Mitigate Complexities in Algorithms using the Computation Virtual Instrument

395P - Filipinos and lung cancer: An infodemiological assessment using Google trends from 2009 to 2019

The aim of this paper is to compare the complexity of three simple sort algorithm; selection sort algorithm, bubble sort algorithm, and insertion sort algorithm. The measurement of the complexity is based on control flow structure and time processing. The control flow structure is illustrated into flowgraph and measured by number of out-degree and number of in-degree. The algorithm is coded in C programming language. The sorting experiment uses four data sets: 100,000 random words, 50,000 random words, 100,000 random integer numbers, and 50,000 random integer numbers to measure the time processing. The result of the measurement explains that the bubble sort algorithm has the complexity more than others.

Research on sorting algorithms is a very core research field in computer science. Today, any advancement in sorting algorithms would lead to less time and space required to perform the sorting task. This paper discusses a newly proposed algorithm—‘ledger-based sorting algorithm’. It is basically an advancement to ‘counting sort’, but not exactly counting sort. The purpose of this paper is to reduce the time and space required for sorting when the numbers given to you belong to a particular range (0–n) and all of them are distinct. This paper also compares the newly proposed algorithm with insertion sort, bubble sort, selection sort, quick sort, merge sort and mainly counting sort through graphical time analysis of these algorithms. The paper especially compares counting sort algorithm with the proposed algorithm in terms of both time and space complexity.

An alternative taxonomy (to that of Knuth and others) of sorting algorithms is proposed. It emerges naturally out of a top-down approach to the derivation of sorting algorithms. Work done in automatic program synthesis has produced interesting results about sorting algorithms that suggest this approach. In particular, all sorts are divided into two categories: hardsplit/easyjoin and easysplit/hardjoin. Quicksort and merge sort, respectively, are the canonical examples in these categories. Insertion sort and selection sort are seen to be instances of merge sort and quicksort, respectively, and sinking sort and bubble sort are in-place versions of insertion sort and selection sort. Such an organization introduces new insights into the connections and symmetries among sorting algorithms, and is based on a higher level, more abstract, and conceptually simple basis. It is proposed as an alternative way of understanding, describing, and teaching sorting algorithms.

Sorting is a classic problem that has been studied for decades. From the beginning of computing, many Sorting algorithms have been investigated. Bubble sort is a very common and powerful sorting technique used in different applications. For high speed data processing, we need faster and efficient environment for any sorting algorithm. In this purpose, FPGA based hardware accelerators can show better performance for high speed data processing than the general purpose processors. In this paper, the sequential and parallel bubble sort algorithm is implemented using FPGA. We show that parallel implementation of Bubble sort algorithm is almost 10 times faster than that of sequential implementation for 20 different data inputs. However, this implementation is faster for more data inputs.

<p>This study examined the effects of peer-led, inquiry-based, and lecture instructional strategies on students’ achievement and retention in basic science in Delta Central Senatorial District. 5 research questions and 5 hypotheses guide the study. The pretest-posttest delayed-posttest planned variation quasi-experimental design was employed for the study. The population of the study consisted of 82,712 JSII basic science students in the 183 public secondary schools. The sample size is 292 basic science students selected from 6 public mixed junior secondary schools. The instrument for data collection, which was duly face and content validated, was the Basic Science Achievement Test (BSAT). The instrument, with a reliability coefficient of 0.79, was established using the Kuder-Richardson Formula – 21 (K-R-21). All research questions were answered using mean and standard deviation, while the hypotheses were tested at a 0.05 level of significance with t-test, and ANCOVA. The study found that; there is a significant difference in the mean achievement scores among students taught basic science using peer-led, inquiry-based and lecture instructional strategies, there is a significant difference in the mean retention scores among students taught basic science using peer-led, inquiry-based and lecture instructional strategies, there is no significant difference in the mean achievement scores of male and female students taught basic science using peer-led, inquiry-based and lecture instructional strategies, there is no significant interaction effect of method and gender on basic science students’ achievement, and there is a significant interaction effect of method and gender on basic science students’ retention. the study, therefore, concluded that the peer-led instructional strategy and the inquiry-based instructional strategy are more effective in enhancing basic science students’ achievement and retention than the lecture method. The study also, amongst others, recommends that basic science teachers should adopt the use of peer-led instructional strategy in teaching basic science in junior and senior secondary schools.</p><p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu/0217/a.php" alt="Hit counter" /></p>

