Miracle-dz/UniFAR-FTUs huggingface dataset:
Intrusion Detection and Anomaly Detection System Using Sequential Pattern Mining

Nowadays the security methods from password protected access up to firewalls which are used to secure the data as well as the networks from attackers. Several times these type of security methods are not enough to protect data. We can consider the use of Intrusion Detection Systems (IDS) is the one way to secure the data on critical systems. Most of the research work is going on the effectiveness and exactness of the intrusion detection, but these attempts are for the detection of the intrusions at the operating system and network level only. It is unable to detect the unexpected behavior of systems due to malicious transactions in databases. The method used for spotting any interferes on the information in the form of database known as database intrusion detection. It relies on enlisting the execution of a transaction. After that, if the recognized pattern is aside from those regular patterns actual is considered as an intrusion. But the identified problem with this process is that the accuracy algorithm which is used may not identify entire patterns. This type of challenges can affect in two ways. 1) Missing of the database with regular patterns. 2) The detection process neglects some new patterns. Therefore we proposed sequential data mining method by using new Modified Apriori Algorithm. The algorithm upturns the accurateness and rate of pattern detection by the process. The Apriori algorithm with modifications is used in the proposed model.
Prevalence and Characteristics of Voice Disorders in a Sample of University Teaching Faculty

ABSTRACT: Purpose: This study examined the prevalence of voice disorders in university teaching faculty as well as demographic and behavioral variables linked with voice disorders in past research. Method: One hundred participants completed a survey. Results: Of the 100 participants, 45 reported vocal difficulties that were substantial enough to interfere with normal communication. Symptoms were consistent with vocal overuse, including increased effort, hoarseness, decreased loudness, and vocal discomfort. Demographic and health/behavioral risk factors (e.g., age, gender, allergies, acid reflux, use of tobacco/alcohol) had little apparent effect on the prevalence of a voice disorder. A comparison with past data suggested that this sample of university faculty had a higher than average prevalence of voice disorder, although it was lower than levels reported for kindergarten through high school teachers. Conclusion: Voice disorder is a considerable problem among university teaching faulty members. The demographic and behavioral factors associated with voice disorder in past studies were not significantly related to voice disorder in the present study. The results suggest that the demands of teaching, and not other demographic and behavioral factors, underlie voice disorder for the faculty participants.
Seven Years after the Manifesto: Literature Review and Research Directions for Technologies in Animal Computer Interaction

As technologies diversify and become embedded in everyday lives, the technologies we expose to animals, and the new technologies being developed for animals within the field of Animal Computer Interaction (ACI) are increasing. As we approach seven years since the ACI manifesto, which grounded the field within Human Computer Interaction and Computer Science, this thematic literature review looks at the technologies developed for (non-human) animals. Technologies that are analysed include tangible and physical, haptic and wearable, olfactory, screen technology and tracking systems. The conversation explores what exactly ACI is whilst questioning what it means to be animal by considering the impact and loop between machine and animal interactivity. The findings of this review are expected to form the first grounding foundation of ACI technologies informing future research in animal computing as well as suggesting future areas for exploration.
A Simple Growth Model Based on Neoclassical Growth, Monopolistic Competition, and Walrasian General Equilibrium Theories

Copyright: © 2019 The Author(s) Published by Human Resource Management Academic Research Society (www.hrmars.com) This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode
Multi-Client Server Communication Enhancement through Intranet

: Chat application is a platform of communication which provides real time transmission of information in the form of text messages or files. The following chat application does not use internet for its operation. It requires all the computers to be connected in a single network, where one of the computers is considered as servers and all others as clients. Every user needs to make a request to the server using the server’s IP address and port number. The sender can later select the intended receiver from the list of online users. The sender can also chose to broadcast the message to all the online users. The user can also chose to share various files in different file formats.
T-tree Index Optimization Based on Main Memory Database

: Main memory database is a database management system in which the total or most of data are stored in the main memory. In order to implement this method, new data structure and algorithm need to be designed and the goal is the efficient application of CPU time and main memory space. In this paper, main memory database and index are introduced, T-tree index algorithm which is the most representative is research and analysis, and the T-tree optimization ideas are put forward.
Designing Scalable and High Performance One Sided Communication Middleware for Modern Interconnects

