Miracle-dz/UniFAR-FTUs huggingface dataset:
IMAGE BASED WEATHER AND TEMPERATURE ANALYSIS SYSTEM

Weather prediction is always a hot topic, as it has great importance in many fields. Recent issues related to climate change shows the importance of weather in man’s daily life. Weather information has a big social impact. There are a lot of methods to predict weather conditions but most of them use additional hardware. For an example, weather prediction using separate weather satellites. These methods are very expensive. This is the place where image based weather recognition is important. Image based weather recognition is an emerging topic. Images carry a lot of information to understand weather. The main advantage of image based weather recognition is large quantity of data, compare to other methods it doesn’t need additional hardware, comparatively less cost and images are easily accessible. Image based weather recognition has large applications like driving assistance, robotics etc. Convolutional neural network, a deep learning method is used to identify the weather information. Weather is divided in to six classes: cloudy, haze, rainy, snowy, sunny, thunder. Images are considered as clusters and each cluster is considered for feature extraction. Temperature analysis is the other field in this work. Even though temperature is influenced by many factors like humidity, pressure, weather etc. Weather has a great influence on temperature. Temperature analysis is calculated using the scores obtained in each weather classes. Keywords—Convolutional Neural Network , VGG16, Euclidean Distance, Image based Weather Recognition.
NerveNet: Learning Structured Policy with Graph Neural Networks

We address the problem of learning structured policies for continuous control. In traditional reinforcement learning, policies of agents are learned by multi-layer perceptrons (MLPs) which take the concatenation of all observations from the environment as input for predicting actions. In this work, we propose NerveNet to explicitly model the structure of an agent, which naturally takes the form of a graph. Speciﬁcally, serving as the agent’s policy network, NerveNet ﬁrst propagates information over the structure of the agent and then predict actions for different parts of the agent. In the experiments, we ﬁrst show that our NerveNet is comparable to state-of-the-art methods on standard MuJoCo environments. We further propose our customized reinforcement learning environments for benchmarking two types of structure transfer learning tasks, i.e., size and disability transfer , as well as multi-task learning . We demonstrate that policies learned by NerveNet are signiﬁcantly more transferable and generalizable than policies learned by other models and are able to transfer even in a zero-shot setting.
Cultural and Economic Risks Factors in UAE Construction Projects

The United Arab Emirates (UAE) construction industry is an essential part of the country’s economy. It provides a significant contribution to employment, housing, commercial buildings and infrastructure. The aim was to study various risks and risk factors related to success of UAE construction projects. An in-depth interview approach involving clients, contractors and consultants was used. It was noted that the differing perspectives of the three main categories of clients, contractors and consultants were critical to success, with communication factors amongst the three identified as playing a most critical role in success. A large of cultural difference was also noted within the workers in UAE industry. There was a lack of understanding of the effects and mechanisms of the risks associated with cultural diversity, including optimal ways to deal with issues and risks. Specifically, this paper identifies the major cultural and economic risks factors that impact the success of large projects.
Automatic Detection of Onset Time of Seismic Waves and its Confidence Interval Using the Autoregressive Model Fitting

Although several techniques have been proposed for a computer-based automatic detection of P and S onset times of small earthquakes, some seismologists have been felt hesitation in using such onset time data on a routine basis. This is mainly due to a lack of parameters judging precision of detected onset times. This paper aimed to introduce a new mathematical aspect for the confidence interval of onset time estimate and to apply the practical tests. After the autoregressive model parameters have been estimated at two windows immediately preceding and behind P or S onset of an earthquake, the likelihood functions for the two models are defined by assuming normality of probability density function of residual time series. The log-likelihood function of the joint model, which is introduced by using of the above mentioned likelihood functions, gave a basis for onset time picking and statistical inference of a confidence interval time. P and S onset times and their 90% confidence interval were automatically estimated for more than one hundred seismograms of microearthquakes. The result made good comparisons with the manual pickings by several persons. When the signal-to-noise ratio is about 10 dB, the 90% confidence interval times are estimated to be 0. 2 and 0. 8 seconds for P and S onsets, respectively.
Functional comparison of the present algorithm on hardware and software embedded platforms

This article shows the implementation of the cryptographic algorithm "Present" in both software and hardware embedded platforms, for which measurements of the performance results of the implementation of the algorithm are performed on the different microcontrollers and also on FPGA type programmable logic devices. Encryption and decryption functions are performed using 80-bit key sizes, performing operation tests for the test vectors. In the microcontroller type software platforms, the use of program memory (FLASH), use of data memory (RAM) and throughput are taken into account; all of this keeping in mind the size of the processor bus and if the processor has pointers to functions or tables and the CPU speed measured in millions of instructions per second MIPS. As for hardware embedded platforms, in this case the throughput, it is significantly higher due to the 1298 Edwar Jacinto Gómez et al. parallelism characteristic of the devices, but the reduction of the use of resources in terms of occupied Slices is sought (CLB-GE); These Slices or functional blocks are different for each company, which makes them difficult to compare.
Development of Spreadsheet-Based Integrated Transaction Processing Systems and Financial Reporting Systems

