Reviewerly/exHarmony huggingface dataset:
Incentives to Fake Reviews in Online Platforms

With the proliferation of online rating platforms, there has been an increasing concern over the authenticity of reviews posted online. This paper develops a theoretical framework to study sellers' incentives to solicit fake reviews in online rating platforms, and provides empirical evidence supporting some of the model's conclusions. The model predicts that sellers' optimal investment in fake reviews is not a monotone function of their reputation, with sellers with either a very good or very bad history of past reviews displaying less incentives to fake reviews. Another prediction from the model is that, in order to maximize the impact from each fake review, sellers tend to concentrate review manipulation at the initial stages following their entrance (or reentered with a new name) into the market. Using data collected from Amazon, I was able to observe those features from the model at the empirical level by estimating the probability of a review being fake as a function of the product's reputation and the time it took for the review to be posted since the seller entered the market.
Dual Steganography Approach Using 3D Playfair Cipher and Pixel Value Differencing Method

In this paper we attempted to incorporate a text encoding technique 3D Playfair Cipher with Pixel Value Differencing (PVD) approach to achieve dual steganography. Dual steganography is very demanding in the present scenario, because steganography is only playing a role to stealth intruder, but sometimes existence of secret data got recognized, in such scenarios dual steganography can only protect our secret exchange. In steganography hiding capability is equally concerned as much as security, so compression of secret message is preferable before imparting it in cover medium. These requirements pushed us to implement a fast, secure, effective and handy steganographic approach to solve secure information exchange problems. In this research we took the advantage of 3D Playfair cipher not to only encode our secret message but also to reduce its size. Here dual steganography is formed using 3D Playfair cipher with PVD method. PVD method implements the concept that edge areas are more vulnerable that smooth areas in images to conceal secrets,which makes it a powerful approach in the field of image steganography due to its stegoimage quality and data hiding capabilities. PVD method hides data in cover image based on the difference of pixel value in the pixel pairs (nonoverlapping consecutive pixels). Proposed approach is much secure and better in data hiding capability along with ensuring better quality stego image quality, it also solves the problem of falling the boundary of the pixels presents in PVD method. Produced Stegoimage of proposed technique is secure enough against the RS detection attack and totally indistinguishable by human eyes.
Hybrid sampling Algorithm Based on Ant Colony Optimization and k-means Clustering

Class imbalance is very common in many real-world datasets and is an active research topic in machine learning and data mining.In this paper, a hybrid sampling algorithm is proposed to deal with class imbalance with minimum loss of existing information and additional computing power.The proposed algorithm undersamples the majority class data by identifying within-class sub-concepts and then deriving an optimal subset of majority class data using ant colony optimization.A representative training dataset is derived by combining the optimal subset of majority class data and minority class data.New synthetic instances are created in the minority class when imbalance still exists in the representative training dataset.The selection of majority class instances to solve the imbalanced data classification problem is novel in the proposed hybrid sampling algorithm.The proposed algorithm is examined on 15 imbalanced datasets.The experiment results revealed that the proposed algorithm achieves good performance in the aspects of performance measures, G-Mean and AUC.The proposed algorithm is compared with the popular sampling ensemble algorithms, and the results revealed that the proposed algorithm outperforms the popular sampling ensemble algorithms.
E-Mail Spam Filtering Through Feature Selection Using Enriched Firefly Optimization Algorithm

E-mail is the most common method of communication because due to its ability to obtain, the rapid modification of messages and low cost of distribution. Spam causes traffic issues and bottlenecks that limit the amount of memory and bandwidth, power and computing speed. For data filtering, various approaches exist that automatically detect and suppress these indefensible messages. A methodology based on Sine- Cosine Algorithm (SCA) introduced which address the problem of space and time complexities are increased in E-Mail spam detection. In this method, WordNet optimized semantic ontology applies different methods based on semantics and similarity measures to reduce the large number of extracted textual features. This paper proposed the Enriched Firefly Optimization Algorithm (EFOA) method effectively selecting suitable features from an upper dimensional space using the fitness function. Once the best feature space is identified through EFOA, the spam classification is done using ANN. Intially, E-mail spam dataset is preprocessed, then the extracted textual features are Semantic-based reduction and Features weights updated using optimized semantic WordNet. The results obtained showed that the ANN classifier after selection of features using EFOA was able to classify e-mails as spam and non-spam. This EFOA demonstrates that the proposed method has led to a remarkable improvement compared to the SCA methods.
DETERMINANTS OF CAPITAL FLIGHT IN POST WAR SIERRA LEONE: AN EMPIRICAL ANALYSIS