The importance of affective domain in acquisition of scientific knowledge cannot be overemphasized. Hence, the study investigated students' motivation and academic achievement in Basic Science. Quasi experimental research design was adopted for the study and purposive sampling technique was used to select Emohua Local Government Area. Stratified random sampling on basis of school location (urban and rural) was used to select two UBE schools. While simple random sampling by balloting was used to select one hundred (100) JSS2 Basic Science students that participated in the study. Basic Science Achievement Test (BSAT) was used to collect data for the study and the data collected were analyzed by using mean and standard deviation to answer all the research questions while Analysis of Covariance (ANCOVA) was used to test the hypotheses at.05 level of significance. The study found that, students' motivation have significant effect on their achievement mean scores in Basic Science P<.05. Gender does not have significant effect on achievement mean scores of motivated students in Basic Science, P >.05. School locations have significant effect on mean scores of motivated students in Basic science P <.05. The urban motivated students did better than the rural students. Hence, this study recommends that students should often be motivated in order for them to achieve maximally in acquiring Basic Science skills and knowledge. Rural schools should also be well equipped to boast the achievement of students in Basic Science.

Online behavior leaves a digital footprint that can be analyzed to reveal our cognitive and psychological state through time. Recognizing these subtle cues can help identify different aspects of mental health, such as low self-esteem, depression, and anxiety. Google's web search engine, used daily by millions of people, logs every search query made by a user, which is accessible through a platform called Google Takeout. Previous researchers have made efforts to detect and predict behaviors associated with depression and anxiety from web data, but only at a population level. This paper fills in the gap of looking into signs of low self-esteem, a condition that work in a vicious cycle with depression and anxiety, at an individual level by looking into Google search history data. We target college students, a population prone to depression, anxiety, and low self-esteem, and ask to take mental health assessment survey along with their individual search history. Textual analysis show that search logs contain strong signals that can identify individuals with current low self-esteem. For example, participants with low self-esteem have fewer searches pertaining to family, friend, and money attributes; and we also observed differences in the search category distribution, over time, when compared with individuals with moderate to high self-esteem. Using these markers we were able to build a probabilistic classifier that can identify low self-esteem conditions, based on search history, with an average F1 score of 0.86.

In this paper we analyze the algorithms expressed as a system of recurrence equations. The algorithms are called 2*1 output algorithms if two output values of one function (variable identification) are specified by the system of recurrence equations for each index point in the algorithm. The algorithm is in free form if the indexes of these two values are not dependent. Two standard classes are determined by this criteria: the nearest neighbour and the all pair form. For example the sorting algorithm can be expressed in the all pair form i.e., the linear insertion algorithm or in the nearest neighbour form i.e., the bubble sort algorithm. However these algorithms are different in their nature. A procedure to eliminate the computational broadcast for the all pair 2*1output algorithm has been proposed by the authors in [1]. The result obtained by implementing this procedure was a localized form of the algorithm and a system of uniform recurrence equations by eliminating the computational and data broadcast. So he data dependence method can be efficiently used for parallel implementations. The proposed procedure cannot be implemented directly on the nearest neighbour form algorithms. Here we show how the algorithm can be restructured into a form where the computational and data broadcast can be eliminated. These transformations result in localized algorithms. A few examples show how these algorithms can be implemented on processor arrays. For example, the Gentleman Kung triangular array [2] can be used for solving the QR decomposition algorithm for both forms of the algorithm. The implementations differ in the order of the data flow and the processor operation. We show that the implementation of the nearest neighbour algorithm is even better than the standard one.

Texas Instruments development kits have a wide application in practical and scientific experiments due to their small size, processing power, available booster packs, and compatibility with different environments. The most popular integrated development environments for programming these development kits are Energia and Code Composer Studio. Unfortunately, there are no existing studies that compare the benefits and drawbacks of these environments and their performances. Conversely, the performances of the FreeRTOS environment are well-explored, making it a suitable baseline for embedded systems execution. In this paper, we performed the experimental evaluation of the performance of Texas Instruments MSP-EXP432P401R when using Energia, Code Composer Studio, and FreeRTOS for program execution. Three different sorting algorithms (bubble sort, radix sort, merge sort) and three different search algorithms (binary search, random search, linear search) were used for this purpose. The results show that Energia sorting algorithms outperform other environments with a maximum of 400 elements. On the other hand, FreeRTOS search algorithms far outperform other environments with a maximum of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{2 5 5, 0 0 0}$</tex> elements (whereas this maximum was <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{1 0, 0 0 0}$</tex> elements for other environments). Code Composer Studio resulted in the largest processing time, which indicates that the lowlevel registry editing performed in this environment leads to significant performance issues.

