bluuebunny/crossref_metadata_2025 huggingface dataset:
Superficial siderosis: comparison of two cases indicates two distinct diagnostic entities. Illustrative cases
Authors: Krishnakumar Asha , Ghadiyaram Ashwin , Patel Vishal C. , Opalak Charles F. , Dixit Neel , Broaddus William C.
Published: May 2023

BACKGROUND

Superficial siderosis is the deposition of hemosiderin in the superficial layers of the central nervous system. It has been described in patients with chronic leakage of blood into the cerebrospinal fluid or with amyloid angiopathy, often associated with Alzheimer’s disease (AD).

OBSERVATIONS

We present two cases of superficial siderosis with vastly different symptomatologies and treatment courses. The patient in case 1 had diffuse superficial siderosis demonstrated on T2-weighted magnetic resonance imaging (MRI), appearing mostly in the inferior cerebellum and extending throughout the neuraxis. He presented with hearing loss, spasticity, gait abnormalities, and urinary incontinence. Ultimately, surgical exploration of the thoracic spinal dura revealed an arteriovenous fistula, which was obliterated. His clinical course stabilized but with persistent deficits. The patient in case 2 had a family history of AD and underwent MRI to evaluate for memory impairment, which demonstrated superficial siderosis of the left occipital lobe. Lumbar puncture demonstrated only traumatic contamination by red blood cells, but tau protein analysis was consistent with the diagnosis of AD.

LESSONS

Superficial siderosis is a diagnostic term prompted by findings on MRI that can arise due to two different pathological entities. The diagnosis in case 1 should be termed diffuse superficial siderosis and in case 2 should be termed lobar cortical siderosis.
Contralateral lower limb radiculopathy by extraforaminal disc herniation following oblique lumbar interbody fusion in degenerative lumbar disorder: illustrative cases
Authors: Hattori Satoshi , Maeda Toru
Published: May 2023

BACKGROUND

Contralateral lower limb radiculopathy is a potential early complication of oblique lumbar interbody fusion (OLIF) in degenerative lumbar disorders. Among several pathologies related to contralateral radiculopathy following OLIF, extraforaminal disc herniation during the OLIF procedure is very rare.

OBSERVATIONS

Case 1 is a 68-year-old male underwent L4–5 and L5–6 OLIF for recurrent lumbar canal stenosis–expressed right leg pain and muscle weakness after surgery. Case 2 is a 76-year-old female on whom L4–5 OLIF was performed for L4 degenerative spondylolisthesis and who presented right leg pain and numbness postoperatively. In both patients, OLIF cages were inserted into the posterior part of the disc space or obliquely and the extraforaminal extruded disc compressed opposite exiting nerve roots (L5 root in case 1 and L4 root in case 2) as shown on magnetic resonance imaging (MRI). Surgical decompression with discectomy was required for pain relief and neurological improvement in both cases.

LESSONS

When emerging from new-onset opposite limb radiculopathy attributed to the OLIF procedure, extraforaminal disc herniation should be considered a potential pathology and MRI is useful for early diagnosis and selecting a subsequent management, including surgery.
Los beneficios del yoga en un entorno comunitario para adolescentes que asisten a un hospital de día de salud mental
Authors: Hermida-Barros Laura , Santamarina-Perez Pilar , Beltran Alicia , Pastor Yeray , Guillen Elias , Morer Astrid
Published: May 2023