Development of spreadsheet-based integrated transaction processing systems and financial reporting systems is intended to optimize the capabilities of spreadsheet in accounting data processing. The purpose of this study are: 1) to describe the spreadsheet-based integrated transaction processing systems and financial reporting systems; 2) to test its technical and operational feasibility. This study type is research and development. The main steps of study are: 1) needs analysis (need assessment); 2) developing spreadsheet-based integrated transaction processing systems and financial reporting systems; and 3) testing the feasibility of spreadsheet-based integrated transaction processing systems and financial reporting systems. The technical feasibility include the ability of hardware and operating systems to respond the application of accounting, simplicity and ease of use. Operational feasibility include the ability of users using accounting applications, the ability of accounting applications to produce information, and control applications of the accounting applications. The instrument used to assess the technical and operational feasibility of the systems is the expert perception questionnaire. The instrument uses 4 Likert scale, from 1 (strongly disagree) to 4 (strongly agree). Data were analyzed using percentage analysis by comparing the number of answers within one (1) item by the number of ideal answer within one (1) item. Spreadsheet-based integrated transaction processing systems and financial reporting systems integrate sales, purchases, and cash transaction processing systems to produce financial reports (statement of profit or loss and other comprehensive income, statement of changes in equity, statement of financial position, and statement of cash flows) and other reports. Spreadsheet-based integrated transaction processing systems and financial reporting systems is feasible from the technical aspects (87.50%) and operational aspects (84.17%).
Affective variables in the transition from school to university mathematics

The transition from school to university mathematics is a difficult step for students, which many of them do not succeed to manage immediately. In this contribution we use questionnaires, which measure mathematics-related affective variables as well as subject-unspecific affective variables and students' achievement during the semester to predict the outcome of the exams at the end of the first semester (as a first indicator for success in their studies) and the students' attendance in this exams (as an indicator for early dropout). We are interested in whether the mathematics-related or the “general” affective variables are more suitable to predict the students' exam attendance and the exam outcome. The students' achievements during the semester turned out to be the best predictor for the exam outcome, whereas the students' attendance was best predicted by their interest in mathematics.
Current Research State of Irregular Objects Simulation

To simulate each kind of natural phenomenon is an important exploration computer graphics domain, especially for those irregular objects is a difficult problem. This paper presented a survey on several methods for modeling and simulating irregular objects such as flame, smoke, and clouds. Some main research methods are introduced briefly, and the future development trend of irregular objects simulation will be given in this paper.
Adoption Spells of Improved Potato Varieties by Smallholder Farmers in Eastern Ethiopia: The Duration Approach

Potato is mainly tagged as a food security crop in Ethiopia. However, its productivity remains low due to low adoption of improved technologies by smallholder farmers. Duration models, namely, Parametric (Weibull) and Non-parametric (Kaplan Meier) were used to analyze the data gathered from 365 sample farmers. The Non-parametric result revealed that the average duration that potato growers should wait before adopting a new variety is about 3.5 years. The Weibull regression indicated that timely availability of seed, access to labor and irrigation water, land size, and adaptation strategy by farmers are found to be factors curtailing the timeframe to adopt improved potato varieties. The regression analysis revealed that costs of inputs such as manure and compost, environmental and market factors such as drought, pest and disease outbreaks, price variability of potato seed, and quality of potato seed were found to be factors influencing adoption decisions of improved potato varieties by smallholder farmers.
Comparative Adaptability Assessment of Two Mangroves from Indian Sundarbans: Some Biochemical Appearances

Comparative adaptability against salinity was assessed between the two wellknown mangroves (Avicennia marina and Heritiera fomes) from Indian Sundarbans in vitro. Occurrence of H. fomes is intermittent in and around of this mangrove swamp. A harmony has to maintain between ROS production and efficient scavenging of ROS by the plant itself for sustainability. In the present work, extent of salt tolerance was evaluated by mainly two ways: i) accumulation of free amino acids in the cytoplasm for proficient osmotic adjustment and ii) promoting elevated amount of antioxidants (both enzymes and secondary metabolites) with respect to substrate salinity. Occurrence of free amino acids (Alanine, Leucine and Proline) in A. marinaare well correlated (p ≤ 0.01) with the increasing salinity and H. fomes (Alanine and Phenyl Alanine) correlation value showed p ≤ 0.05. ROS scavenging reflected through ABTS, DPPH and Fe2+ chelating activity and results indicating that A. marina have some advantage over the other investigated taxa. Amount of phenols and flavonoids also designated the same. Additional number of isoforms of two antioxidant enzymes (peroxidase and super oxide dismutase) occurred in A. marina as the salinity enhanced, but in case of H. fomes, which was lacking. The experimental results might be designated towards the comfortable adaptability to A. marina, rather to H. fomes.
IMPLEMENTASI FUZZY C-MEANS UNTUK PREDIKSI PERILAKU MAHASISWA BERDASARKAN JUMLAH KETIDAKHADIRAN

