Final Remarks for the Research With Advanced Machine Learning Methods in Colon Cancer Analysis

2021 ◽  
pp. 151-154
Keyword(s):  
Colon Cancer ◽  
Time Complexity ◽  
High Performance ◽  
Complexity Analysis ◽  
Search Algorithm ◽  
Cancer Treatments ◽  
Cancer Dataset ◽  
Performance Accuracy ◽  
Research Questions

Generally, classification accuracy is very important to gene processing and selection and cancer classification. It is needed to achieve better cancer treatments and improve medical drug assignments. However, the time complexity analysis will enhance the application's significance. To answer the research questions in Chapter 1, several case studies have been implemented (see Chapters 4 and 5), each was essential to sustain the methodologies discussed in Chapter 3. The study used a colon-cancer dataset comprising 2000 genes. The best search algorithm, GA, showed high performance with a good efficient time complexity. However, both DTs and SVMs showed the best classification contribution with reference to performance accuracy and time efficiency. However, it is difficult to apply a completely fair comparative study because existing algorithms and methods were tested by different authors to reflect the effectiveness and powerful of their own methods.

Research Approach With Machine Learning Underpinned

2021 ◽  
pp. 63-97
Keyword(s):  
Machine Learning ◽  
Colon Cancer ◽  
Feature Selection ◽  
High Performance ◽  
Classification Algorithms ◽  
Research Approach ◽  
Research Questions ◽  
Selection Algorithms ◽  
Gene Feature

This chapter describes several methodologies and proposed models used to examine the accuracy and efficiency of high-performance colon-cancer feature selection and classification algorithms to solve the problems identified in Chapter 2. An elaboration of the diverse methods of gene/feature selection algorithms and the related classification algorithms implemented throughout this study are presented. A prototypical methodology blueprint for each experiment is developed to answer the research questions in Chapter 1. Each system model is also presented, and the measures used to validate the performance of the model's outcome are discussed.

An Overview on Bioinformatics

2021 ◽  
pp. 7-62
Keyword(s):  
Colon Cancer ◽  
Feature Selection ◽  
Time Complexity ◽  
Gene Selection ◽  
Complexity Analysis ◽  
Research Area ◽  
Cancer Dataset ◽  
Algorithm Efficiency ◽  
Current Topic ◽  
Key Concepts

This chapter presents a thorough background and deep literature review of the current topic of study. It also presents and defines the key concepts utilised throughout this investigation. It consists of ten sections: (1) a background on bioinformatics, (2) a discussion of colon cancer, (3) an overview of the microarray technology that is used to extract the dataset, (4) an overview of the colon cancer dataset, (5) a review of the most prevalent algorithms employed for gene selection and cancer classification, (6) a presentation of related works from the literature, (7) identification of feature selection approaches and procedures, (8) an investigation of the ML concept, (9) a review of algorithm efficiency and time complexity analysis, and (10) identification of current problems in the research area.

Design and Procedures for the Investigation Conducted

2021 ◽  
pp. 98-116
Keyword(s):  
Colon Cancer ◽  
Time Complexity ◽  
High Performance ◽  
Gene Selection ◽  
Feature Selection Method ◽  
Selection Method ◽  
Cancer Classification ◽  
Experimental Setup ◽  
Detailed Design

In this chapter, the design of each proposed case study model mentioned in Chapter 3 is presented with their different experimental procedures. The chapter includes the data preparation, suitable parameters and data pre-processing, and detailed design of two case studies. Case 1: examining the accuracy and efficiency (time complexity) of high-performance gene selection and cancer classification algorithms; Case 2: A two-stage hybrid multi-filter feature selection method for high colon-cancer classification. It shows the experimental setup and environment and the description of the hardware and software components used.

Application of High Performance Electro-Hydraulic Synchronous Servo System on NC Broaching Machine

2013 ◽  
Vol 721 ◽  
pp. 497-500
Author(s):  
Guo Jin Chen ◽  
Jing Ni ◽  
Ting Ting Liu ◽  
Ming Xu
Keyword(s):  
High Performance ◽  
Control Process ◽  
Servo System ◽  
Numerical Control ◽  
Servo Drive ◽  
Loop Control ◽  
Performance Accuracy ◽  
Drive Control ◽  
Hydraulic Servo ◽  
Output Quantity

Aiming at the lower performance, accuracy and efficiency of the existing motion control process for the traditional broaching machine, the paper studies the high-performance dual-hydraulic synchronous servo drive control technology. The synchronous electro-hydraulic servo system forms the closed loop control by the detection and feedback of the output quantity. It eliminates and restrains largely the influence of the adverse factors to obtain the high-precision synchronous driving performance. The numerical control system based on the real-time error compensation and the intelligent control to the auxiliary machinery is developed. It is used for the CNC broaching machine to make the steady-state synchronous displacement error of the double cylinders be ≤ 0.5mm.

