Set Of Codes Research Articles

Studio Culture as Competency

The teaching of design, the act of design itself, and its competencies are always conceived as a mystery – knowable to a certain extent yet unknowable in its totality. In studies of how design knowledge is transferred in the studio, the focus typically centers around a determinate and quantifiable pedagogical exchange between student and tutor, consistent with its etymological roots in paidagōgia, suggestive of instruction akin to the teaching of a child. Yet, we witness other kinds of exchanges and social formations in the studio that expand beyond the student-tutor exchange, more akin to the cultural transmission of a distinct set of codes, behaviors, norms, and organizations autonomous from pedagogical structures. In this paper, we shift the conversation from one solely centered around pedagogy to an orbit of the architecture studio’s culture, whose social making, we argue, produces the public body of the architecture community and is itself the competency acquired in the architecture studio.

Direct Construction of Optimal Z-Complementary Code Sets With Even Lengths by Using Generalized Boolean Functions

Z-complementary code set (ZCCS) are well known to be used in multicarrier code-division multiple access (MCCDMA) system to provide a interference free environment. Based on the existing literature, the direct construction of optimal ZCCSs are limited to its length. In this paper, we are interested in constructing optimal ZCCSs of all possible even lengths using Pseudo-Boolean functions. The maximum column sequence peakto-man envelop power ratio (PMEPR) of the proposed ZCCSs is upper-bounded by two, which may give an extra benefit in managing PMEPR in an ZCCS based MC-CDMA system, as well as the ability to handle a large number of users.

New Construction of Multiple Complete Complementary Codes With Inter-Set Zero Cross-Correlation Zone

Controlling the peak-to-mean envelope power ratio (PMEPR) of multi-carrier code division multiple access (MC-CDMA) transmissions is a notoriously important problem. In this letter, a direct construction of multiple complete complementary codes (CCCs) with inter-set zero cross-correlation zone (ZCCZ) is proposed based on multivariable functions. The presented construction has an advantage over the previous works with regard to the new flexible parameters and low column sequence PMEPR, which may give an extra benefit in fulfilling different requirements and managing PMEPR in MC-CDMA systems with multiple cells. In addition, it turns out that the combination of the constructed CCCs results in a new optimal Z-complementary code set (ZCCS).

Asymptotically Guaranteed Anti-Jamming Spread Spectrum Random Access Without Pre-Shared Secret

Our main contribution is the design of a spread spectrum random access scheme without pre-shared secret with asymptotically guaranteed availability against electronic/cyber-based jamming attacks. In order to establish asymptotic anti-jamming guarantees, first we develop the system model and show that for reactive jamming (only limited by the laws of physical propagation), the required location for a successful attack can be controlled by design. Then, for non-reactive protocol-aware jamming, we map a random selection of (publicly known) spreading codes to the computational birthday problem. Differently to the related literature, we formulate the birthday problem using entropic measures (Rényi entropy), which allows to obtain the optimal spreading code set sizes that guarantee asymptotically zero collision probability. Accordingly, the birthday attack is the best strategy to optimize the (trial and error) blind acquisition at the legitimate detector. We obtain numerical results that illustrate how to use our entropic method as a system design degree of freedom to identify realistic spreading code set sizes. We also derive an upper bound of the detection latency. Finally, we show that the resulting anti-jamming throughput is higher than the throughput under conventional operation (i.e. without anti-jamming guarantees) due to the control of collision probability by-design.

Cross-Project Software Defect Prediction Based on Class Code Similarity

Software defect prediction techniques can help software developers find software defects as soon as possible. It can also reduce the cost of software development. This technique usually predicts the target project through the entire source project. However, the data distribution difference between the entire source project and the target project is generally large, so the software defect prediction accuracy is not high. we propose a cross-project software defect prediction technique based on class code similarity CCS-CPDP. Firstly, this technique converts the code set extracted by AST(Abstract Syntax Tree) into a vector set through the DTI (Doc2Bow and TF-IDF) strategy; Secondly, the similarity will be calculated between the vector set of target items and training items; Finally, according to the principle of the majority decision subordinate category in KNN, the number of most similar class instances of the training item is determined, and the source item is refined by selecting the class instance, thereby we can realize software defect prediction. This method compares with four traditional classification models (KNN, Random Forest, Naive Bayes, and Logistic Regression) for defect prediction. Experimental results show that CCS-CPDP compared with the baseline, recall and f1 increased by 18.03% and 14.1% respectively. In addition, the refined source projects selected by CCS-CPDP compared with the current source project selection technology, recall and f1 had improved by 37.6% and 12.7%.