High-end computing (HEC) systems are enabling scientists and engineers to tackle grand challenge problems in their respective domains and make significant contributions to their fields. Examples of such problems include astro-physics, earthquake analysis, weather prediction, nanoscience modeling, multiscale and multiphysics modeling, biological computations, computational fluid dynamics, etc. There has been great emphasis on designing, building and deploying ultra scale HEC systems to provide true petascale performance for these grand challenge problems. At the same time, Clusters built from commodity PCs are being predominantly used as main stream tools for high-end computing owing to their cost-effectiveness and easy availability. Communication subsystem plays a pivotal role in achieving scalable performance in clusters. Of late there has been a lot of interest in one-sided communication model and they are seen as a viable option for petascale applications. The one-sided communication provides good potential for computation communication overlap. In order to provide high performance and scalability, the one-sided communication subsystem needs to be designed to leverage the advanced capabilities of the modern interconnects.
Determinants of Effectiveness of Performance Appraisal (EPA) for Academics in Nigerian Higher Education Institutions (HEIs): A Pilot Study

Effective performance appraisal (EPA) is indispensable to organizations in establishing their accomplishments as well as improving employees’ performance. Previous literature has indicated the impacts of organizational fairness, organizational politics, transactional leadership and employee’s participation on performance appraisal (PA). The objective of this study is to confirm the validity and reliability of the research instruments in examining the relationships between organizational fairness, Politics, transactional leadership, and employees’ participation on EPA among academics in Nigeria. A survey method was employed, and a total of 40 questionnaires set was distributed to respondents via convenience sampling. Results confirmed the validity and reliability of the instruments adapted.
Analysis and design of space-time block codes for coded MIMO transmissions. (Analyse et conception de code espace-temps en blocs pour transmissions MIMO codées)

Most of the modern wireless communication systems as WiMAX, DVB-NGH, WiFi, HSPA+ and 4G have adopted the use of multiple antennas at the transmitter and the receiver, called multiple-input multiple-output (MIMO). Space time coding for MIMO systems is a promising technology to increase the data rate and enhance the reliability of wireless communications. Space-time block codes (STBCs) are commonly designed according to the rank-determinant criteria suitable at high signal to noise ratios (SNRs). In contrast, wireless communication standards employ MIMO technology with capacity-approaching forward-error correcting (FEC) codes like turbo codes and low-density parity-check (LDPC) codes, ensuring low error rates even at low SNRs. In this thesis, we investigate the design of STBCs for MIMO systems with capacity-approaching FEC codes. We start by proposing a non-asymptotic STBC design criterion based on the bitwise mutual information (BMI) maximization between transmitted and soft estimated bits at a specific target SNR. According to the BMI criterion, we optimize several conventional STBCs. Their design parameters are shown to be SNR-dependent leading to the proposal of adaptive STBCs. Proposed adaptive STBCs offer identical or better performance than standard WiMAX profiles for all coding rates, without increasing the detection complexity. Among them, the proposed adaptive trace-orthonormal STBC can pass continuously from spatial multiplexing, suitable at low SNRs and therefore at low coding rates, to the Golden code, optimal at high SNRs. Uncorrelated, correlated channels and transmit antenna selection are considered. We design adaptive STBCs for these cases offering identical or better performance than conventional non-adaptive STBCs. In addition, conventional STBCs are designed in a way achieving the asymptotic DMT frontier. Recently, the finite-SNR DMT has been proposed to characterize the DMT at finite SNRs. Our last contribution consists of the derivation of the exact finite-SNR DMT for MIMO channels with dual antennas at the transmitter and/or the receiver. Both uncorrelated and correlated Rayleigh fading channels are considered. It is shown that at realistic SNRs, achievable diversity gains are significantly lower than asymptotic values. This finite-SNR could provide new insights on the design of STBCs at operational SNRs.
Doubly disadvantaged? Gender, informal job search, and labor market outcomes among South Korea’s immigrant workers

This research investigates the gendered labor market consequences of immigrant social networks. Based on a nationally representative sample and using alternative analytic strategies, the present study investigates how and the extent to which informal job search, that is, finding a job through a personal contact, is associated with the earnings outcome for male and female immigrant workers in South Korea. Unlike most previous studies, it distinguishes between job contact sources: bonding and bridging. Contrary to the notion that immigrant women are ‘doubly disadvantaged’ in the labor market, findings indicate that informal job search yields lower monthly income for male workers only. In addition, significant evidence suggests that for the male subsample, securing a job through a bonding (co-ethnic) tie results in an earnings penalty. Negative income returns on using a bridging (inter-ethnic) tie, on the other hand, receive conditional empirical support.
The effects of aging and perceived loneliness on lexical ambiguity resolution

