Miracle-dz/UniFAR-FTUs huggingface dataset:
Convergence Technologies For Information, Communication And Entertainment (5g)

This paper describe all generations of mobile communication ranges from zero to fifth generation technology. It mainly focuses on network architecture of fifth generation technology which provides sensible broadband wireless connectivity at very high speed. As 5G mobile technology is expected to be prepared by 2020 researches are being made on progress of World Wide Wireless Web, Dynamic Ad-hoc Wireless Networks and existing Wireless World. Fifth generation also focus on Voice over IP enabled devices that user will occurrence a high level of call volume and data transmission. So the main features in 5G mobile network is that user can at the same time connect to the many wireless technologies and can switch between them.
Quality of primary care from the patient’s point of view. A systematic review. There is currently no acceptable tool for practice or research purposes.

Background To run an inventory of instruments which assess quality of care from the patients’ experiences in primary care, in the context of multi-disciplinary health-care centres and which appraise their measurement quality, taking into account the methodological quality of their validation studies. Method Systematic review using Medline, Pascal, PsycINFO, Google Scholar, Cochrane, Scopus and CAIRN. For each instrument identified, the level of evidence was assessed using the COnsensus-based Standards for the selection of health status Measurement Instruments (COSMIN) checklist; the appraisal of the psychometric quality of the measurement property using three possible quality scores and the best-evidence synthesis based on the number of studies, their methodological and psychometric quality, and the direction and consistency of the results. Details of the subscales used to capture patients’ experiences of primary care were extracted and synthesized by grouping them into 9 dimensions defined by the Institute Of Medicine (IOM). Results 29 articles describing 29 instruments were found. Constructs captured by the assessment tools included illustrated a diversity of conceptualizations of patients’ experiences of primary care. There was no clear consensus across the assessment tools included about what patient experience in primary care ought to measure. There is an overall lack of evidence of their measurement quality, either because validation is missing or because methods are poor. Conclusion Due to the lack of evidence, the choice for the most appropriate instrument is difficult. Improvement and validation of existing instruments, and the use of COSMIN-guidelines could help make evaluations more effective.
Critical Data Analysis of Flight Data Recorder for Safety of Flight

This paper presents a novel approach to perform effective analysis of critical data analysis stored in crash protected memory module. This module retains recent 25 hours of digital flight data and timing information. The data stored in it consist of information related with the various parameters applicable for current status of the behavior of the aircraft and avionics equipment. The proposed approach provides a way to analyze the critical data for further action of investigation. The analysis also help pilot to take measures to avoid crashes. The graphical analysis helps to compare various critical parameters all together to take better decision during flight and post flight. Keywords—Data Analysis, safety, critical systems, embedded systems, reliability
Proactive personality, job autonomy and career competencies as antecedents of job crafting among academicians in Zagazig University

It has been increasingly recognized that job crafting is an important employee proactive organizational behavior which leads to numerous beneficial outcomes for both the organization and employees. Therefore, it is important to investigate job crafting antecedents particularly, in the situations where job demands hinder employees' ability to perform effectively in work environment. Examples are developing countries, including Egypt. Therefore, this study aimed at exploring proactive personality, job autonomy and career competencies as antecedents of job crafting among academicians in Zagazig University in Egypt. Three basic Hypotheses were developed, data were collected by self-report survey from a stratified sample which comprised of 318 from those academicians. Multiple Regression analysis’s main findings confirmed a significant effect of each of proactive personality, job autonomy, and career competencies on job crafting among academicians in Zagazig University. Results were discussed; recommendations, limitations, and future research were presented. Key Terms: Proactive personality, job autonomy, career competencies, job crafting, academicians, Zagazig University. Volumes 3 Science Journal for Commercial Research July 2018
Análise automática do modelo de features em linha de produtos de software

A abordagem de Linhas de Produtos de Software (LPS) se preocupa com o desenvolvimento de aplicações utilizando técnicas sistemáticas de reuso de software, capturando características (features) comuns e variáveis de de uma família de sistemas pertencentes a um mesmo domínio. As características de uma LPS são comumente representadas utilizando modelos de features, que guiam a derivação (automática) dos produtos. Com isso, tornase necessária a utilização de suporte ferramental não apenas para o processo de derivação de produtos, mas também a própria análise dos modelos de features. A ferramenta Hephaestus possui funcionalidades para atender a ambos os objetivos, apesar de não suportar todas as operações de análise aplicáveis aos modelos de features. Este trabalho contribui com a implementação de novas operações para a ferramenta Hephaestus, além de realizar uma análise extensiva da escalabilidade dos modelos de features com diferentes graus de complexidade. Palavras-chave: linha de produtos para software, modelo de features, satisfatibilidade
Image Encryption for Secure Data Transfer and Image based Cryptography