New Class of Optimal Z-Complementary Code Sets

Z-complementary code sets (ZCCSs) can support interference-free multi-carrier code-division multiple access (MC-CDMA) in quasi-synchronous channels due to their favourable correlation properties. In this letter, based on the existing optimal ZCCSs and CCCs, we propose new class of optimal ZCCSs using Kronecker product. The resultant sequence sets have enlarged set size and sequence lengths which have not been reported before.

Transmission of Secret Information Based on Time Instances

This Paper presents improvement and extension of previous methodology about timing steganography based on network steganography. The previous article uses time interval between two successive time instances of transmissions mixed with cryptography prior to hiding. However, this improvement tends to extend and provide new methods based on single time instance unlike the previous methodology which depend on two-time instances such as hours, minutes, second, millisecond etc. It further examines how to handle effect of different time zone and high precision timing for ultrafast timing such as millisecond, and many more which human actions is too slow for perfect timing. In addition, the extension based on Transmission Control Protocol and Internet Protocol (TCP-IP) status codes where each element of set of status code are index and the index represents certain numeric of combination for hiding. Finally, the cryptography method is improved and extended to series-based cryptography with any defined number of different cryptography methods combined altogether with multiple keys generated dynamically. The methods for both cryptography and steganography were integrated and each module carefully tested for their feasibility and appropriate analysis, comparisons presented too. A brief discussion of possible extension or application of Time Interval and Instance Steganography from network based to Video and Audio time Steganography are presented which depends on time such as rate of change of features in Video, or in Audio as well. However, these video and audio Time steganography are considered as out of scope for this article which is mainly about network Steganography.

On the Construction of Chaotic Dynamical Systems on the Box Fractal

In this paper, our main aim is to obtain two different discrete chaotic dynamical systems on the Box fractal ($B$). For this goal, we first give two composition functions (which generate Box fractal and filled-square respectively via escape time algorithm) of expanding, folding and translation mappings. In order to examine the properties of these dynamical systems more easily, we use the intrinsic metric which is defined by the code representation of the points on $B$ and express these dynamical systems on the code sets of this fractal. We then obtain that they are chaotic in the sense of Devaney and give an algorithm to compute periodic points.

Elementary Schools' Response to Student Wellness Needs during the COVID-19 Shutdown: A Qualitative Exploration Using the R = MC2 Readiness Heuristic.

During spring of 2020, the COVID-19 pandemic and accompanying public health advisories forced K-12 schools throughout the United States to suspend in-person instruction. School personnel rapidly transitioned to remote provision of academic instruction and wellness services such as school meals and counseling services. The aim of this study was to investigate how schools responded to the transition to remote supports, including assessment of what readiness characteristics schools leveraged or developed to facilitate those transitions. Semi-structured interviews informed by school wellness implementation literature were conducted in the spring of 2020. Personnel (n = 50) from 39 urban and rural elementary schools nationwide participated. The readiness = motivation capacity2 (R = MC2) heuristic, developed by Scaccia and colleagues, guided coding to determine themes related to schools’ readiness to support student wellness in innovative ways during the pandemic closure. Two distinct code sets emerged, defined according to the R = MC2 heuristic (1) Innovations: roles that schools took on during the pandemic response, and (2) Readiness: factors influencing schools’ motivation and capacity to carry out those roles. Schools demonstrated unprecedented capacity and motivation to provide crucial wellness support to students and families early in the COVID-19 pandemic. These efforts can inform future resource allocation and new strategies to implement school wellness practices when schools resume normal operations.

Impact of Variability in Job Coding on Reliability in Exposure Estimates Obtained via a Job-Exposure Matrix.