Language is central to the interactional nature of the social life within which it is situated. To react or respond in a particular situation, we must be able to recognize the social situation. Growing evidence has demonstrated the negative impact of perceived loneliness on late-life executive functions. Yet little is known about how social factors impact language processing for older people. The current study aims to fill this gap, first by assessing age-related changes in lexical processing during Chinese word reading, second, by examining whether older adults’ individual differences, such as processing speed and verbal abilities, modulate meaning retrieval and, third, by investigating whether perceived loneliness can hinder word reading. The use of compound words in Chinese enables significant sublexical ambiguity, requiring varying executive load during word recognition: when a word’s constituent characters carry multiple meanings, readers must consider the meaning contributions of both constituent characters and use top-down word information to determine the most accurate meaning of the ambiguous character, a process termed “sublexical ambiguity resolution. ” In this study, adults read real Chinese words (including both sublexically ambiguous and unambiguous words) and pseudowords, and they were asked to make lexical decisions. Older adults exhibited greater lexicality effects (i.e., real words were easier to be identified than pseudowords) and similar sublexical ambiguity effects compared with young adults. Among older participants, processing speed could account for their ability to differentiate between words and pseudowords. In contrast, the level of perceived loneliness modulated the efficacy of sublexical ambiguity resolution: the participants with higher perceived loneliness displayed a greater sublexical ambiguity disadvantage effect. These results indicate that perceived loneliness may affect the use of contextual information in meaning retrieval during reading. The findings provide an important link between social connections and language processing.
Are there periodically collapsing bubble behaviours in the global coffee market?

ABSTRACT This paper investigates price bubbles in the global coffee market using the generalised supremum augmented Dickey-Fuller test. This approach can recognise multiple bubbles and date their origination and termination. The empirical results show that three bubbles existed in the coffee market from January 1990 to September 2017, during which the coffee price deviated from its fundamental value. Mismatch between supply and demand, speculation, US dollar fluctuations and climate change are applied to explain these bubbles. Corresponding policies, such as the prevention of pests and disease, emergency assistance, market structure improvement and recognition of US dollar fluctuations, should be emphasised to relieve the negative impacts of excessive coffee price volatility.
Data Quality Improvement through Horizontal Fragmentation in Data Warehouses

In this paper we propose the procedure forhorizontal fragmentation of data warehouse tables andshow how it affects data warehouse’s data quality, namely, completeness and timeliness data qualitydimensions. Horizontal fragmentation is suitable whendata from multiple, more or less independent, organizational units are stored in the same fact table. Insuch cases, proposed procedure enables horizontal dataseparation based on the configured attributes thusisolating one institution’s data quality problems fromanother. The proposed procedure relies on metadata andis generic and applicable to any data warehouse.
Belief Value Development In Dempster-Shafer With Particle Swarm Optimization(PSO) For Determining Of The Provision On Cases Of Persecution

The problem of uncertainty often becomes an obstacle, especially in terms of diagnosing the provision in this study. There is an algorithm that can solve this problem is Dempster-shafer (D-S), this algorithm has belief value that serves to determine the influence between symptoms. Belief value is obtained from experts, when there are new symptoms must have to ask the experts to know the value of belief, and takes time as well. So the Particle Swarm Optimization (PSO) algorithm will help generate and optimize the value of belief in D-S. PSO is able to produce optimal belief value. This research is to generate value belief D-S with PSO.
Consumers’ Intention to Stay in Green Hotels in Australia: Theorization and Implications

Despite multiple calls to protect the environment, adopting environmentally friendly behaviors is still considered to be one of the most persistent challenges in behavior transformation agendas. This study sought to expand existing knowledge of hotel consumers’ green behaviors by developing and testing an extended model of the theory of planned behavior. More specifically, this study incorporated past experience into the theory of planned behavior model to understand comprehensively consumers’ decision-making processes with respect to their intentions to stay at a green hotel. Results from the structural model from a sample of 781 Australian travelers showed that the proposed theoretical framework had a strong ability to predict intention and identified the prominent role of past experience in generating intention. The results offer further perspectives into consumers’ decision-making processes, which can assist hotel managers in the development and execution of hotel operations accounting for consumers’ environmentally friendly purchase behavior.
Meeting an un-MET need: Targeting MET in non-small cell lung cancer

