Aplikasi Algoritma Genetik Untuk Optimasi Penjadwalan Kuliah (Studi Kasus di Program Studi Teknik Industri Undip)

ABSTRAK Penjadwalan kuliah pada suatu universitas adalah suatu pekerjaan menempatkan kegiatan perkuliahan kedalam ruangan dan waktu yang ada sedemikian rupa agar dapat meminimasi pelanggaran terhadap sejumlah batasan-batasan tertentu. Batasan-batasan yang harus dipenuhi oleh sebuah jadwal kuliah dapat dibedakan menjadi dua kategori: hard constraints dan soft constraints. Sebuah jadwal kuliah adalah feasibel jika dan hanya jika semua hard constraints dapat dipenuhi. Tujuan dari optimasi penjadwalan kuliah adalah untuk mencari jadwal kuliah yang tidak memiliki pelanggaran terhadap hard constraints dan sebisa mungkin memimimasi pelanggaran terhadap soft constraints. Permasalahan ini sangatlah kompleks karena melibatkan banyak batasan-batasan yang harus dipertimbangkan. Hard constraints meliputi konflik dari sumber daya yang ada (dosen, mahasiswa, ruangan) dan juga kapasitas ruangan yang tersedia. Permasalahan akan menjadi semakin rumit jika terdapat soft constraints seperti waktu mengajar yang dipilih oleh para dosen. Otomasi penjadwalan kuliah merupakan hal yang sangat penting karena dapat menghemat jam kerja dan memberikan solusi optimum dalam waktu yang singkat, yang dapat meningkatkan produktivitas, kualitas proses belajar mengajar, dan kualitas pelayanan. Salah satu metode yang dapat digunakan untuk menyelesaikan permasalahan penjadwalan kuliah ini adalah pendekatan algoritma genetik. Algoritma genetik merupakan alat optimasi yang memodelkan prinsip evolusi. Algoritma genetik mampu menemukan solusi optimum secara global dalam ruang pencarian yang sangat kompleks. Dengan menggunakan sebuah populasi awal dari solusi yang dikodekan dan dipilih berdasarkan kualitasnya, lalu digunakan untuk membuat populasi baru dengan menggunakan proses kawin silang dan mutasi atas individu-individu awal. Fungsi evaluasi digunakan untuk menghitung hard constraints dan soft constraints yang dapat dipenuhi. Tugas akhir ini membahas penjadwalan kuliah yang terdapat pada Program Studi Teknik Industri Undip. Tujuan dari penelitian ini adalah untuk mengoptimasi penjadwalan kuliah dan memudahkan pekerjaan penjadwalan kuliah dengan membuat sebuah software penjadwalan kuliah. Software yang dibuat dirancang menggunakan algoritma genetik. Hasil pengujian yang dilakukan menunjukkan bahwa software algoritma genetik telah dapat menghasilkan nilai fitness maksimum yang berarti semua batasan-batasan yang ada berhasil dipenuhi. Dengan demikian, jadwal kuliah yang dihasilkan merupakan solusi yang optimum

Assessment on recent landslide susceptibility mapping methods: A review

Landslide is a destructive natural hazard that causes severe property loss and loss of lives. Numerous researchers have developed landslide susceptibility maps in order to forecast its occurrence, particularly in hill-site development. Various quantitative approaches are used in landslide susceptibility map production, which can be classified into three categories; statistical data mining, machine learning and deterministic approach. In this paper, we choose two regular models in each category, which are Weight of Evidence (WoE) and Frequency Ratio (FR), Artificial Neutral Networks (ANN) and Support Vector Machines (SVM), Shallow Landsliding Stability Model (SHALSTAB) and YonSei-Slope (YS-Slope). Discussion and assessment on these models are based on relevant literature

Bromocarbons in the tropical coastal and open ocean atmosphere during the Prime Expedition Scientific Cruise 2009 (PESC 09)

Atmospheric concentrations of very short-lived species (VSLS) bromocarbons, including CHBr3, CH2Br2, CHCl2Br, CHClBr2, and CH2BrCl, were measured in the Strait of Malacca and the South China and Sulu–Sulawesi seas during a two-month research cruise in June–July 2009. The highest bromocarbon concentrations were found in the Strait of Malacca, with smaller enhancements in coastal regions of northern Borneo. CHBr3 was the most abundant bromocarbon, ranging from 5.2 pmol mol−1 in the Strait of Malacca to 0.94 pmol mol−1 over the open ocean. Other bromocarbons showed lower concentrations, in the range of 0.8–1.3 pmol mol−1 for CH2Br2, 0.1–0.5 pmol mol−1 for CHCl2Br, and 0.1–0.4 pmol mol−1 for CHClBr2. There was no significant correlation between bromocarbons and in situ chlorophyll a, but positive correlations with both MODIS and SeaWiFS satellite chlorophyll a. Together, the shortlived bromocarbons contribute an average of 8.9 pmol mol−1 (range 5.2–21.4 pmol mol−1) to tropospheric bromine loading, which is similar to that found in previous studies from global sampling networks (Montzka et al., 2011). Statistical tests showed strong Spearman correlations between brominated compounds, suggesting a common source. Log–log plots of CHBr3/CH2Br2 versus CHBr2Cl/CH2Br2 show that both chemical reactions and dilution into the background atmosphere contribute to the composition of these halocarbons at each sampling point. We have used the correlation to make a crude estimate of the regional emissions of CHBr3 and to derive a value of 32 Gg yr−1 for the Southeast (SE) Asian region (10◦ N–20◦ S, 90–150◦ E). Finally, we note that satellite-derived chlorophyll a (chl a) products do not always agree well with in situ measurements, particularly in coastal regions of high turbidity, meaning that satellite chl a may not always be a good proxy for marine productivity