The use of a job-exposure matrix (JEM) to assess exposure to potential health hazards in occupational epidemiological studies requires coding each participant's job history to a standard occupation and/or industry classification system recognized by the JEM. The objectives of this study were to assess the impact of inter-coder variability in job coding on reliability in exposure estimates derived from linking the job codes to the Canadian job-exposure matrix (CANJEM) and to identify influent parameters. Two trained coders independently coded 1000 jobs sampled from a population-based case-control study to the ISCO-1968 occupation classification at the five-digit resolution level, of which 859 could be linked to CANJEM using both assigned codes. Each of the two sets of codes was separately linked to CANJEM and thereby generated, for each of the 258 occupational agents available in CANJEM, two exposure estimates: exposure status (yes/no) and intensity of exposure (low, medium, and high) for exposed jobs only. Then, inter-rater reliability (IRR) was computed (i) after stratifying agents in 4 classes depending, for each, on the proportion of occupation codes in CANJEM defined as 'exposed' and (ii) for two additional scenarios restricted to jobs coded differently: the first one using experts' codes, the other one using codes randomly selected. IRR was computed using Cohen's kappa, PABAK and Gwet's AC1 index for exposure status, and weighted kappa and Gwet's AC2 for exposure intensity. Across all agents and based on all jobs, median (Q1, Q3; Nagents) values were 0.68 (0.59, 0.75; 220) for kappa, 0.99 (0.95, 1.00; 258) for PABAK, and 0.99 (0.97, 1.00; 258) for AC1. For the additional scenarios, median kappa was 0.28 (0.00, 0.45; 209) and -0.01 (-0.02, 00; 233) restricted to jobs coded differently using experts' and random codes, respectively. A similar decreasing pattern was observed for PABAK and AC1 albeit with higher absolute values. Median kappa remained stable across exposure prevalence classes but was more variable for low prevalent agents. PABAK and AC1 decreased with increasing prevalence. Considering exposure intensity and all exposed jobs, median values were 0.79 (0.68, 0.91; 96) for weighted kappa, and 0.95 (0.89, 0.99; 102) for AC2. For the additional scenarios, median kappa was, respectively, 0.28 (-0.04, 0.42) and -0.05 (-0.18, 0.09) restricted to jobs coded differently using experts' and random codes, with a similar though attenuated pattern for AC2. Despite reassuring overall reliability results, our study clearly demonstrated the loss of information associated with jobs coded differently. Especially, in cases of low exposure prevalence, efforts should be made to reliably code potentially exposed jobs.

Calligraphic Design in Fractal Model Based on Rectangle Collage Decomposition

A fractal model can deliver the beauty of self-similarity feature to be used in designing artistic things such as calligraphic characters. The fractal model can deliver the power of mathematics to be used in modeling the complex things that can be handled by computer programs. This paper delivers the short-cut way to design the artistic calligraphic characters based on the modification of the existing form of the simple rectangle fractal object to construct the stroke form of the calligraphic character as the simple solution of the inverse problem. The upright collage component design of rectangle fractal object can be decomposed into many cells of collage component of a calligraphic character with equal size in the right position of the cells according to the stroke of calligraphic character designed. The short-cut way to encode the fractal object is by copy-editing the representative IFS code based on the position of the cells according to the position of each component of the stroke. The calligraphic characters in fractal form as the collection of IFS code set are the representation of the affine coefficient functions, so they can be easily modified by means of the affine transformation function to any desired form.

RELIGIOUS EDUCATION AND ADOLESCENT RELIGIOSITY (Part 1: Urban and Rural Madrasah Aliyah Characteristics in Lombok Island)

The current social circumstances at the spiritual level have brought an enormous influence on the establishment of religious behavior in adolescent students, both in the level of belief, practice, and religious experience. Religious education in the madrasah environment has a strategic position in building students' religious behavior. This study aims to explain why the rural and urban madrasah environment context is essential to observe the role of religious education, especially Islamic education, in building students' religious behavior in Lombok island. Then it sorts out the madrasahs characteristics or uniqueness from the two different regions, rural and urban. This research is qualitative psychological research with ecological contextual theory as the theoretical framework. The data analysis method is descriptive and holistic by employing three flows of interacting activities, e.g., reducing data, presenting it, and drawing conclusions. Data was obtained through documentation, observation, and in-depth interviews. This research was conducted in six madrasahs, i.e., two Madrasah Aliyah located in the downtown, and four Madrasah Aliyah, which geographically represent the category of the rural madrasah. The research results indicate that the spiritual development of the students cannot be separated from the religious education context in their environment. In urban areas context, the madrasah environment has formal systemic characteristics, is supported by strong management and leadership, maintains the madrasah stability and conduciveness by implementing a power strategy through a set of rules and code of conduct. Meanwhile, madrasas in rural areas have flexible, dynamic, and adaptive characteristics, in which education takes into account cultural aspects and values applied in the community.

Ascertainment of Veterans With Metastatic Prostate Cancer in Electronic Health Records: Demonstrating the Case for Natural Language Processing.