Los adolescentes con trastorno mental grave suelen tener importantes dificultades en la toma de conciencia de sus sensaciones corporales, emociones y pensamientos, lo que se asocia con escasas habilidades de regulación emocional. Objetivo: Este estudio tiene como objetivo analizar los efectos del yoga en las habilidades de conciencia corporal en adolescentes con trastorno mental grave que asisten a un hospital de día. Material y métodos: La muestra estuvo formada por ocho adolescentes de 12 a 16 años. Los pacientes acudieron a la Casa del Tíbet de Barcelona semanalmente para recibir sesiones de yoga durante un máximo de 14 sesiones. El Mindful Attention Awareness Scale-Adolescents (MAAS-A) y el Child and Adolescent Mindfulness Measure (CAMM) fueron rellenadas antes y después del programa. Resultados: Al final de la intervención la conciencia corporal mejoró, especialmente en el CAMM. Conclusiones: Los resultados sugieren que el yoga puede mejorar las habilidades de conciencia plena en adolescentes con trastornos mentales que por su gravedad e interferencia asisten a un hospital de día.
Pandemi Dönemindeki Yara Enfeksiyon Etkenlerinin ve Antibiyotik Duyarlılıklarının Pandemi Öncesi ile Karşılaştırılması/ Comparison of Wound Infectious Agents and Antibiotic Sensitivity During the Covid-19 Pandemic Period with Pre-Pandemic
Authors: AKKAYA Oya
Published: May 2023

Amaç: Pandemi öncesi (PÖ) ve pandemi dönemi (PD) yara enfeksiyon etkenleri ve antibiyotik direnç profillerini karşılaştırmak.

Gereç ve Yöntemler: Ocak 2019-Aralık 2021 tarihleri arasında yara sürüntü örneklerinde üreyen bakteriler ve antibiyotik direnç oranları retrospektif olarak kaydedilmiştir. Bu sonuçlar PÖ (Ocak 2019 -Haziran 2020; n = 684) ve PD (Haziran 2020- Aralık 2021; n = 255) arasında karşılaştırılmıştır.

Bulgular: Yara yeri enfeksiyonlarının kliniklere göre dağılımı şu şekildeydi: PÖ grubunda %27 ile yoğun bakımlar, %15 genel cerrahi servisi ve %13 enfeksiyon kliniği; PD grubunda %29 yoğun bakımlar, %24 COVID servisi ve %12 genel cerrahi servisi. Patojen sıklıkları, PÖ grubunda %19 E.coli, %16 S.aureus, %12 P.aeruginosa, %11 K.pneumoniae ve %10 A.baumannii iken, PD grubunda ise sırasıyla %22, %19, %9, %14, %10 olmuştur. PÖ grubunda S.aureus suşlarının %28’i metisilin dirençli iken, PD grubunda bu oran %35 olmuştur (p = 0,328). Meropeneme dirençli K.pneumoniae sıklığı PÖ'de %47’den PD'de %53’e yükselmiştir (p = 0,693).

Sonuç: COVID-19 PD’de yara enfeksiyonlarında etken olan bakteri tiplerinin değişmediği, ama bazı antibiyotiklere direnç oranlarının hafif düzeyde arttığı gözlenmiştir. Pandemide antibiyotiklerin gereğinden çok ve uygunsuz kullanımı, çoklu ilaç direcine sahip gram negatif bakterilerin artışının sebebi olabilir.

Aim: to compare the infectious agents and antibiotic resistance profiles of wound samples obtained during the pre-pandemic period (PP) and pandemic period (PD).

Materials and Methods: We retrospectively recorded the rates of bacteria grown in wound swab samples and antibiotic resistance between January 2019 and December 2021. These results were compared between the PP (January 2019 - June 2020; n=684) and PD (June 2020 - December 2021; n=255) periods.

Results: The distribution of wound infections according to clinics was as follows: in the PP, 27% were in intensive care units (ICU), 15% were in general surgery, and 13% were in infection clinics; in the PD, 29% were in ICU, 24% were in COVID service, and 12% were in general surgery. The pathogen frequencies were 19% for E.coli, 16% for S.aureus, 12% for P.aeruginosa, 11% for K.pneumoniae, and 10% for A baumannii in the PP, while they were 22%, 19%, 9%, 14%, and 10%, respectively, in the PD. While 28% of S aureus strains were methicillin-resistant in the PP, it was 35% in the PD (p=0.328). The incidence of meropenem-resistant K.pneumoniae increased from 47% in the PP to 53% in the PD (p=0.693).

