would learn from the network structural information. It first estimates the NPGF based reconstruction model from normal sensor data, and then detects anomalous sensors as those attaining high reconstruction error from the model. The proposed algorithm is shown to achieve 0.1 higher detection rate on anomalies with small deviations, compared with another recent graph-based detector based on linear graph frequency.
Penerapan PHP Framework Pada Website Online Toko Djinggo

The need to be able to increase sales and reach wider consumers, Djinggo Shop needs a new system. Currently Djinggo Shop marketing and its services only use Instagram and facebook  accounts, so building a new system that can reach market segments by utilizing a website is needed. In this study, uses a form of case study research, while the research method used is Research and Development. The data collection techniques used are observation, interview, documentation study and internet access. The software design model used is the Rapid Application Development model consisting of planing, design, construction. To model the system from starting to model system information for companies to applications, the author uses UML (Unifield Modeling Language). Software is built using CodeIgniter PHP Framework, with a MySQL database. The results of this design produce a website-based application on Djinggo Shop by providing effective information such as search features, managing data items, managing sales and managing content on the website. Sales website at the Djinggo Shop is designed to attract new consumers, make it easier for consumers to find the items needed, enhance the image of the Djinggo Shop so that it is better known to the public, giving owners the convenience of managing and providing services to consumers.
Maxing, Ranking and Preference Learning

Author(s): Pichapati, Venkatadheeraj | Advisor(s): Orlitsky, Alon | Abstract: PAC maximum selection (maxing) and ranking of $n$ elements via randompairwise comparisons have diverse applications and have been studiedunder many models and assumptions. We consider $(\epsilon,\delta)$-PACmaxing and ranking using pairwise comparisons for \nobreak{general}probabilistic models. We present a comprehensive understanding ofthree important problems in PAC preference learning: maxing, ranking,and estimating \emph{all} pairwise preference probabilities, in theadaptive setting.{\bf SST + STI:} We consider $(\epsilon,\delta)$-PAC maximum-selectionand ranking using pairwise comparisons for \nobreak{general}probabilistic models whose comparison probabilities satisfy\emph{strong stochastic transitivity (SST)} and \emph{stochastic triangle inequality (STI)}. Modifying the popular knockouttournament, we propose a simple maximum-selection algorithm that uses$\mathcal{O}\left(\frac{n}{\epsilon^2} \log\frac1{\delta}\right)$ comparisons, optimal up to a constantfactor. We then derive a general framework that uses noisy binarysearch to speed up many ranking algorithms, and combine it with mergesort to obtain a ranking algorithm that uses $\mathcal{O}\left(\fracn{\epsilon^2}\log n(\log \log n)^3\right)$ comparisons for$\delta=\frac1n$, optimal up to a $(\log \log n)^3$ factor.{\bf SST +/- STI and Borda:} With just one simple natural assumption:\emph{strong stochastic transitivity (SST)}, we show that maxing canbe performed with linearly many comparisons yet ranking requiresquadratically many. With no assumptions at all, we show that for theBorda-score metric, maximum selection can be performed with linearlymany comparisons and ranking can be performed with $\cO(n\log n)$comparisons.{\bf General Transitive Models} With just \emph{Weak Stochastic Transitivity (WST)}, we show that maxing requires $\Omega(n^2)$comparisons and with slightly more restrictive \emph{Medium Stochastic Transitivity (MST)}, we present a linear complexity maxingalgorithm. With \emph{Strong Stochastic Transitivity (SST)} and\emph{Stochastic Triangle Inequality (STI)}, we derive a rankingalgorithm with optimal $\mathcal{O}(n\log n)$ complexity and anoptimal algorithm that estimates all pairwise preferenceprobabilities.{\bf Sequential and Competitive} We extend the well-known\emph{secretary problem} to a probabilistic setting, and apply theintuition gained to derive the first query-optimal sequentialalgorithm for probabilistic-maxing. Furthermore, departing fromprevious assumptions, the algorithm and performance guarantees applyeven for infinitely many items, hence in particular do not requirea-priori knowledge of the number of items. The algorithm has linearcomplexity, and is optimal also in the streaming setting and for bothtraditional- and dueling-bandits. In a non-streaming setting, amodification of the algorithm is \emph{competitive} in that itrequires essentially the lowest number of queries not just in theworst case, but for every underlying distribution.
Rancang Bangun Website Penjualan Pada Toko Sixteen Sport

