Gypsum-DL: an open-source program for preparing small-molecule libraries for structure-based virtual screening

Computational techniques such as structure-based virtual screening require carefully prepared 3D models of potential small-molecule ligands. Though powerful, existing commercial programs for virtual-library preparation have restrictive and/or expensive licenses. Freely available alternatives, though often effective, do not fully account for all possible ionization, tautomeric, and ring-conformational variants. We here present Gypsum-DL, a free, robust open-source program that addresses these challenges. As input, Gypsum-DL accepts virtual compound libraries in SMILES or flat SDF formats. For each molecule in the virtual library, it enumerates appropriate ionization, tautomeric, chiral, cis/trans isomeric, and ring-conformational forms. As output, Gypsum-DL produces an SDF file containing each molecular form, with 3D coordinates assigned. To demonstrate its utility, we processed 1558 molecules taken from the NCI Diversity Set VI and 56,608 molecules taken from a Distributed Drug Discovery (D3) combinatorial virtual library. We also used 4463 high-quality protein-ligand complexes from the PDBBind database to show that Gypsum-DL processing can improve virtual-screening pose prediction. Gypsum-DL is available free of charge under the terms of the Apache License, Version 2.0

Bildebehandling og Autonomi

Abstrakt. Denne bachelor oppgaven omhandler utvikling og implementering av programvare for en undervanns robot (ROV), som tar i bruk blide behandling og data syn for å utføre autonome oppgaver. Dette gjøres som en en del av et tverrfaglig prosjekt i student organisasjonen UiS Subsea. ROV-en er bygd med mål om å delta i MATE ROV World Championship, som holdes i Colorado, USA, den 20-24. juni 2023. Denne bachelor oppgaven beskriver hvordan kamera-strømmer mottas på topside systemet, fra ROV-en, hvordan bilde behandling blir brukt til å løse autonome oppgaver, hvordan programmet implementeres i et brukergrensesnitt (GUI) og hvordan kjøre kommandoer sendes ned til ROV-en. Et modulært system har blitt laget, som mottar flere kamera strømmer, utfører autonome oppgaver og sender styre kommandoer. Programmet er blitt implementert inn i en GUI og testet på land. Tydelige definerte bildebehandlings oppgaver er gitt ut av MATE. Alle oppgavene er løst, utenom 3D modellering. Programmet er testet på land og oppfører seg som ønsket. Derimot, er ikke programmene testet i vann. Grunnen til dette er at ROV-en ikke var ferdigstilt i tide for vår gruppe å teste programmene våre. Testing og forbedring av programmet vill fortsette i forberedelser til MATE. Grunnet leveringsfristen for bachelor oppgaven, blir ikke dette inkludert i denne rapporten. Se vår GitHub repository for koden: https://github.com/UiS-Subsea/Bachelor_Bildebehandling Se GUI gruppens GitHub repository for implementeringen av vår kode inn i deres kode: https://github.com/UiS-Subsea/Bachelor_GUIAbstract. This bachelor’s thesis is about creating and implementing a software program on an underwater robot (ROV), that utilizes image processing and computer vision to perform autonomous tasks. This is done as part of an interdisciplinary project in the student organization UiS Subsea. The ROV is built with the purpose of competing in the MATE ROV World Championship, which is held in Colorado, USA, on the 20-24th of June 2023. This thesis describes how camera feeds are received on the topside system, from the ROV, how image processing is utilized to solve autonomous tasks, the implementation of the program into a graphical user interface (GUI), and the sending of driving commands down to the ROV. Additionally, an attempt was made to use computer vision to create a 3D model of a coral head. A modular program has been made, receiving multiple camera feeds, performing autonomous tasks, and sending driving commands. This program was implemented into a GUI, and tested on land. Clearly defined image-processing tasks were given by MATE. All of them were solved except for 3D modeling. The program was tested on land and behaved as intended. However, the programs were not tested in water. This was due to the ROV not being finished in time for our group to test our programs. Testing and improving the program will continue in preparation for MATE. Due to the submission date for the bachelor’s thesis, this will not be included in this paper. See our GitHub repository for the code: https://github.com/UiS-Subsea/Bachelor_Bildebehandling See the GUI group’s repository for our code implemented into their code: https://github.com/UiS-Subsea/Bachelor_GU