scholarly journals Binary Spring Search Algorithm for Solving Various Optimization Problems

2021 ◽  
Vol 11 (3) ◽  
pp. 1286 ◽  
Author(s):  
Mohammad Dehghani ◽  
Zeinab Montazeri ◽  
Ali Dehghani ◽  
Om P. Malik ◽  
Ruben Morales-Menendez ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
High Performance ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Bat Algorithm ◽  
Search Space ◽  
Binary Particle Swarm Optimization ◽  
Dragonfly Algorithm ◽  
Grasshopper Optimization Algorithm

One of the most powerful tools for solving optimization problems is optimization algorithms (inspired by nature) based on populations. These algorithms provide a solution to a problem by randomly searching in the search space. The design’s central idea is derived from various natural phenomena, the behavior and living conditions of living organisms, laws of physics, etc. A new population-based optimization algorithm called the Binary Spring Search Algorithm (BSSA) is introduced to solve optimization problems. BSSA is an algorithm based on a simulation of the famous Hooke’s law (physics) for the traditional weights and springs system. In this proposal, the population comprises weights that are connected by unique springs. The mathematical modeling of the proposed algorithm is presented to be used to achieve solutions to optimization problems. The results were thoroughly validated in different unimodal and multimodal functions; additionally, the BSSA was compared with high-performance algorithms: binary grasshopper optimization algorithm, binary dragonfly algorithm, binary bat algorithm, binary gravitational search algorithm, binary particle swarm optimization, and binary genetic algorithm. The results show the superiority of the BSSA. The results of the Friedman test corroborate that the BSSA is more competitive.

Energy Efficient VLSI Based DCT Architecture with Accurate Error Compensation

2014 ◽  
Vol 626 ◽  
pp. 127-135 ◽  
Author(s):  
D. Jessintha ◽  
M. Kannan ◽  
P.L. Srinivasan
Keyword(s):  
Low Power ◽  
Energy Efficient ◽  
Time Complexity ◽  
High Performance ◽  
Low Power Consumption ◽  
Distributed Arithmetic ◽  
Technology Scaling ◽  
Truncation Errors ◽  
History Of ◽  
Technology Dependency

Discrete Cosine Transform (DCT) is commonly used in image compression. In the history of DCT, a milestone was the Distributed Arithmetic (DA) technique. Due to the technology dependency a multiplier-less computation was built with DA based technique. It occupied less area but the throughput is less. Later, due to the technology scaling, multiplier based architectures can be easily adapted for low-power and high-performance architecture. Fixed width multipliers [1]-[7] reduces hardware and time complexity. In this work, Radix 4 fixed width multiplier is adapted with DCT architecture due to low power consumption and saves 30% power. In order to reduce truncation errors caused during fixed width multiplication, an estimation circuit is designed based on conditional probability theory.

scholarly journals The Impact of Organizational Culture and Performance Work System on Employees’ Performance

2018 ◽  
Vol 11 (6) ◽  
pp. 199 ◽  
Author(s):  
Amirreza Salehipour ◽  
Abdollah Ah mand
Keyword(s):  
Organizational Culture ◽  
High Performance ◽  
Ministry Of Education ◽  
Work System ◽  
Strong Relation ◽  
High Performance Work System ◽  
Research Questions ◽  
And Performance ◽  
The Impact ◽  
The Given

Necessity of improving employees’ performance in ministry of education in Iran was the reason of conducting this research. Authors are focused on the impact of High Performance Work System (HPWS) and the culture of organization on employees’ performance in Iran ministry of education. By conducting specified study based on distributed survey questionnaire to 162 members of ministry of education in Iran, this study aims to provide answer to the given research questions of study. The outcome of hypotheses testing illustrate HPWS significantly effects ministry members’ performance and shows strong relation between variables. Likewise, organizational culture demonstrates significant affirmative impact on Iran ministry of education members and employees’ performance. Findings of current research indicate that the ministry of education in Iran requires immediate action toward improving performance of members to obtain desired outcome. Accordingly, to the result of present study, current research attempts to provide practical concepts and illustrate limitations, suggestions for improvement of ministry and future study in this field.

scholarly journals Evaluation of the antitumor effects of PP242 in a colon cancer xenograft mouse model using comprehensive metabolomics and lipidomics

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Md Mamunur Rashid ◽  
Hyunbeom Lee ◽  
Byung Hwa Jung
Keyword(s):  
Colon Cancer ◽  
Mouse Model ◽  
High Performance ◽  
Tca Cycle ◽  
Treated Group ◽  
Metabolic Changes ◽  
Antitumor Effects ◽  
Xenograft Mouse Model ◽  
Metabolic Mechanism ◽  
Comprehensive Metabolomics