The need to produce an effective web-based online sales system at Sixteen Sport Stores requires a new innovation in building a system that can help companies reach market segments. Because the business activities owned by the Sixteen Sport Store still require telephone communication media to order and store customer data, they are still manually typed by company employees. Designing a website sales business can help support regional economic growth without a large investment. The purpose of research produces a system for implementing business online. The form of this research uses R & D (Research & Development) method and for software design used is RAD (Rapid Application Development). The aim of the research is to produce a sales website that is able to market goods (sports equipment products) online and reach the wider community and provide convenience for consumers to get goods and interact. The main features that are produced are item detail features, shopping basket, invoice, payment confirmation, list of consumer orders, payment list, and other features that can be used by the admin to manage website sales data.
Automatic IoT Based Agricultural Assistant

Abstract — During the main objective is to assist the farmers to improve agricultural practices using the image processing technique. Increasing population requires the food production to be increased which requires better cultivation in the form of proper utilization fertilizers. The objective of autonomous agribot is to effectively utilize the resources and to reduce labour work. By developing this robotic vehicle with its multitasking agricultural features, farmer can cultivate irrespective of the conditions based on its optimal parameters resulting in a profitable job. Image processing has been proved to be effective tool for analysis in various fields and applications of an agriculture sector. The responsibility of controlling and managing the plant growth from early stage to mature harvest stage involves monitoring and identification of plant diseases, controlled irrigation and optimal use of fertilizers and pesticides. Keywords – Image Processing, Raspberry pi, Agribot, Internet of things, Arduino Cite this Article Yuvaraj K, Deenadhayalan TU, Gowtham K, Harshitha L. Automatic IoT Based Agricultural Assistant. Current Trends in Information Technology. 2019; 9(2): 1–4p.
The NAI Suite - Drafting and Reasoning over Legal Texts.

A prototype for automated reasoning over legal texts, called NAI, is presented. As an input, NAI accepts formalized logical representations of such legal texts that can be created and curated using an integrated annotation interface. The prototype supports automated reasoning over the given text representation and multiple quality assurance procedures. The pragmatics of the NAI suite as well its feasibility in practical applications is studied on a fragment of the Smoking Prohibition (Children in Motor Vehicles) (Scotland) Act 2016 of the Scottish Parliament.
Research on An Improved Evaluation System of Urban Distribution Network Based on Development Adaptability

In recent years, electricity demand has maintained a relatively rapid growth in China. Strengthening the scientific planning and construction of power grids, especially the comprehensive evaluation of distribution network, is conducive to the sustainable development of electric power and the effective play of the important basic role of electric power in the development of national economy. This paper considers the coordination of distribution network with superior power grid, local economy development, and the penetration of distributed generation, also the adaptability to the reliability requirements of power supply. Based on this, an improved evaluation system is propose considering the adaptability of urban power grid. Firstly, the advantages and disadvantages of the traditional evaluation system are analyzed; secondly, the evaluation objectives of adaptable urban distribution network are established, and the specific indicators involved in each objective are analyzed; then a new evaluation system of adaptable distribution network is given; finally, an appropriate example of distribution network is used to verify it, and the results show that the system can effectively evaluate urban distribution network , also find out the weak links and give solutions.
Refined image colorization using capsule generative adversarial networks