With rapid progress in internet and digital imaging technology there are more and more ways to easily create, publish and distributed images. A major issue for computer networks is to prevent important information from being disclosed to illegal users. Valuable multimedia content such as digital images, however, is vulnerable to unauthorized access while in storage and during transmission over a network. Resent advances in visual cryptography, including probabilistic schemes and colored image sharing techniques were introduced. Visual cryptography is a method for protecting image based secrets that has a computation-free decoding process. This paper focuses on image feature protection techniques which enable similarity comparison among protected features. Experimental results shows that secure image retrieval can achieve comparable retrieval performance to conventional image retrieval techniques without revealing information about image content. Thus the image retrieval process becomes simple. MATLAB based coding manage the query phase of the system. Based on the simulation results, the proposed system not only shows the efficiency in hiding the attributes but also provides other advantages such as: (1) fast transmission of the retrieval image to the receiver, (2) searching made easy. This work enriches the area of secure information retrieval and can find applications in secure online services for images and videos. Keywords—Cryptography, secure image retrieval, visual cryptography, content based image retrieval, feature protection.
Pengiriman data hasil pengukuran parameter lingkungan menggunakan jaringan seluler dengan Raspberry Pi sebagai node

In this research has built a data delivery system of environmental parameters from Raspberry Pi into a webserver database for monitoring temperature, humidity, and light intensity in realtime, which used two Raspberry Pi as the two sensor nodes. Data from measurement of temperature, humidity, and light intensity of the sensor node is transmitted into the webserver via the mobile network, then the data is stored in a MySQL database, then the data is displayed in the form of websites. Applications to display the information of temperature, humidity and light intensity are made in the form of web programming with PHP and HTML discussed. With the appearance of the web is expected to facilitate the users to access through related information anywhere and anytime with the terms connected to the network internet. from this study, obtained results Raspberry Pi is able to transmit the observed data well into the webserver with a minimum data transmission delay of 1 second and 12 second maximum delay for a sensor node-1 and minimum delivery delays 1 second and 13 second maximum delay for sensor node-2. Keywords : Raspberry Pi , webserver, PHP, MySQL
The Three Tier security scheme in wireless sensor network With mobile sinks

Mobile sinks (MSs) are vital in many wireless sensor network (WSN) applications for efficient data accumulation, localized sensor reprogramming, and for distinguishing and revoking compromised sensors. However, in sensor networks that make use of the existing key predistribution schemes for pairwise key establishment and authentication between sensor nodes and mobile sinks, the employment of mobile sinks for data collection elevates a new security challenge: in the basic probabilistic and qcomposite key predistribution schemes, an attacker can easily obtain a large number of keys by capturing a small fraction of nodes, and hence, can gain control of the network by deploying a replicated mobile sink preloaded with some compromised keys. This article describes a threetier general framework that permits the use of any pairwise key predistribution scheme as its basic component. The new framework requires two separate key pools, one for the mobile sink to access the network, and one for pairwise key establishment between the sensors. To further reduce the damages caused by stationary access node replication attacks, we have strengthened the authentication mechanism between the sensor and the stationary access node in the proposed framework. Through detailed analysis, we show that our security framework has a higher network resilience to a mobile sink replication attack as compared to the polynomial pool-based scheme.
Batch

- In this paper, we present a system for batch processing and visualization of Formula 1 telemetry data. The goal of this system is to facilitate easier processing and visualization of Formula 1 telemetry data. To achieve this, a system designed for batch processing was implemented. Main features of the system are that the system can work independently with the help of a job orchestrator, which fetches and processes data after every race, as well as visualization of processed
Categorization of Thai Fast Food Based on Image Classification

This survey uses the prediction model for classification of Thai Fast Food images. The model uses a deep learning process that was trained on natural images using dataset and was fine-tuned to generate the predictive Thai fast food model. We are taking images from the dataset called Thai Fast Food which is publically available. The dataset contain images and is divided into eleven groups of food images comprised of omelet on rice, rice topped with stir-fried chicken and basil, barbecued red pork in sauce with rice, stewed pork leg on rice, Thai fried noodle, rice with curried chicken, steamed chicken with rice, shrimp-paste fried rice, fried noodle with pork in soy sauce and vegetables, wide rice noodles with vegetables and meat. The final group comprised dishes which are not members of the other ten groups listed (non tentypes), but which exist among Thai fast food. The process contains feature extraction of food and then classification. After prediction of food the calorie related to that food will be shown by the system.
Joint Responsibility of the Parent Company under Obligations of Subsidiary Company