Conclusion: Our study showed that the types of bacteria causing wound infections did not change significantly during the COVID-19 pandemic period, but there was a slight increase in resistance rates to some antibiotics. The increase in multi-drug resistant gram-negative bacteria may be attributed to the excessive and inappropriate use of antibiotics during the pandemic.
AUGMENTASI DATA PADA IMPLEMENTASI CONVOLUTIONAL NEURAL NETWORK ARSITEKTUR EFFICIENTNET-B3 UNTUK KLASIFIKASI PENYAKIT DAUN PADI
Authors: Putri Ayuni Desy , Jasril  , Irsyad Muhammad , Yanto Febi , Sanjaya Suwanto
Published: May 2023

Padi adalah salah satu jenis biji-bijian dengan urutan ketiga sebagai bahan pokok makanan setelah gandum dan jagung. Jenis penyakit yang menyerang daun tanaman terdiri atas blast, brownspot, leaf smut. Pada penelitian ini metode Convolutional Neural Network dengan Arsitektur Efficientnet-B3 digunakan untuk mengklasifikasikan penyakit daun pada tanaman padi. Tujuan penelitian ini membandingkan tingkat akurasi menggunakan data tanpa augmentasi (asli) dan data yang telah di augmentasi. Augmentasi data yang digunakan brightness, rotation, dan vertical_flip. Selain itu dilakukan juga pengujian menggunakan optimizer yang berbeda yaitu  optimizer RMSprop dan optimizer SGD (Stochastic Gradient Descent). Pengujian dilakukan dengan tiga model perbandingan data yaitu 90:10, 80;20 dan 70:30. Hasil pengujian memperlihatkan akurasi tertinggi menggunakan data asli pada rasio 70:30 yaitu sebesar 92.39% dengan optimizer RMSprop. Sedangkan untuk akurasi tertinggi menggunakan data augmentasi terdapat pada rasio 90:10 yaitu sebesar 98.91% dengan optimizer RMSprop.
Hubungan Posisi Kerja dengan Keluhan Low Back Pain pada Pekerja Sarang Burung Walet Kembangbahu
Authors: Ayuni Rinda Fitri , Inayah Zufra
Published: May 2023

Low back pain adalah gangguan musculoskeletal yang mempengaruhi punggung bagian bawah yang disebabkan oleh posisi kerja yang salah. Statistik AS menunjukkan bahwa tingkat kejadian tahunan sekitar 15%-20%, sebanyak 90% kasus nyeri punggung disebabkan oleh posisi tubuh yang salah saat bekerja. Penelitian ini menganalisis hubungan posisi kerja dengan keluhan low back pain pada pekerja sarang burung walet Kembangbahu. Metode yang digunakan adalah observasional analitik dengan desain penelitian cross sectional. Sampel penelitian sebanyak 44 pekerja dengan menggunakan cluster random sampling dan instrumen menggunakan kuesioner. Hasil analisis data menggunakan uji Somers’d diperoleh nilai p value 0,036 < α 0,05 sehingga dapat disimpulkan bahwa terdapat hubungan yang signifikan antara posisi kerja dengan keluhan low back pain pada pekerja sarang burung walet Kembangbahu.
PENGGUNAAN MEDIA SOSIAL FACEBOOK SEBAGAI MEDIA PEMASARAN PRODUK
Authors: Hazrah Siti
Published: May 2023