Parallel Processing with Digital Signal Processing Hardware and Software

The assembling and testing of a parallel processing system is described which will allow a user to move a Digital Signal Processing (DSP) application from the design stage to the execution/analysis stage through the use of several software tools and hardware devices. The system will be used to demonstrate the feasibility of the Algorithm To Architecture Mapping Model (ATAMM) dataflow paradigm for static multiprocessor solutions of DSP applications. The individual components comprising the system are described followed by the installation procedure, research topics, and initial program development

Bildebehandling og Autonomi

Abstrakt. Denne bachelor oppgaven omhandler utvikling og implementering av programvare for en undervanns robot (ROV), som tar i bruk blide behandling og data syn for å utføre autonome oppgaver. Dette gjøres som en en del av et tverrfaglig prosjekt i student organisasjonen UiS Subsea. ROV-en er bygd med mål om å delta i MATE ROV World Championship, som holdes i Colorado, USA, den 20-24. juni 2023. Denne bachelor oppgaven beskriver hvordan kamera-strømmer mottas på topside systemet, fra ROV-en, hvordan bilde behandling blir brukt til å løse autonome oppgaver, hvordan programmet implementeres i et brukergrensesnitt (GUI) og hvordan kjøre kommandoer sendes ned til ROV-en. Et modulært system har blitt laget, som mottar flere kamera strømmer, utfører autonome oppgaver og sender styre kommandoer. Programmet er blitt implementert inn i en GUI og testet på land. Tydelige definerte bildebehandlings oppgaver er gitt ut av MATE. Alle oppgavene er løst, utenom 3D modellering. Programmet er testet på land og oppfører seg som ønsket. Derimot, er ikke programmene testet i vann. Grunnen til dette er at ROV-en ikke var ferdigstilt i tide for vår gruppe å teste programmene våre. Testing og forbedring av programmet vill fortsette i forberedelser til MATE. Grunnet leveringsfristen for bachelor oppgaven, blir ikke dette inkludert i denne rapporten. Se vår GitHub repository for koden: https://github.com/UiS-Subsea/Bachelor_Bildebehandling Se GUI gruppens GitHub repository for implementeringen av vår kode inn i deres kode: https://github.com/UiS-Subsea/Bachelor_GUIAbstract. This bachelor’s thesis is about creating and implementing a software program on an underwater robot (ROV), that utilizes image-processing and computer vision to perform autonomous tasks. This is done as part of an interdisciplinary project in the student organization UiS Subsea. The ROV is built with the purpose of competing in the MATE ROV World Championship, which is held in Colorado, USA, on the 20-24th of June 2023. This thesis describes how camera feeds are received on the topside system, from the ROV, how image processing is utilized to solve autonomous tasks, the implementation of the program into a graphical user interface (GUI), and the sending of driving commands down to the ROV. Additionally, an attempt was made to use computer vision to create a 3D model of a coral head. A modular program has been made, receiving multiple camera feeds, performing autonomous tasks, and sending driving commands. This program was implemented into a GUI, and tested on land. Clearly defined image-processing tasks were given by MATE. All of them were solved except for 3D modeling. The program was tested on land and behaved as intended. However, the programs were not tested in water. This was due to the ROV not being finished in time for our group to test our programs. Testing and improving the program will continue in preparation for MATE. Due to the submission date for the bachelor’s thesis, this will not be included in this paper. See our GitHub repository for the code: https://github.com/UiS-Subsea/Bachelor_Bildebehandling See the GUI group’s repository for our code implemented into their code: https://github.com/UiS-Subsea/Bachelor_GU