The objective of this article is to identify the problems of joint responsibility of the parent company for the obligations of the subsidiary company and propose a solution to them. The author has used the analysis method while studying the legislation governing the joint responsibility of the parent company, its law enforcement practice and scientific literature on problems in this area. The experience of legal regulation of joint responsibility of the parent company under the obligations of the subsidiary company has been compared with the legal experience of the United States of America. Studying the conditions for holding the parent company liable for the obligations of a subsidiary, the author has concluded that at present, the Russian legislation defining the legal status of the parent companies is imperfect and needs to be changed. Accordingly, a new version of paragraph 2 of clause 2 of Article 67.3 of the Civil Code of the Russian Federation has been proposed, as well as recommendations for the Supreme Court of the Russian Federation.
Blockchain beyond Digital Currencies - A Structured Literature Review on Blockchain Applications

Attention for blockchain technology has increased continuously since the concept has been introduced in 2008. Implications of practically implementing blockchain-based solutions are yet to be explored adequately from a scientific perspective. The goal of this research is to develop a deeper understanding for the fields of studies and applications of blockchain technology. In a systematic literature review, this study provides a classification of scientific contributions that cover blockchain applications beyond financial transactions. The results outline fields of applications, potential benefits and limitations associated with blockchain-based solutions. We identify a lack of qualitative and quantitative research and conclude that the implications of utilizing blockchain technology are yet to be evaluated on an empirical scientific basis.
The great Transformer: Examining the role of large language models in the political economy of AI

In recent years, AI research has become more and more computationally demanding. In natural language processing (NLP), this tendency is reflected in the emergence of large language models (LLMs) like GPT-3. These powerful neural network-based models can be used for a range of NLP tasks and their language generation capacities have become so sophisticated that it can be very difficult to distinguish their outputs from human language. LLMs have raised concerns over their demonstrable biases, heavy environmental footprints, and future social ramifications. In December 2020, critical research on LLMs led Google to fire Timnit Gebru, co-lead of the company’s AI Ethics team, which sparked a major public controversy around LLMs and the growing corporate influence over AI research. This article explores the role LLMs play in the political economy of AI as infrastructural components for AI research and development. Retracing the technical developments that have led to the emergence of LLMs, we point out how they are intertwined with the business model of big tech companies and further shift power relations in their favour. This becomes visible through the Transformer, which is the underlying architecture of most LLMs today and started the race for ever bigger models when it was introduced by Google in 2017. Using the example of GPT-3, we shed light on recent corporate efforts to commodify LLMs through paid API access and exclusive licensing, raising questions around monopolization and dependency in a field that is increasingly divided by access to large-scale computing power.
EFFECT OF RISK ASSESSMENT BY INTERNAL AUDITOR ON EFFECTIVENESS OF LISTED COMPANIES IN NIGERIA

Past studies focused on the role of internal auditors in fraud prevention and internal auditing in relation to good corporate governance and did not explore risk assessment by internal auditor for effectiveness in an organisation with the view to prevent corporate failure. This study investigated the effect of risk assessment by internal auditor on effectiveness of listed companies in Nigeria. The study adopted a survey research design. The population of the study consisted of 24 companies selected from the eleven industrial sub-sectors of the 161 listed companies on Nigerian Stock Exchange as at 30th November, 2019. The sample frame is 5012 and sample size of 501 (comprising 401 internal auditors and 100 top management staff) representing 10% of the population. Structured questionnaire with a five point Likert – scale was administered with 87.43% response rate. Random sampling technique was adopted in the selection of the 24 companies with each chosen company representing each sector. The research instrument was subjected to content validity and test and re-test method of reliability which yield Cronbach alpha value of 0.798. Result indicated that risk assessment (RA) by internal auditors has positive effect on effectiveness (EFFTV) of listed companies in Nigeria with β = 0.194, t (438) = 9.827, p<0.05. F-Statistics of 12.653; Adjusted R2 = 0.051 with p – value of 0.000 which is statistically significant at p < 0.05. Therefore, companies’ management are advised to strengthen the internal auditors in the assessment of risk that might impact on the effectiveness of an organisation to be able to avert organisational emerging risk.
Survey on Data Routing for In-Network Aggregation: A Lightweight and Reliable Routing Approach for In-Network Aggregation in Wireless Sensor Networks