Setiap orang membutuhkan informasi untuk menunjang aktivitas mereka, sehingga berusaha untuk mengakses informasi secepat mungkin. Untuk memperkenalkan produk  barang atau jasa yang akan dijual, perusahaan atau usaha kecil dan menengah membutuhkan promosi, dan pola di bidang bisnis melalui facebook atau melalui toko  berbasis web sangat menggembirakan. Pencipta menggunakan pendekatan pemeriksaan  subjektif yang mencerahkan di mana informasi yang dikumpulkan sebagian besar  berupa kata-kata dan kalimat, atau gambar yang lebih penting daripada angka atau  frekuensi. Pelaksanaan pemanfaatan media berbasis web Facebook meliputi  membangun metodologi data, merencanakan kemajuan dan membangun jaringan  dengan menggunakan gathering dan fanspages
From a Grassland to a Bush Capital: A Historic Review of Canberra’s Green Infrastructure Development
Authors: MOFRAD FAHIMEH , IGNATIEVA MARIA
Published: May 2023

Canberra was built in harmony with its landscape setting, creating a legacy of urban form well-connected to the natural environment. Its urban design and planning not only amplified the surrounding natural landscape such as forested hills and mountains but also created a human-made green urban character. However, plans for future development as a compact city pose a challenge to conserving the city’s green spaces. A green infrastructure plan is necessary to consider the city’s green space design heritage and the linked socio-ecological values while minimising the urban footprint. The paper employs a historical literature review to understand the factors and characteristics that shaped Canberra’s green character and the socio-ecological values of its green spaces. The research found the influence of historical and modern design and planning concepts in consolidating green infrastructure and creating ecological corridors and social infrastructure. One of the essential conditions for maintaining the unique character of Canberra is the preservation of the socio-ecological values of its existing green spaces. A trade-off study must be conducted to balance green infrastructure planning while considering these values, in light of development changes.
Constructing multistage linear fuzzy ellipsoid number to express multi-channel uncertain digital information and application
Authors: Wang Tengfei , Shi Peng
Published: May 2023

In this paper, the problems of expressing and fusing multi-channel uncertain digital information is studied. The concept of a special high-dimensional fuzzy number called multi-level linear fuzzy ellipsoid number is given, and a method of constructing such high dimensional fuzzy number to express multi-channel uncertain digital information is established. Then a calculation formula of the centroid of multistage linear fuzzy ellipsoid number is deduced. And then, as an application example of multi-channel uncertain digital information fusion, a specific example is given to show ranking some objects which are characterized by multi-channel uncertain digital information by using the obtained results and the concept of fuzzy order on high dimensional fuzzy number space.
More accurate simulation for insurance data based on a modified SVM polynomial method1
Authors: Nurhidayat Irfan , Pimpunchat Busayamas , Klomsungcharoen Wiriyabhorn
Published: May 2023

This study aims to present the modified SVM polynomial method in order to evaluate insurance data. The research methodology discusses classical and modified SVM polynomial methods by R programming, and uses performance profiles to create the most preferable methods. It offers a new algorithm called an accurate evaluating algorithm as the way to construct the modified SVM polynomial method. The classical SVM polynomial method is also represented as the main idea in finding the modified polynomial SVM method. Model Performance Evaluation (MPE), Receiver Operating Characteristics (ROCs) Curve, Area Under Curve (AUC), partial AUC (pAUC), smoothing, confidence intervals, and thresholds are further named an accurate evaluating algorithm, employed to build the modified SVM polynomial method. The research paper also presents the best performance profiles based on the computing time and the number of iterations of both classical and modified SVM polynomial methods. Performance profiles show numerical comparisons based on both methods involving insurance data also displayed in this paper. It can be concluded that applying an accurate evaluating algorithm on the modified SVM polynomial method will improve the data accuracy up to 86% via computing time and iterations compared to the classical SVM polynomial method, which is only 79%. This accurate evaluating algorithm can be applied to various large-sized data by utilizing R programming with changing any suitable kernels for that data. This vital discovery will offer solutions for faster and more accurate data analysis that can benefit researchers, the private sector, or governments struggling with data.
Input predictors for networked iterative learning control systems with data dropouts and time delays
Authors: Huang Lixun , Sun Lijun , Chen Tianfei , Zhang Qiuwen , Huo Linlin , Liu Weihua
Published: May 2023