Background and Purpose: There is much evidence that the prevalence of academic misbehaviors is increasing in universities. This study examined the motivation and attitudes of medical students of Shahid Beheshti University of Medical Sciences on cheating and its frequency. Methods: The study is a survey of medical students’ of Shahid Beheshti University of Medical Sciences attitudes on cheating and Data was analyzed using Chi-square and McNemar's test. Results: One hundred and sixty medical students participated in this study. The mean and standard deviation of students’ age was 22.69±2.29 years. Basic Sciences and internship students’ attitudes on three cheating behaviors, including cheating from others (P=0.028), helping other students to copy answers during exams (P=0.001), and recording false reports deliberately to facilitate assignments were significantly different (P=0.0001). The students' highest motivation for cheating was fear of failing in the exam (79.3%) and difficulty of the course (77.5%). Conclusions: The results showed that there were a higher number of interns than basic sciences students considered two behaviors of helping others to cheat and copying from one’s hand as cheating. It seems that policy-making in universities must be in a way that the problems of educational program, attitude and environment get more attention. In this regard, medical ethics education, reduced stress and pressure associated with medical education, fair and decisive punishment for dishonest people and appropriate resource allocation should be carried out for exam’s environment control. Keywords: Motivation, Attitude, Medical Students, Cheating

The study investigated the better strategy to use in fostering achievement and retention in Basic Science considering simulation and demonstration strategies. The study also compared the achievement as well as the retention of female and male students in basic science when exposed to simulation strategy. The research region is Kogi State's Ankpa Education Zone. A multistage sampling strategy was used to choose 120 Basic II students from four schools in the research region. The study used a quasi-experimental design. Data were analyzed using means and standard deviations, while ANCOVA was utilized to test the hypotheses. The study's results indicated that students taught using the simulation technique achieved considerably better mean achievement and retention scores in Basic Science than students taught using the demonstration strategy. Additionally, no significant difference in mean achievement scores between male and female students taught utilizing the simulation teaching technique was discovered. The research demonstrates a substantial difference in the mean retention scores of male and female students in Basic Science who are taught utilizing a simulation technique. Following the findings, it was suggested that Science teachers should use simulation strategy for the teaching of various topics in Basic Science to improve students’ achievement in Basic Science.

Bubble sort algorithm and its variants are discussed in detail. Bubble sort algorithm is the slowest one in application; improved bubble sort algorithm is superior to it because of the introduction of flag variant and the forward movement of end index; improved bubble sort algorithm moves the end index more quickly; bidirectional bubble sort algorithm quickly moves the end index forwards and the start index backwards at the same time. In all these algorithms, bidirectional bubble sort algorithm is especially suitable to those sequence parts items of which are already in expected order. Bidirectional bubble sort algorithm is of great significance and has the highest efficiency.

Librarians should think explicitly about Google users whenever they publish on the Web, and should update their policies and procedures accordingly. The article describes procedures that libraries can adopt to ensure that their publications are optimised for access by users of Google and other Web search engines. The aim of these procedures is to enhance resource discovery and information retrieval, and to enhance the reputation of libraries as valued custodians of published information, as well as exemplars of good practice in information management.

This paper proposes a new strategy to achieve balanced capacitor voltages in modular multilevel converters. Among the possible solutions, centralized arm control approaches are often adopted. These methods require a balancing technique based on a sorted list of the sub-modules according to their capacitor voltages. In order to achieve the aforementioned sorted list, different algorithms have been proposed in literature, such as: Sorting algorithms, max/min approaches, etc. However, the sorting algorithms require a long execution time, while the max/min approaches affect the converter dynamic response during faults. To overcome these issues, a new mapping strategy providing a quasi-sorted list is proposed in this paper. The suggested method is compared in simulation with both the classical bubble sorting algorithm, and the max/min method during both normal and faulty conditions. Moreover, the three methods have been implemented in a Xilinx Zynq-7000 System-on-Chip (SoC) device, in order to analyze the corresponding execution time and the required computational effort. Hardware-in-the-loop results are presented for demonstrating the superior performance of the proposed balancing strategy.