HUBUNGAN SIKAP DAN PERAN TEMAN SEBAYA DENGAN PERILAKU SEKSUAL PADA REMAJA

Pada masa remaja, hormon-hormon yang mulai berfungsi selain menyebabkan perubahan fisik juga mempengaruhi dorongan seks pada remaja. Perilaku seksual pranikah merupakan segala tingkah laku yang didorong oleh hasrat seksual baik yang dilakukan sendiri, dengan lawan jenis maupun sesama jenis tanpa ada ikatan pernikahan. Tujuan penelitian ini adalah menganalisis hubungan sikap dan peran teman sebaya dengan perilaku seksual pada remaja. Penelitian ini dilakukan pada Bulan Juni 2020 dengan menggunakan desain penelitian analitik korelasi dengan pendekatan cross-sectional . Teknik sampling penelitian ini menggunakan stratified random sampling dengan menggunakan aplikasi random generator memasukkan nomor responden yang sudah bersedia mengisi di gogglefrom dengan jumlah sampel sebanyak 129 Orang. Hasil Penelitian ini menunjukan bahwa tidak ada hubungan yang signifikan antara sikap dengan perilaku seksual pada remaja dari hasil Chi-square p-value > 0,05 akan tetapi terdapat hubungan yang signifikan antara peran teman sebaya dengan perilaku seksual remaja Chi-square p-value < 0,05. Diharapkan dengan penelitian ini remaja akan lebih selektif dalam memilih teman sebaya sehingga tidak terjadi perilaku seksual yang menyimpang pada mereka.

Clustered sparsity and Poisson-gap sampling

Non-uniform sampling (NUS) is a popular way of reducing the amount of time taken by multidimensional NMR experiments. Among the various non-uniform sampling schemes that exist, the Poisson-gap (PG) schedules are particularly popular, especially when combined with compressed-sensing (CS) reconstruction of missing data points. However, the use of PG is based mainly on practical experience and has not, as yet, been explained in terms of CS theory. Moreover, an apparent contradiction exists between the reported effectiveness of PG and CS theory, which states that a “flat” pseudo-random generator is the best way to generate sampling schedules in order to reconstruct sparse spectra. In this paper we explain how, and in what situations, PG reveals its superior features in NMR spectroscopy. We support our theoretical considerations with simulations and analyses of experimental data from the Biological Magnetic Resonance Bank (BMRB). Our analyses reveal a previously unnoticed feature of many NMR spectra that explains the success of ”blue-noise” schedules, such as PG. We call this feature “clustered sparsity”. This refers to the fact that the peaks in NMR spectra are not just sparse but often form clusters in the indirect dimension, and PG is particularly suited to deal with such situations. Additionally, we discuss why denser sampling in the initial and final parts of the clustered signal may be useful.

A Pseudo-Random Generator Whose Output is a Normal Sequence

Pseudo-random number generators (PRNGs) are widely used in computer simulation, cryptography, and many other fields. In this paper, we describe a PRNG class, which, firstly, has been successfully tested using the most powerful modern test batteries, and secondly, is proved to consist of generators that generate normal sequences. The latter property means that, for any generated sequence [Formula: see text] and any binary word [Formula: see text], we have [Formula: see text] where [Formula: see text] is the number of occurrences of [Formula: see text] in the sequence [Formula: see text], [Formula: see text].

Quantum generators of random numbers

Generation of random numbers is a central problem for many applications in the field of information processing, including, e.g., cryptography, in classical and quantum regime, but also mathematical modeling, Monte Carlo methods, gambling and many others. Both, the quality of the randomness and efficiency of the random numbers generation process are crucial for the most of these applications. Software produced pseudorandom bit sequences, though sufficiently quick, do not fulfill required randomness quality demands. Hence, the physical hardware methods are intensively developed to generate truly random number sequences for information processing and electronic security application. In the present paper we discuss the idea of the quantum random number generators. We also present a variety of tests utilized to assess the quality of randomness of generated bit sequences. In the experimental part we apply such tests to assess and compare two quantum random number generators, PQ4000KSI (of company ComScire US) and JUR01 (constructed in Wroclaw University of Science and Technology upon the project of The National Center for Research and Development) as well as a pseudorandom generator from the Mathematica Wolfram package. Finally, we present our new prototype of fully operative miniaturized quantum random generator JUR02 producing a random bit sequence with velocity of 1 Mb/s, which successfully passed standard tests of randomness quality (like NIST and Dieharder tests). We also shortly discuss our former concept of an entanglement-based quantum random number generator protocol with unconditionally secure public randomness verification.

Modul Simulator Pembangkitan Sinyal Pseudo Random Generator pada Sistem Komunikasi Spread Spectrum Memanfaatkan Microcontroller

Sebuah modul simulator perangkat keras untuk sinyal pseudo random generator (PRG) telah dibuat dengan memanfaatkan microcontroller 8951. Dari data pengujian sistem pemancar dan bagian penerima telah menunjukkan bahwa simulator ini mampu menunjukkan 3 sifat dasar dari sebuah spreading dan despreading pada sistem direct sequence spread spectrum (DSSS), yaitu autokorelasi, balance property dan run property. Dengan input base band sebesar 4 kHz, sistem ini mampu memberikan coding gain sebesar 8, 2 dB.

Layer entanglement in multiplex, temporal multiplex, and coupled multilayer networks

Complex networks, such as transportation networks, social networks, or biological networks, capture the complex system they model by often representing only one type of interactions. In real world systems, there may be many different aspects that connect entities together. These can be captured using multilayer networks, which combine different modalities of interactions in a single model. Coupling in multilayer networks may exhibit different properties which can be related to the very nature of the data they model (or to events in time-dependent data). We hypothesise that such properties may be reflected in the way layers are intertwined. In this paper, we investigated these through the prism of layer entanglement in coupled multilayer networks. We test over 30 real-life networks in 6 different disciplines (social, genetic, transport, co-authorship, trade, and neuronal networks). We further propose a random generator, displaying comparable patterns of elementary layer entanglement and transition coupling entanglement across 1,329,696 synthetic coupled multilayer networks. Our experiments demonstrate difference of layer entanglement across disciplines, and even suggest a link between entanglement intensity and homophily. We additionally study entanglement in 3 real world temporal datasets displaying a potential rise in entanglement activity prior to other network activity.

Multilevel Monte Carlo by using the Halton sequence

Monte Carlo (MC) simulation depends on pseudo-random numbers. The generation of these numbers is examined in connection with the Brownian motion. We present the low discrepancy sequence known as Halton sequence that generates different stochastic samples in an equally distributed form. This will increase the convergence and accuracy using the generated different samples in the Multilevel Monte Carlo method (MLMC). We compare algorithms by using a pseudo-random generator and a random generator depending on a Halton sequence. The computational cost for different stochastic differential equations increases in a standard MC technique. It will be highly reduced using a Halton sequence, especially in multiplicative stochastic differential equations.

An Image Encryption Scheme Using Chaotic Baker Map

In this paper, we propose a new image encryption method based on Chaos Baker map and Lanczos algorithm. Two levels of security are achieved to enhance the level of image security. In the first level, the Chaotic Baker map is a randomization technique used to make the pixels more shuffled. A pseudo-random generator is used with the second-level Lanczos algorithm which is applied to generate eigenvalues and eigenvectors. The proposed method resists various attacks: plaintext attacks, maximum deviation, correlation analysis and key sensitivity. Experimental results show that this method has better time complexity when protecting images.