Dalam kegiatan belajar mengajar di perguruan tinggi, mahasiswa dituntut tertib dalam melaksanakan perkuliahan. Sebagai syarat agar mahasiswa dapat melanjutkan ke semester berikutnya adalah jumlah kehadiran dan indeks prestasi. Dalam pelaksanaannya, selalu ada mahasiswa bermasalah yang melakukan pelanggaran yaitu jumlah ketidakhadiran yang melebihi batas sehingga harus diterbitkan Surat Peringatan, atau bahkan putus studi. Tujuan surat peringatan ini adalah agar mahasiswa mengetahui status akademiknya sekaligus memunculkan efek jera agar kesalahan yang serupa tidak diulangai lagi. Namun pada prakteknya, masih ada saja mahasiswa yang melanggar meskipun sudah pernah mendapatkan surat peringatan. Kecenderungan yang terjadi adalah mahasiswa yang memiliki jumlah ketidakhadiran cukup banyak selama beberapa semester, pada semester berikutnya jumlah ketidakhadirannya pun akan banyak lagi. Hal ini juga berdampak pada indeks prestasi semesternya. Dalam penelitian ini akan dibuat sebuah sistem yang dapat mengklasifikasikan mahasiswa berdasarkan jumlah ketidakhadiran mahasiswa selama dua semester. Metode klasifikasi yang digunakan adalah clustering dengan Fuzzy C-Means. Hasil klasifikasi digunakan untuk memprediksi perilaku mahasiswa di semester berikutnya. Diharapkan penelitian ini akan bermanfaat untuk proses pembinaan mahasiswa dalam menempuh kegiatan belajar mengajar di perguruan tinggi.
Improving Kurdish Web Mining through Tree Data Structure and Porter’s Stemmer Algorithms

Stemming is one of the main important preprocessing techniques that can be used to enhance the accuracy of text classification. The key purpose of using the stemming is combining the number of words that have same stem to decrease high dimensionality of feature space. Reducing feature space cause to decline time to construct a model and minimize the memory space. In this paper, a new stemming approach is explored for enhancing Kurdish text classification performance. Tree data structure and Porter’s stemmer algorithms are incorporated for building the proposed approach. The system is assessed through using Support Vector Machine (SVM) and Decision Tree (C4.5) to illustrate the performance of the suggested stemmer after and before applying it. Furthermore, the usefulness of using stop words are considered before and after implementing the suggested approach.
On the Application of Particle Swarm Optimization in Minimum Time Launch Vehicle Trajectory Optimization Problem

The application of Particle Swarm Optimization (PSO), in solving minimum time trajectory optimization problem, studied in this paper. The ascent phase of a launch vehicle trajectory is considered, due to its highly nonlinear nature. It is one of the challenging problems in optimization scenario. Achieving the target in minimum time and error, satisfying all the constraints is the major objective. A highly nonlinear complex system, launch vehicle, is considered with the control parameter as its angle of attack. It is proved that, PSO approach outperforms other such type of optimization, procedures in trajectory optimization scenario, by providing better accuracy. The numerical results are evaluated, analyzed and presented in a MATLAB simulation environment.
Interface Design for Hyperdata: Models, Maps and Cues

Now that large stores of information in a variety of media can truly be at our fingertips, how do we know what we have and how to get at it? Hypermedia databases present new challenges to interface designers whose goals are to make such databases truly accessible and easy to use. In this paper, using HyperCard (1987) as an example, I discuss some of the user interface issues that arose as we observed children and adults interacting with computerized hypermedia environments. And I describe some design principles and examples that have emerged from our work in the Human Interface Group at Apple Computer, Inc.
Analysis of Receptive and Expressive Vocabulary Test Performancein Children of Varying Language Abilities