The objective of this paper is to investigate the determinants of capital flight in Sierra Leone and the direction of causality between capital flight and key variables, within the context of the autoregressive distributed lag (ARDL) estimation technique and the granger causality framework. The study utilizes quarterly data spanning the period 2000:Q1 to 2019:Q1. The bound test result confirms the existence of cointegration. The long run result reveals that real effective exchange rate, corruption and external debt are the main determinants of capital flight in Sierra Leone. Specifically, the finding indicates that real effective exchange rate, high level of corruption and accumulation of external debt cause an increase in capital flight. Furthermore, the result reveals that lagged capital flight, corruption, external debt and financial deepening are the main drivers of capital flight in the short run. Whilst lagged capital flight, corruption and external debt accumulation increase capital flight, the result reveals that a well-developed financial system reduce capital flight. The finding asserts that any disequilibrium in the model is corrected at the 26% adjustment speed annually. The diagnostic test confirms that the coefficients are stable, given that the CUSUM and CUSUMSQ lie within the critical band. The granger causality test results reveal that, external debt and capital flight exhibits bi-directional causality. However, both inflation and exchange rate demonstrate uni-directional causality, given that these variables granger cause capital flight, with no feedback effect. The study therefore urges the Government to take measures to strengthen the Anti-corruption Commission and the judiciary with a view to intensify the fight against corruption, and reduce capital flight. Also, government should put in place modalities to ensure strict capital controls, deepen the financial market and maintain broad macroeconomic stability as recipe to reduce capital flight.Keywords: ARDL, granger causality, capital flight, Sierra Leone, quarterly dataJEL Classifications: C 32, F 21, F 40DOI: https://doi.org/10.32479/ijefi.11271
Thematic organization of instructional texts as a linguistic basis for the acquisition of knowledge by an intelligent agent

The article examines the thematic organization of instructional texts in the aspect of problems relevant to work on the creation of a cognitive assistant. The purpose of the assistant is to provide a user with the necessary information to follow the rules of a particular scenario to successfully achieve a goal according to the search query. The query containing certain keywords, further specified as the task being solved, is focused on a detailed set of topics which mark the subject areas reflected in the scenario. The authors of the article provide a review of some linguistic works devoted to the issues of theme-rhematic structuring of a produced text and its compression within the limits of keywords. The importance of the description of the text’s thematic chains, to obtain the detailed objective information on its thematic structure, is emphasized. When comparing the list of keywords identified by the automatic system TextApplianсe in a collection of Internet-extracted instructional texts retrieved from the Internet with the results of hand-held analysis of these texts, to determine the place of various nominative units in the text’s thematic organization, the authors consider the most significant characteristics of a keyword shown in different nominative units to varying degrees. This is a high indicator of a text identifier, content capacity, and communicative significance of a word or a substantive phrase as a marker of important information for a recipient. Defining keywords in whole instructional texts and in relatively independent text fragments (subtexts) that describe individual stages of the user’s goal achievement (for example, the stages of selecting a car, its inspection, making a transaction, car registration) makes it possible to improve the quality of scenario identification in the Network. Extracting keywords along with their context allows for the creation of a recommendations’ database for users automatically. The significance of the theme-rhematic text structure analysis, as a sign for its modeling in the sign picture of the world, is revealed.
A modular system for behaviour analytics from airborne full-motion video

The next generation of multi-domain airborne platforms will provide military operators with unparalleled sensor data streams spanning video, radar, and other sensor inputs. These expanded sensor capabilities will substantially increase access to critical, near-real time surveillance. However, the process of interpreting video feeds places a significant burden on intelligence operators, a demand that can be addressed by AI-based algorithms. AI-based tools complement the aerial footage processing tasks performed by full motion video analysts. In this work, we introduce a new aerial pattern of life dataset and describe our latest algorithmic developments, which uses deep learning to gain an understanding of a scene’s patterns of life. This approach allows anomalies, outliers from standard patterns of life, to be identified using supervised and unsupervised learning approaches. Herein, we describe our deep learning models and our corresponding microservices software architecture. The patterns of life and anomaly detection performance is measured through analysis of video from this new remotely piloted aerial system (RPAS) flight campaign dataset.
Experts Review on Factors to Consider When Designing Virtual Environment for Stress Therapy