Automatic image colorization has increasingly become a heavily researched topic over the last decade. It has become of interest for many application areas including colorization of black and white movies, historical images, surveillance feeds and generally old image restoration. Recent state-of-the-art methods utilize Deep Convolutional Generative Adversarial Networks (DCGAN) for the colorization process. However, with the introduction of capsule networks, many flaws of the convolutional neural networks began to surface. In this paper, the convolutional network layers inside the discriminator of a DCGAN will be replaced with capsule network layers. Further studies are employed to show how capsule networks as a discriminator in a DCGAN perform in the image colorization task.
Unknown Anomaly Detection Using Hidden Markov Model and AreaSensing Techniques

In this paper, we propose an anomaly detection method for equipment abnormalities using data measured by AreaSensing techniques. The data are gathered from the vibration of equipment installed in a wide area or large scales such as conveyor equipment and bridges. It is difficult to know which data of displacement, velocity, and acceleration is appropriate in advance because each frequency component is different. So, we apply the Hidden Markov Model, which estimates the latent state for each decomposition level by continuously frequency-resolving time series data using Wavelet method. The analysis results show that the normal and abnormally states are estimated. However, as the problem of this method, it is not possible to compare and apply the information criteria such as AIC to the Wavelet decomposed data as it is to appropriately decide which data and model parameters should be used. To overcome the defects, we propose a new evaluation function and developed a method to find a model that can stably estimate the normal and abnormal state transition, even for data separated into different frequencies. Besides, when the current measurement data contains no abnormal state, there was a problem of extracting multiple latent states that are normal but different. We focus on the difference between the state transition probabilities of the normal and unknown model. As the experimental result, the effectiveness of the proposed method has been confirmed. By using the method, it is possible to continuously diagnose abnormalities using vibration measurement data measured by AreaSensing techniques.
Verification Voting Machine and the Management of the 2015 Presidential Election in Nigeria

Election is at the epicenter in any democratic government worldwide and its basic tenets could be seen in allowing the electorate to freely exercise their franchise on contenders for public office.Election serves as a house wire by which the electorates can have control over their representatives.These invariably condition the elected officials to be accountable as they could be removed through the same process when they fail to represent the electorate.It was based on this that in 2015 General election of Nigeria, former President Good luck on different times keep emphasizing his readiness to guarantee the sanctity of the ballots.This effort was in consonance with his believe that until the citizens right to decide who represents them is enforced and guaranteed, leaders who are committed for the common good of all would be difficult to get.Presumably, this was to prove to the people that absolute power resides on them even though, history has it that past elections in Nigeria had remained controversial, crisis ridden among politicians, political parties and other stake holders in an attempt to subvert the will of the people and democratic process.Elections are not only meant to ensure, confirm or re-affirm the legitimacy of the executives through a regular consent, but also provide a fertile ground for liberal democracy to thrive and be consolidated.However, it is necessary to state that election may not guarantee the consolidation and the attainment of the democratic process but it remains vital in the democratization process.Therefore, it is central and a sine qua non for democratic consolidation.From preindependence election of 1959 to post independence election of 2007 in Nigeria, electoral process and system had remain the same with worsening incidence of disenfranchisement of some electorates, manipulation or falsification of election results, unnecessary suit case at the tribunals, harassment and intimidation of opponents, unnecessary crisis among others.Conducting free and fair elections in Nigeria has been a very big problem since independence.The 1964 federal elections and 1965 Western region elections were marred by widespread electoral malpractices.The violence and crisis that followed it gave the Western region the name 'wild wild west'.These electoral problems and violence were some of the remote causes of the civil war in Nigeria from 1966 -1970.In line with this, Nigeria almost broke up as a country over the crisis that arose from the annulled election of MKO Abiola in 1993.
Andrea Long Chu Says You Are a Female, and He's Only Partly Wrong

Transgender performance of femaleness can only be a parody, because no amount of bottom surgery will make a male into the kind of human being who has the natural power to bear a child. The woman has the spontaneous, natural power to make space for the other, which embodies the spiritual reality to which all human beings are called.