Treatment Guidance for Patients With Lung Cancer During the Coronavirus 2019 Pandemic

The global coronavirus disease 2019 pandemic continues to escalate at a rapid pace inundating medical facilities and creating substantial challenges globally. The risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in patients with cancer seems to be higher, especially as they are more likely to present with an immunocompromised condition, either from cancer itself or from the treatments they receive. A major consideration in the delivery of cancer care during the pandemic is to balance the risk of patient exposure and infection with the need to provide effective cancer treatment. Many aspects of the SARS-CoV-2 infection currently remain poorly characterized and even less is known about the course of infection in the context of a patient with cancer. As SARS-CoV-2 is highly contagious, the risk of infection directly affects the cancer patient being treated, other cancer patients in close proximity, and health care providers. Infection at any level for patients or providers can cause considerable disruption to even the most effective treatment plans. Lung cancer patients, especially those with reduced lung function and cardiopulmonary comorbidities are more likely to have increased risk and mortality from coronavirus disease 2019 as one of its common manifestations is as an acute respiratory illness. The purpose of this manuscript is to present a practical multidisciplinary and international overview to assist in treatment for lung cancer patients during this pandemic, with the caveat that evidence is lacking in many areas. It is expected that firmer recommendations can be developed as more evidence becomes available

The phylogenetic landscape and nosocomial spread of the multidrug-resistant opportunist Stenotrophomonas maltophilia

Recent studies portend a rising global spread and adaptation of human- or healthcare-associated pathogens. Here, we analyse an international collection of the emerging, multidrug-resistant, opportunistic pathogen Stenotrophomonas maltophilia from 22 countries to infer population structure and clonality at a global level. We show that the S. maltophilia complex is divided into 23 monophyletic lineages, most of which harbour strains of all degrees of human virulence. Lineage Sm6 comprises the highest rate of human-associated strains, linked to key virulence and resistance genes. Transmission analysis identifies potential outbreak events of genetically closely related strains isolated within days or weeks in the same hospitals

An Improved Protocol for N-Glycosylation Analysis of Gel-Separated Sialylated Glycoproteins by MALDI-TOF/TOF

Different glycoforms of some proteins have been identified as differential spots for certain diseases in 2-DE, indicating disease-related glycosylation changes. It is routine to determine the site-specific glycosylation of nonsialylated N-glycoproteins from a single gel spot, but some obstacles still exist in analyzing sialylated glycoproteins due to the lability and higher detection limit of acid glycans in MALDI-TOF/TOF analysis. Thus, we present an improved protocol here. Tryptic glycopeptides were separated and subjected to MALDI-TOF/TOF analysis, resulting in the identification of site-specific glycosylation of high-intensity glycopeptides. Sequential deglycosylation and desialylation were used to improve the identification of glycosylation sites and desialylated glycans. The site-specific glycosylation of large glycopeptides and low-intensity glycopeptides was deduced based on the masses of glycopeptides, deglycosylated peptides and desialylated glycans. By applying it to 2-DE separated human serum, the difference of N-glycosylation was successfully determined for α1-antitrypsin between different gel spots

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Internet of Things in Water Management and Treatment

The goal of the water security IoT chapter is to present a comprehensive and integrated IoT based approach to environmental quality and monitoring by generating new knowledge and innovative approaches that focus on sustainable resource management. Mainly, this chapter focuses on IoT applications in wastewater and stormwater, and the human and environmental consequences of water contaminants and their treatment. The IoT applications using sensors for sewer and stormwater monitoring across networked landscapes, water quality assessment, treatment, and sustainable management are introduced. The studies of rate limitations in biophysical and geochemical processes that support the ecosystem services related to water quality are presented. The applications of IoT solutions based on these discoveries are also discussed

Genomic analyses in Cornelia de Lange Syndrome and related diagnoses: Novel candidate genes, <scp>genotype–phenotype</scp> correlations and common mechanisms

Cornelia de Lange Syndrome (CdLS) is a rare, dominantly inherited multisystem developmental disorder characterized by highly variable manifestations of growth and developmental delays, upper limb involvement, hypertrichosis, cardiac, gastrointestinal, craniofacial, and other systemic features. Pathogenic variants in genes encoding cohesin complex structural subunits and regulatory proteins (NIPBL, SMC1A, SMC3, HDAC8, and RAD21) are the major pathogenic contributors to CdLS. Heterozygous or hemizygous variants in the genes encoding these five proteins have been found to be contributory to CdLS, with variants in NIPBL accounting for the majority (&gt;60%) of cases, and the only gene identified to date that results in the severe or classic form of CdLS when mutated. Pathogenic variants in cohesin genes other than NIPBL tend to result in a less severe phenotype. Causative variants in additional genes, such as ANKRD11, EP300, AFF4, TAF1, and BRD4, can cause a CdLS‐like phenotype. The common role that these genes, and others, play as critical regulators of developmental transcriptional control has led to the conditions they cause being referred to as disorders of transcriptional regulation (or “DTRs”). Here, we report the results of a comprehensive molecular analysis in a cohort of 716 probands with typical and atypical CdLS in order to delineate the genetic contribution of causative variants in cohesin complex genes as well as novel candidate genes, genotype–phenotype correlations, and the utility of genome sequencing in understanding the mutational landscape in this population