Virtual reality (VR) based therapy is an alternative technique available for stress treatment. In this technique, virtual reality is used as a tool to assist users to reduce stress and induce relaxation. Many previous literatures published have acknowledged the effectiveness of virtual reality based therapy as compared to other techniques such as breathing exercise and imagination. However, previous studies available only focused on proving the effectiveness of virtual reality application in reducing stress, but are lacking discussions on factors that should be taken into consideration when designing its virtual environment. In previous study, initial framework containing possible factors to be considered when designing virtual environment for stress therapy has been proposed. In this paper, an expert review was conducted to validate the usefulness of the identified factors. Findings from the validation process has resulted in the improved version of the initial framework and their application in virtual environment.
The Development of Mobile Augmented Reality Application to Facilitate High School Students with Various Learning Strategies in Learning History

Augmented Reality is a demanding feature that widely embeds in our mobile devices. With the current mobile networks this feature will be increasingly accessible in many areas such as education. The current situation in learning history is boring and unattractive to high school students. In addition, the current history books as well as additional revision books are very textual and contain less pictures.The aim of this paper is to describe the mapping of the different learning styles that the students have employed onto the AR mobile application in learning history. The mapping should facilitate all learning styles so that learning history becomes more interactive and engaging.
Digital Preservation of Cultural Heritage and Opportunities Created by the Pandemic Crisis for Bringing New Life to Historical and Cultural Artefacts

The article describes possible strategies for saving the cultural heritage and accelerated digitization of cultural artefacts and items of national historical significance. Emphasis is placed on the specific opportunities posed by the pandemic crisis and the labor market fluctuations to introduce ICT innovations in museums, libraries, and other cultural institutions.
A Journal on Cervical Cancer Prediction Using Artificial Neural Networks

Artificial neural networks (ANN) assume a significant part in numerous clinical imaging applications. Cervical cancer ranks the 4th dangerous women cancers in less developed countries due to insufficient trained staffs and medical procedures. The location of cervical malignancy cells utilizes ANN for characterizing the typical and unusual cells in the cervix wall of the uterus. Cervical malignancy location is exceptionally difficult on the grounds that this disease happens with no manifestations. The order between the typical,unusual and malignant cells produces exact outcomes than other manual screening techniques.The ANN utilizes a few models for a simple and precise identification of cervical cells. The main aim of artificial neural networks is to supply right information at a right time. Hence we implement artificial neural techniques with collected data Analysis,to improve the life of an individual and to decrease the death rate of the society respectively. &#x0D;
Developing a Novel Hands-Free Interaction Technique Based on Nose and Teeth Movements for Using Mobile Devices

Human-mobile interaction is aimed at facilitating interaction with the smartphone devices. The conventional way to interact with mobile devices is through manual input where most of the applications are made assuming that the end user has full control over their hand movements. However, this assumption excludes people who are unable to use their hands or have suffered limb damage. In this paper, we proposed a nose and teeth based interaction system, which allows the users to control their mobile devices completely hands free. The proposed system uses the front facing camera of the smartphone to track the position of the nose for cursor control on the smartphone screen. The system detects teeth for performing the touch screen events such as tap, scroll, long press, and drag. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Viola-Jones</i> algorithm is used to detect the face and teeth based on the Haar features. After detecting the face, the nose position is calculated and tracked continuously using <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Lucas Kanade’s</i> method for optical flow estimation. All the touch screen events have been implemented in the system so that the user can execute all the operations of the smartphone. To evaluate the performance and the effect of (smartphone) device type on the execution time, the proposed system was installed in 3 smartphone devices and 7 trials for each device were performed by 3 different able-bodied elderly persons. The result shows a significant success rate for the detection of nose and teeth, and for the execution of the operations. The execution time of each operation slightly varies by 0.72s on average because of the configuration of the smartphones.
The Internet and its Opportunities for Cybercrime – Interpersonal Cybercrime