The MET pathway can be activated by MET exon 14 skipping mutations, gene amplification, or overexpression. Mutations within this pathway carry a poor prognosis for patients with non-small cell lung cancer (NSCLC). MET exon 14 skipping mutations occur in 3-4% of patients with NSCLC, while MET amplifications are found in 1-6% of patients. The most effective method for detection of MET amplification is fluorescent in situ hybridization (FISH) and of MET exon 14 skipping mutations is RNA-based next generation sequencing (NGS). Immunohistochemistry (IHC) is an alternative method of diagnosis but is not as reliable. Early studies of MET tyrosine kinase inhibitors (TKIs) demonstrated limited clinical benefit. However, newer selective MET TKIs, such as capmatinib and tepotinib, have improved efficacy. Both drugs have an acceptable safety profile with the most common treatment-related adverse event being peripheral edema. One of the most frequent resistance mechanisms to EGFR inhibition with osimertinib is MET amplification. There is interest in combining EGFR inhibition plus MET inhibition in an attempt to target this resistance mechanism. Additional ways of targeting MET alterations are currently under investigation, including the bi-specific antibody amivantamab. Additional research is needed to further understand resistance mechanisms to MET inhibition. There is limited research into the efficacy of immune checkpoint inhibition for MET-altered NSCLC, though some data suggests decreased efficacy compared with wild-type patients and increased toxicity associated with the combination of immunotherapy and MET TKIs. Future directions for research will include combination clinical trials and understanding rational combinations for MET alterations.
Creating a Statewide Absence Policy for Expecting and Parenting Students: A Case Study of Community-Based Policy Work

Community-based coalitions can be a powerful force for social change. This article describes how a group of organizations and individuals combined their knowledge and strengths to succeed in crafting an educational policy that was signed into state law. The Young Parent Working Group is a multidisciplinary coalition that advocates for the educational attainment of expecting and parenting students. This case-study highlights the progression of the initial policy development, the evolution of the group, successful interpersonal processes, legislation, messaging, lobbying for bi-partisan support, and finally the transition to policy implementation and next steps.
Use of Probiotics For Oral Health

The term “probiotic” was first used in 1965, by Lilly and Stillwell, to describe substances secreted by one organism which stimulate the growth of another. The number of products containing probiotics, viable bacteria with proven health benefits, entering the market is increasing. The use of antibiotics, immunosuppressive therapy and irradiation, amongst other means of treatment, may cause alterations in the composition and have an effect on the GIT flora. Therefore, the introduction of beneficial bacterial species to GI tract may be a very attractive option to re-establish the microbial equilibrium and prevent disease. Traditionally, probiotics have been associated with gut health, and most clinical interest has been focused on their use for prevention or treatment of gastrointestinal infections and diseases; however, during the last decade several investigators have also suggested the use of probiotics for oral health purposes.
Modeling Green Entrepreneurial Intention among University Students Using the Entrepreneurial Event and Cultural Values Theory

Going green has created significant enthusiasm across the society. However, green entrepreneurial intention is still at evolving stage. The main objective of this study is to reveal the association of entrepreneurial event theory and cultural values theory with the green entrepreneurial intention. Cross sectional survey was conducted through structured questionnaire among the university students. Partial least squares method has been adopted using the SmartPLS 3.0 software for analysing the data from 835 respondents. The findings of the results revealed that perceived desirability, perceived feasibility, opportunity seeking, and reasonability taking plays significant role for green entrepreneurial intention. The result of the study will provide the governments to explore opportunities for the green entrepreneurial ventures among universities. Universities may offer customised academic courses, or training program to trigger the green business initiative among the students. Students will be benefited to learn the essentials of green entrepreneurial intention from this research.
Optimization of Spatial Convolution in ConvNets on Intel KNL

Most of the experts admit that the true behavior of the neural network is hard to predict. It is quite impossible to deterministically prove the working of the neural network as the architecture gets bigger, yet, it is observed that it is possible to apply a well engineered network to solve one of the most abstract problems like image recognition with substantial accuracy. It requires enormous amount of training of a considerably big and complex neural network to understand its behavior and iteratively improve its accuracy in solving a certain problem. Deep Neural Networks, which are fairly popular nowadays deal with such complicated and computationally intensive neural networks and their training process usually takes hours,days or, in some cases months,to achieve a particular accuracy. This opens up an opportunity for code modernizers and computer architecture experts to systematically study and optimize the core computational modules of the deep neural networks or simply DNN’s. In this thesis one such module called Spatial Convolution module is selected. This module is seen in most popular DNN architectures today and is also a major computational bottleneck. It is optimized for Intel Architecture, specifically the Knights Landing Architecture which is a powerful many-core processor introduced recently by Intel. The main strategy here was to use an unconventional convolution algorithm called Winograd Convolution algorithm to decrease the number of arithmetic operations. However, the reduction of arithmetic operations in Winograd algorithm comes at the cost of complicating the memory accesses. So the objective was to use