Bildebehandling og Autonomi

Abstrakt. Denne bachelor oppgaven omhandler utvikling og implementering av programvare for en undervanns robot (ROV), som tar i bruk blide behandling og data syn for å utføre autonome oppgaver. Dette gjøres som en en del av et tverrfaglig prosjekt i student organisasjonen UiS Subsea. ROV-en er bygd med mål om å delta i MATE ROV World Championship, som holdes i Colorado, USA, den 20-24. juni 2023. Denne bachelor oppgaven beskriver hvordan kamera-strømmer mottas på topside systemet, fra ROV-en, hvordan bilde behandling blir brukt til å løse autonome oppgaver, hvordan programmet implementeres i et brukergrensesnitt (GUI) og hvordan kjøre kommandoer sendes ned til ROV-en. Et modulært system har blitt laget, som mottar flere kamera strømmer, utfører autonome oppgaver og sender styre kommandoer. Programmet er blitt implementert inn i en GUI og testet på land. Tydelige definerte bildebehandlings oppgaver er gitt ut av MATE. Alle oppgavene er løst, utenom 3D modellering. Programmet er testet på land og oppfører seg som ønsket. Derimot, er ikke programmene testet i vann. Grunnen til dette er at ROV-en ikke var ferdigstilt i tide for vår gruppe å teste programmene våre. Testing og forbedring av programmet vill fortsette i forberedelser til MATE. Grunnet leveringsfristen for bachelor oppgaven, blir ikke dette inkludert i denne rapporten. Se vår GitHub repository for koden: https://github.com/UiS-Subsea/Bachelor_Bildebehandling Se GUI gruppens GitHub repository for implementeringen av vår kode inn i deres kode: https://github.com/UiS-Subsea/Bachelor_GUIAbstract. This bachelor’s thesis is about creating and implementing a software program on an underwater robot (ROV), that utilizes image processing and computer vision to perform autonomous tasks. This is done as part of an interdisciplinary project in the student organization UiS Subsea. The ROV is built with the purpose of competing in the MATE ROV World Championship, which is held in Colorado, USA, on the 20-24th of June 2023. This thesis describes how camera feeds are received on the topside system, from the ROV, how image processing is utilized to solve autonomous tasks, the implementation of the program into a graphical user interface (GUI), and the sending of driving commands down to the ROV. Additionally, an attempt was made to use computer vision to create a 3D model of a coral head. A modular program has been made, receiving multiple camera feeds, performing autonomous tasks, and sending driving commands. This program was implemented into a GUI, and tested on land. Clearly defined image-processing tasks were given by MATE. All of them were solved except for 3D modeling. The program was tested on land and behaved as intended. However, the programs were not tested in water. This was due to the ROV not being finished in time for our group to test our programs. Testing and improving the program will continue in preparation for MATE. Due to the submission date for the bachelor’s thesis, this will not be included in this paper. See our GitHub repository for the code: https://github.com/UiS-Subsea/Bachelor_Bildebehandling See the GUI group’s repository for our code implemented into their code: https://github.com/UiS-Subsea/Bachelor_GU

A Classification and Survey of Computer System Performance Evaluation Techniques

Classification and survey of computer system performance evaluation technique

Preventive measures of struck-by accidents at the construction site: Perspectives from construction personnel in Johor

Struck-by accidents are among the main contributor to fatality number in the Malaysian construction industry. From the standpoint of construction safety professionals, this study explores the main preventive measures for struck-by accidents at the construction site. The data for this study was gathered through the questionnaire distributed to construction site safety workers in Johor, Malaysia, and about 116 answered questionnaires were received. Data were analyzed using the Relative Importance Index (RII) and Spearman’s rank correlation. The main preventive measure factor identified was related to training. This study provides eye-opening findings in terms of the weak correlational relation between the views of safety personnel and the most effective preventive strategy. This research raises awareness of the problem, and more action should be made to lower the fatality rate in struck-by-object accidents