With the advancement in technology, computers and the internet are easily accessible to the masses. It has made it easier for people to keep in touch across long distances and have also provided a platform to collaborate for purposes related to business, education, and culture. However, this free flow of information has given rise to irresponsible behavior online. It is used not only for the benefit of individuals but also exposes them to numerous crimes that are being committed online. It is the duty and responsibility of the legal systems to keep pace with the same and to ensure that such technologies do not become tools of exploitation and harassment. Through World Wide Web, user can circulate images, text, videos, and sounds. Websites provide a plethora of opportunities to the individuals. However, they are also used to circulate offensive content such as child sexual abuse, hate speech, and defamation. The intellectual property rights of authors and artists are also violated through the unauthorized circulation of their works. Internet provides the convenient shield of anonymity and fake identities. Errant persons become more emboldened in their offensive behavior if they think that they will not face any consequences. Those who post personal information about themselves on job and marriage websites or social networking websites are often at the receiving end of ‘cyber-stalking’. Women and minors who post their contact details become especially vulnerable since lumpen elements such as sex-offenders can use this information to target potential victims. Digital unlawful acts perpetrated against persons incorporate different law violations like the transmission of child pornography, person harassment utilizing computer, and others. The trafficking, posting, appropriation, and spread of revolting material including erotica and foul presentation, constitutes a standout amongst the most vital cyber law violations known today. The technological advancement has made the world a global village. There are virtually no boundaries in this Global village and the distance between places and people has been reduced to a mere nothing. This has influenced the phenomenon of globalization, which has created an impact on the socio-economic and the cultural texture of the society. Thus, the information technology has become a boon to the human community, but this paradigm-shift in the human being all over is also reflected in the area of crime, as along with the positives there is a wide spectrum of negatives which has become a cause of worry because the negative facets are being efficiently utilized by the sadistic minds of the society for committing crimes in the virtual environment called the Cyber Crimes.
Corrigendum to “Experimental implementation of a new multi input multi output fuzzy-PID controller in a poultry house system” [Heliyon 6 (8) (2020) e04645]

In the original published version of this article, the second author (Fathallah Rerhrhaye) had their name misspelled as Fathlah Rerhrhaye. The authors apologize for the error. Both the HTML and PDF versions of the article have been updated to correct the errors. Experimental implementation of a new multi input multi output fuzzy-PID controller in a poultry house systemLahlouh et al.HeliyonAugust 22, 2020In BriefAgriculture; Electrical engineering; Energy; Energy conservation; Process monitoring; Animal breeding; Livestock management; Green engineering; SCADA; Poultry farming; MIMO fuzzy; Energy efficiency. Full-Text PDF Open Access
Translating Hausdorff is Hard: Fine-Grained Lower Bounds for Hausdorff Distance Under Translation

Computing the similarity of two point sets is a ubiquitous task in medical imaging, geometric shape comparison, trajectory analysis, and many more settings. Arguably the most basic distance measure for this task is the Hausdorff distance, which assigns to each point from one set the closest point in the other set and then evaluates the maximum distance of any assigned pair. A drawback is that this distance measure is not translational invariant, that is, comparing two objects just according to their shape while disregarding their position in space is impossible. Fortunately, there is a canonical translational invariant version, the Hausdorff distance under translation, which minimizes the Hausdorff distance over all translations of one of the point sets. For point sets of size n and m, the Hausdorff distance under translation can be computed in time 𝒪(nm) for the L₁ and L_∞ norm [Chew, Kedem SWAT'92] and 𝒪(nm (n+m)) for the L₂ norm [Huttenlocher, Kedem, Sharir DCG'93].As these bounds have not been improved for over 25 years, in this paper we approach the Hausdorff distance under translation from the perspective of fine-grained complexity theory. We show (i) a matching lower bound of (nm)^{1-o(1)} for L₁ and L_∞ assuming the Orthogonal Vectors Hypothesis and (ii) a matching lower bound of n^{2-o(1)} for L₂ in the imbalanced case of m = 𝒪(1) assuming the 3SUM Hypothesis.
The Kanji Code: See the Sounds with Phonetic Components and Visual Patterns

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Convolutional codes over finite chain rings, MDP codes and their characterization

In this paper, we develop the theory of convolutional codes over finite commutative chain rings.In particular, we focus on maximum distance profile (MDP) convolutional codes and we provide a characterization of these codes, generalizing the one known for fields.Moreover, we relate (reverse) MDP convolutional codes over a finite chain ring with (reverse) MDP convolutional codes over its residue field.Finally, we provide a construction of (reverse) MDP convolutional codes over finite chain rings generalizing the notion of (reverse) superregular matrices.
Metric-Type Identification for Multi-Level Header Numerical Tables in Scientific Papers

Numerical tables are widely used to present experimental results in scientific papers.For table understanding, a metric-type is essential to discriminate numbers in the tables.We introduce a new information extraction task, metrictype identification from multi-level header numerical tables, and provide a dataset extracted from scientific papers consisting of header tables, captions, and metric-types.We then propose two joint-learning neural classification and generation schemes featuring pointergenerator-based and BERT-based models.Our results show that the joint models can handle both in-header and out-of-header metric-type identification problems.