Prostate cancer (PCa) is among the leading causes of cancer deaths. While localized PCa has a 5-year survival rate approaching 100%, this rate drops to 31% for metastatic prostate cancer (mPCa). Thus, timely identification of mPCa is a crucial step toward measuring and improving access to innovations that reduce PCa mortality. Yet, methods to identify patients diagnosed with mPCa remain elusive. Cancer registries provide detailed data at diagnosis but are not updated throughout treatment. This study reports on the development and validation of a natural language processing (NLP) algorithm deployed on oncology, urology, and radiology clinical notes to identify patients with a diagnosis or history of mPCa in the Department of Veterans Affairs. Using a broad set of diagnosis and histology codes, the Veterans Affairs Corporate Data Warehouse was queried to identify all Veterans with PCa. An NLP algorithm was developed to identify patients with any history or progression of mPCa. The NLP algorithm was prototyped and developed iteratively using patient notes, grouped into development, training, and validation subsets. A total of 1,144,610 Veterans were diagnosed with PCa between January 2000 and October 2020, among which 76,082 (6.6%) were identified by NLP as having mPCa at some point during their care. The NLP system performed with a specificity of 0.979 and sensitivity of 0.919. Clinical documentation of mPCa is highly reliable. NLP can be leveraged to improve PCa data. When compared to other methods, NLP identified a significantly greater number of patients. NLP can be used to augment cancer registry data, facilitate research inquiries, and identify patients who may benefit from innovations in mPCa treatment.

Successful Problem Solving in Genetics Varies Based on Question Content.

Problem solving is a critical skill in many disciplines but is often a challenge for students to learn. To examine the processes both students and experts undertake to solve constructed-response problems in genetics, we collected the written step-by-step procedures individuals used to solve problems in four different content areas. We developed a set of codes to describe each cognitive and metacognitive process and then used these codes to describe more than 1800 student and 149 expert answers. We found that students used some processes differently depending on the content of the question, but reasoning was consistently predictive of successful problem solving across all content areas. We also confirmed previous findings that the metacognitive processes of planning and checking were more common in expert answers than student answers. We provide suggestions for instructors on how to highlight key procedures based on each specific genetics content area that can help students learn the skill of problem solving.

Hospital utilization for hypoglycemia among patients with type 2 diabetes using pooled data from six health systems

IntroductionHypoglycemia is the most common serious adverse effect of diabetes treatment and a major cause of medication-related hospitalization. This study aimed to identify trends and predictors of hospital utilization for...

Optimizing over the Closure of Rank Inequalities with a Small Right-Hand Side for the Maximum Stable Set Problem via Bilevel Programming

In the context of the maximum stable set problem, rank inequalities impose that the cardinality of any set of vertices contained in a stable set be, at most, as large as the stability number of the subgraph induced by such a set. Rank inequalities are very general, as they subsume many classical inequalities such as clique, hole, antihole, web, and antiweb inequalities. In spite of their generality, the exact separation of rank inequalities has never been addressed without the introduction of topological restrictions on the induced subgraph and the tightness of their closure has never been investigated systematically. In this work, we propose a methodology for optimizing over the closure of all rank inequalities with a right-hand side no larger than a small constant without imposing any restrictions on the topology of the induced subgraph. Our method relies on the exact separation of a relaxation of rank inequalities, which we call relaxed k-rank inequalities, whose closure is as tight. We investigate the corresponding separation problem, a bilevel programming problem asking for a subgraph of maximum weight with a bound on its stability number, whose study could be of independent interest. We first prove that the problem is [Formula: see text]-hard and provide some insights on its polyhedral structure. We then propose two exact methods for its solution: a branch-and-cut algorithm (which relies on a family of faced-defining inequalities which we introduce in this paper) and a purely combinatorial branch-and-bound algorithm. Our computational results show that the closure of rank inequalities with a right-hand side no larger than a small constant can yield a bound that is stronger, in some cases, than Lovász’s Theta function, and substantially stronger than bounds obtained with standard inequalities that are valid for the stable set problem, including odd-cycle inequalities and wheel inequalities. Summary of Contribution: This paper proposes two original methods for solving a challenging cut-separation problem (of bilevel type) for a large class of inequalities valid for one of the key operations research problems, namely, the max stable set problem. An extensive set of experimental results validates the proposed methods. All the source code and data sets are available online on GitHub.

Design and Experiment of a Prototype Electronic Control Unit Direct Injection Fuel System Arduino-Based for 2-stroke Spark Ignition Engine

The development of technology on the 2-stroke direct-injection spark-ignition engine is expected to be a solution to optimize engine performance and reduce exhaust pollution. The fuel injection system in the operation of the spark-ignition engine is controlled by the Electronic Control Unit (ECU), so this study aims to design and experiment with a prototype of an Arduino-based direct injection fuel injection electronic control unit for 2-stroke spark-ignition engines. This research method begins with the design of an electronic control unit prototype that is selected for easy setup and low cost. Then, experiments were conducted on variations in injection timing and injection duration, which are the two main parameters of the fuel system to determine their effect on engine performance. This data is then used as a basis for setting the amount of fuel injected. The results show that there is an optimal performance under certain conditions from setting the injection timing and injection duration which is easily applied to the open-source code setting of this electronic control unit.