This study examined the results of receptive and expressive vocabulary tests to investigate the strength of semantic representations. Participants in this research consisted of 24 children, 16 males and 8 females, from ages 5-13. A series of tests measuring language ability and attention were administered to the participants. For the purposes of this research the Expressive Vocabulary Test (EVT II) and the Peabody Picture Vocabulary Picture Test (PPVT IV) were analyzed to determine how the participants’ semantic representations were related to their expressive and receptive abilities. In the context of this thesis semantic representation refers to a child’s ability to pair the meaning of a word with a referent. Although many of the participants earned scores on the two tests that were comparable, some participants had scores that differed by at least one standard deviation. The hypothesis states, for those that had a difference between their EVT and PPVT score of at least one standard deviation, their receptive scores should be higher than the expressive scores because the receptive test puts less stress on semantic representations. The hypothesis was tested by comparing the results of the EVT and the PPVT. The results from comparing the EVT and PPVT revealed that receptive scores were better than expressive scores. In addition to comparing the EVT and PPVT, the hypothesis was supported through further analysis of the EVT where a pattern of errors was established. The errors were also broken down into seven categories. It was determined that the errors of those who had better receptive scores, could be categorized into category member errors and semantically related responses. The results suggest that fine-grained analysis of receptive and expressive vocabulary scores may provide better understanding of the semantic representations of children with and without language impairment.
Indoor air CO2 assessment of classrooms of educational institutes of hyderabad city and its comparison with other countries

Indoor air quality is given lot of importance in modern societies and healthy environment. We spend most of time at indoor homes, workplace, offices, schools, hospitals, factories or even at the shopping malls e.t. c. The buildings may have good or bad indoor air quality (IAQ). Bad indoor air quality leads adverse impacts. If the Indoor air quality is not so good and tends to get poor then it affects the health, and the apparent effects get severe ultimately causing death. This study focuses on the assessment indoor air CO2 in classrooms of the educational institutes. To conduct the research work, many important studies from literature are surveyed and the standard followed internationally for the normal and abnormal levels of indoor air CO2 are kept as reference to rate the measured values. For the purpose of analysis, one government school, two private schools and two private centers are selected. During various visits to the institutions the required physical data regarding dimensions and conditions of classrooms are collected, which consists of number of doors, windows with dimensions and location, ventilation mode and number of fans etc. For noting these results, a data sheet is used. A questionnaire is also used to know the perceptions of teachers of these institutes about the impact of IAQ on the performance of students, teachers and several factors are analyzed in SPSS software. The indoor air CO2 is found to be in fair, good and excellent ranges in most of the institutes. However, in some classrooms, the CO2 concentrations is in higher ranges indicating the possibility of contaminated air, and this demanding more ways of ventilation.
A Escala de Respostas Socialmente Desejáveis-5: Validação numa Amostra Escolar de Jovens Portugueses

EnglishThe main aim of the present study was to validate the Socially Desirable Response Set -5 (SDRS-5) among a school sample (N=543) of male and female Portuguese youths. The SDRS-5 demonstrated good results, namely in terms of its one-factor structure, internal consistency, convergent validity, discriminant validity, criterion-related validity and known-groups validity. Cross-gender measurement invariance was demonstrated. The psychometric properties that were found mostly justify the use of the SDRS-5 among Portuguese adolescents from a school context. portuguesO objetivo do presente estudo consistiu na validacao da Escala de Respostas Socialmente Desejaveis - 5 (SDRS-5) numa amostra escolar (N=543) de jovens portugueses de ambos os sexos. A SDRS-5 apresenta resultados adequados do ponto de vista psicometrico, nomeadamente em termos da sua estrutura fatorial unidimensional, consistencia interna, validade convergente, validade discriminante, validade criterio e validade de grupos-conhecidos. Foi evidenciada invariância de medida entre rapazes e raparigas. As propriedades psicometricas identificadas justificam a utilizacao da SDRS-5 com jovens portugueses em contexto escolar
Community First Choice Implementation in Maryland, 2014-2016

In CY 2016, the majority of CFC participants were African American, female, over the age of 65, dually eligible, and used the personal assistance service more than any other service. While multi-year data points are shown, it is important to keep in mind that Maryland phased in different populations of individuals gradually; thus, any changes should not be interpreted as a trend. Personal Assistance Background and Objective
Change Detection using Spatio-Temporal Features and Feedback Loops

- Change detection is one of the most commonly used tasks in video processing. Background subtraction based change detection is the first step in many video applications to detect the foreground objects. Most of the background subtraction methods such as Local Binary patterns (LBP) and Local Ternary Patterns (LTP) are implemented using pixel by pixel representation. These can be viewed as improvements in many cases but they suffer in complexity, processing speed and illumination variations. In this paper, Local Binary Similarity Patterns (LBSP) makes pixel level decisions with automatic adjustment of tuning parameters for locally adapting to the changing input. It assigns the binary codes based on the similarity. For dynamic texture analysis, each pixel is modelled as a group of Spatiotemporal LBP (STLBP) histograms which combine spatial texture and temporal motion information together. The feedback loops are used to adjust the internal parameters and these adjustments are based on the continuous monitoring of model fidelity and segmentation noise which is observed under the form of blinking pixels. Adaptive background subtraction methods address all types of real time challenges including