In a huge sensor network, in-network aggregation considerably reduces the amount of communication and energy consumption. Newly, the research group of people has proposed a robust aggregation structure called synopsis diffusion that unites multipath routing schemes with duplicate-insensitive algorithms to precisely compute aggregates (e.g, predicate count, sum) in spite of message losses resulting from node and transmission failures. However, this aggregation framework does not attend to the problem of false sub cumulative values contributed by compromised nodes resulting in large errors in the collective computed at the base station, which is the root node in the aggregation hierarchy, This is an important problem since sensor networks are extremely vulnerable to node compromises due to the unattached nature of sensor nodes and lack of tamper-resistant hardware. In this paper we have presented introduction about wireless sensor network, data aggregation, application of wireless network, routing protocol, aggregation network and we have also proposed data aggregation in WSN. Keywords-; Routing Protocol; Data Aggregation; WSN
Cross-Sectional Surveys as A Tool To Study Epidemiological Factors And Exploring Social Dynamics of Seasonal Influenza In Malta

Background: Seasonal influenza has major implications for healthcare services as outbreaks often lead to high activity levels in the health system. Mathematical models have extensively been used to predict epidemics of infectious diseases such as seasonal influenza and to assess effectiveness of proposed control strategies. However, the availability of comprehensive and reliable datasets is limited. In this paper we combine a unique epidemiological dataset collected in Malta through GPs with a novel method that uses cross-sectional surveys to study the dynamics of seasonal influenza in Malta in 2014-2016, to include social dynamics and self-perception related to seasonal influenza.Methods: Two cross-sectional public surveys (n=406 per survey) were performed by phone across the Maltese population in 2014-15 and 2015-16 influenza seasons. Survey results were compared with incidence data (diagnosed seasonal influenza cases) collected by GPs in the same period and with Google Trends data for Malta. The information was collected on whether participants recollected their health status in past months, occurrences of influenza symptoms, hospitalisation rates due to seasonal influenza, whether they sought GP advice, and other medical information. Results: We demonstrate that cross-sectional surveys are a reliable alternative source of data to medical records. The two surveys gave comparable results, indicating that the level of recollection among the public is high. Based on two seasons of data, the reporting rate in Malta varies between 14% and 22%. The comparison with Google Trends suggests that the online searches peak at about the same time as the maximum extent of the epidemic, but then the public interest declines and returns to the background level. We also found that the public intensively searched the Internet for influenza-related terms even when the number of cases was low.Conclusions: Our research shows that a telephone survey is an appropriate way to gain deeper insight into the population self-perception of influenza and its symptoms and to provide another benchmark for medical statistics provided by GPs and Google Trends. The information collected in different ways can be used to improve epidemiological modelling capacity for seasonal influenza and other infectious diseases, thus contributing to public health.
Electric power converter

Provided is an electric power converter. A First and second series circuits of switching devices and a series circuit of capacitors are connected in parallel. Between the connection point in the first series circuit of switching devices and the connection point in the series circuit of capacitors, a first bidirectional switch is connected and, between the connection point in the second series circuit of switching devices and the connection point in the series circuit of capacitors, a second bidirectional switch is connected. The connection point in the first series circuit of switching devices is connected through a reactor to an input-output common connection line connected to one end of an AC power supply and the other end of the AC power supply is connected to the connection point in the series circuit of capacitors.
Eliminate Aspect Angle Variations for Human Activity Recognition using Unsupervised Deep Adaptation Network

Activity recognition and monitoring using radar micro-Doppler signatures ($\boldsymbol{\mu}-\mathbf{DS}$) classification has played an vital part in various security and healthcare applications. In the practical scenario, aspect angle variations of $\boldsymbol{\mu}-\mathbf{DS}$ increase the data diversity but can be regarded as a distraction factor for activity recognition. The learned feature extractor and classifier will degrade a lot if the test $\boldsymbol{\mu}-\mathbf{DS}$ is from a different aspect angle from the training dataset. This is because the aspect angle variations between training and test dataset will break the assumption of the classification methods: the training and test data are drawn from the same distribution. This paper aims to eliminate the aspect angle variations by learning aspect angle invariant and meanwhile discriminative features in the bi-static radar geometry using the unlabeled test data. More specifically, we first propose a new problem to train a feature extractor using certain aspect angles but generalizes well for other aspect angles in the test stage. Next, we propose two adaptation networks termed as MMD-DAN and JS-DAN, utilizing two widely used distribution divergence measurements. Finally, we evaluate our experimental setting and methods using experimental data.