Socially Disadvantaged Youth: Forms of Expression and Communication in Social Networks as a Vehicle of Inclusion

Socially disadvantaged youth are a group to which prejudices are attached which question the appropriateness of their participation, communication and language in the digital setting. From this perspective, the aim of the present research proposes to identify the forms and expressions of communication used by socially disadvantaged young people from the city of Madrid in social networks. This will be examined as a tool for the development of interpersonal and social relatedness processes, which will enable inclusion and socialisation in contemporary society. To this end, a qualitative approach was proposed which enabled a set of core memos, codes, networks and categories to be established, through which study data were interpreted. WhatsApp images and interviews conducted with 78 informants were analysed using Atlas.ti 9 software. All participants belonged to a social group characterised by circumstances of social vulnerability. Of the main findings, it should be indicated that these young people exhibit a social network use that is not limited to engagement in digital leisure but, instead, is based on the exchange of communication. For this reason, these individuals have developed their own language, a fact that highlights specific traits of the digital culture to which they belong and contributes to disproving the idea that these young people use the digital setting inappropriately.

PseUdeep: RNA Pseudouridine Site Identification with Deep Learning Algorithm.

Background: Pseudouridine (Ψ) is a common ribonucleotide modification that plays a significant role in many biological processes. The identification of Ψ modification sites is of great significance for disease mechanism and biological processes research in which machine learning algorithms are desirable as the lab exploratory techniques are expensive and time-consuming. Results: In this work, we propose a deep learning framework, called PseUdeep, to identify Ψ sites of three species: H. sapiens, S. cerevisiae, and M. musculus. In this method, three encoding methods are used to extract the features of RNA sequences, that is, one-hot encoding, K-tuple nucleotide frequency pattern, and position-specific nucleotide composition. The three feature matrices are convoluted twice and fed into the capsule neural network and bidirectional gated recurrent unit network with a self-attention mechanism for classification. Conclusion: Compared with other state-of-the-art methods, our model gets the highest accuracy of the prediction on the independent testing data set S-200; the accuracy improves 12.38%, and on the independent testing data set H-200, the accuracy improves 0.68%. Moreover, the dimensions of the features we derive from the RNA sequences are only 109,109, and 119 in H. sapiens, M. musculus, and S. cerevisiae, which is much smaller than those used in the traditional algorithms. On evaluation via tenfold cross-validation and two independent testing data sets, PseUdeep outperforms the best traditional machine learning model available. PseUdeep source code and data sets are available at https://github.com/dan111262/PseUdeep.

A Novel miRNA Screen Identifies miRNA-4454 as a Candidate Biomarker for Ventricular Fibrosis in Patients with Hypertrophic Cardiomyopathy.

(1) Background: Left ventricular hypertrophy, myocardial disarray and interstitial fibrosis are the hallmarks of hypertrophic cardiomyopathy (HCM). Access to the myocardium for diagnostic purposes is limited. Circulating biomolecules reflecting the myocardial disease processes could improve the early detection of HCM. Circulating miRNAs have been found to reflect disease processes in several cardiovascular diseases. (2) Methods: We quantified circulating miRNA molecules in the plasma of 24 HCM and 11 healthy controls using the Human v3 miRNA Expression Assay Kit Code set (Nanostring Tech., Seattle, WA, USA) and validated differentially expressed miRNAs using RT-PCR. (3) Results: In comparison to healthy controls, the levels of six miRNAs (miR-1, miR-3144, miR-4454, miR-495-3p, miR-499a-5p and miR-627-3p) were higher in the plasma of HCM patients than healthy individuals (p < 0.05). Of these, higher levels of miR-1, miR-495 and miR-4454 could be validated by real-time PCR. In addition, elevated miR-4454 levels were significantly correlated with cardiac fibrosis, detected by magnetic resonance imaging in HCM patients. (4) Conclusions: Circulating miR-1, miR-495-3p and miR-4454 levels are elevated in the plasma of HCM patients. To the best of our knowledge, this is the first report showing a correlation between miR-4454 levels and cardiac fibrosis in HCM. This suggests miR-4454 as a potential biomarker for fibrosis in these patients.