Abstract PP242, an inhibitor of mechanistic target of rapamycin (mTOR), displays potent anticancer effects against various cancer types. However, the underlying metabolic mechanism associated with the PP242 effects is not clearly understood. In this study, comprehensive metabolomics and lipidomics investigations were performed using ultra-high-performance chromatography-Orbitrap-mass spectrometry (UHPLC-Orbitrap-MS) in plasma and tumor tissue to reveal the metabolic mechanism of PP242 in an LS174T cell-induced colon cancer xenograft mouse model. After 3 weeks of PP242 treatment, a reduction in tumor size and weight was observed without any critical toxicities. According to results, metabolic changes due to the effects of PP242 were not significant in plasma. In contrast, metabolic changes in tumor tissues were very significant in the PP242-treated group compared to the xenograft control (XC) group, and revealed that energy and lipid metabolism were mainly altered by PP242 treatment like other cancer inhibitors. Additionally, in this study, it was discovered that not only TCA cycle but also fatty acid β-oxidation (β-FAO) for energy metabolism was inhibited and clear reduction in glycerophospholipid was observed. This study reveals new insights into the underlying anticancer mechanism of the dual mTOR inhibitor PP242, and could help further to facilitate the understanding of PP242 effects in the clinical application.

scholarly journals Complexity of Error-Correcting Code Based on Nearest Neighbor Search Algorithm

2019 ◽  
pp. 7-20
Author(s):  
Levon Arsalanyan ◽  
Hayk Danoyan
Keyword(s):  
Time Complexity ◽  
Nearest Neighbor ◽  
Search Algorithm ◽  
Error Correcting Code ◽  
Error Correcting Codes ◽  
Code Word ◽  
Nearest Neighbor Search ◽  
Perfect Codes ◽  
Neighbor Search ◽  
Weight Structures

The Nearest Neighbor search algorithm considered in this paper is well known (Elias algorithm). It uses error-correcting codes and constructs appropriate hash-coding schemas. These schemas preprocess the data in the form of lists. Each list is contained in some sphere, centered at a code-word. The algorithm is considered for the cases of perfect codes, so the spheres and, consequently, the lists do not intersect. As such codes exist for the limited set of parameters, the algorithm is considered for some other generalizations of perfect codes, and then the same data point may be contained in different lists. A formula of time complexity of the algorithm is obtained for these cases, using coset weight structures of the mentioned codes

scholarly journals Transgelin interacts with PARP1 and affects Rho signaling pathway in human colon cancer cells

2020 ◽  
Author(s):  
Zhen-xian Lew ◽  
Hui-min Zhou ◽  
Yuan-yuan Fang ◽  
Zhen Ye ◽  
Wa Zhong ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Colon Cancer ◽  
Transcription Factor ◽  
High Performance Liquid Chromatography ◽  
Cancer Cells ◽  
Signaling Pathway ◽  
High Performance ◽  
Colon Cancer Cells ◽  
Over Expression ◽  
Key Genes

Abstract Background: Transgelin, an actin-binding protein, is associated with the cytoskeleton remodeling. Our previous studies found that transgelin was up-regulated in node-positive colorectal cancer versus in node-negative disease. Over-expression of TAGLN affected the expression of 256 downstream transcripts and increased the metastatic potential of colon cancer cells in vitro and in vivo. This study aims to explore the mechanisms that transgelin participates in the metastasis of colon cancer cells.Methods: Immunofluorescence and immunoblotting analysis were used to determine the cellular localization of the endogenous and exogenous transgelin in colon cancer cells. Co-immunoprecipitation and subsequent high performance liquid chromatography/tandem mass spectrometry were performed to identify the proteins potentially interacting with transgelin. Bioinformatics methods were used to analyze the 256 downstream transcripts regulated by transgelin to discriminate the specific key genes and signaling pathways. By analyzing the promoter region of these key genes, GCBI tools were used to predict the potential transcription factor(s) for these genes. The predicted transcription factors were matching to the proteins that have been identified to potentially interact with transgelin. The interaction between transgelin and these transcription factors was verified by co-immunoprecipitation and immunoblotting.Results: Transgelin was found to localize both in the cytoplasm and the nucleus of colon cancer cells. 297 proteins have been identified to interact with transgelin by co-immunoprecipitation and subsequent high performance liquid chromatography/mass spectrometry. Over-expression of TAGLN could lead to differential expression of 184 downstream genes. By constructing the network of gene-encoded proteins, 7 genes (CALM1, MYO1F, NCKIPSD, PLK4, RAC1, WAS and WIPF1) have been discriminated as key genes using network topology analysis. They are mostly involved in the Rho signaling pathway. Poly ADP-ribose polymerase-1 (PARP1) was predicted as the unique transcription factor for the key genes and concurrently matching to the DNA-binding proteins potentially interacting with transgelin. Immunoprecipitation validated that PARP1 interacted with transgelin in human RKO colon cancer cells.Conclusions: The results of this study suggest that transgelin binds to PARP1 and regulates the expression of the downstream key genes mainly involving Rho signaling pathway, thus participates in the metastasis of colon cancer.

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