Hold-up compensation decelerates the convergence of iterative learning control (ILC) systems with data dropouts and time delays. Only depending on the prior knowledge of both ILC controllers and transmission channels, this paper develops a predictor to calculate the input not received on time due to data dropouts and time delays. First, a controller adopting the proportional learning strategy is considered directly, which is appropriate for objects in ideal communication conditions. After that, two data-receiving equations are given to describe the effect of data dropouts and one-step time delays. Finally, a predictor is designed according to the innovation analysis approach. Since the prediction uses all historical input at the identical time index in previous iterations, the predicted input is more approximate to the one not received on time than the input held up for compensation. Simulation results show the object with prediction compensation tracks the expected trajectory faster than that with input-hold compensation.
Exponential information measures-driven Pythagorean fuzzy MADM method and its application to new energy battery supplier evaluation problem
Authors: Jin Feifei , Li Danning , Guo Shuyan , Zhou Ligang , Chen Yi , Zhu Jiaming
Published: May 2023

Under the Pythagorean fuzzy environment, this paper presents a multi-attribute decision-making (MADM) model based on exponential entropy measure and exponential similarity measure to evaluate new energy battery supplier’s performance. In this method, the notion of Pythagorean fuzzy linguistic sets (PFLSs) is first introduced by combining the linguistic fuzzy sets (LFSs) and the Pythagorean fuzzy sets (PFSs). Then, the axiomatic definitions of Pythagorean fuzzy entropy and Pythagorean fuzzy similarity measure are developed to measure the degree of uncertainty and similarity between two Pythagorean fuzzy linguistic values (PFLVs). The PFLVs can be expressed by the linguistic membership degree (LMD) and linguistic non-membership degree (LNMD). In addition, we construct two new information measure formulas based on exponential function. Through a series of proofs, we verify that they satisfy the axiomatic conditions of entropy and similarity measure of Pythagorean fuzzy language respectively. On this basis, we research the relationship between the two information measures. Finally, we present a novel Pythagorean fuzzy linguistic MADM model. An example for evaluating performance of new energy battery supplier is given to explain the effectiveness of the newly-developed approach. The stability and validity of the newly-developed approach is performed by sensitivity analysis and comparative analysis.
Tunicate Swarm Algorithm based Optimized PID controller for automatic generation control of two area hybrid power system
Authors: Memon Abdul Sami , Laghari J.A. , Bhayo Muhammad Akram , Khokhar Suhail , Chandio Sadullah , Memon Muhammad Saleem
Published: May 2023

In the modern power system, the use of renewable energy sources is increasing rapidly, which makes the system more sensitive. Therefore, it requires effective controllers to operate within the allowable ranges. The existing techniques based on cascaded controllers implemented so far for load frequency control have the advantage of improving the system response. However, this makes the system a more complex and time-consuming process. This makes the system more straightforward, makes it easy to optimize PID parameters, and provides results in acceptable ranges. This paper attempts to solve the load frequency control (LFC) problem in an interconnected hybrid power system with a classical PID controller employing the tunicate swarm algorithm (TSA). This algorithm is used for two areas of an interconnected hybrid power system: thermal, hydro, nuclear, and wind. The PID controller parameters are optimized by tunicate swarm algorithm using integral time absolute error (ITAE) based objective function. To show the robustness of the proposed TSA algorithm, a sensitivity analysis is performed for four case studies ranging from 20% to 30% load increments and decrements. The performance of the proposed TSA algorithm has been compared with the well-known optimization algorithms, particle swarm optimization (PSO), artificial bee colony (ABC), and arithmetic optimization algorithm (AOA) in terms of overshoot, undershoot, and settling time. The simulation results show that the proposed TSA has better optimization capability than PSO, ABC, and AOA in terms of overshoot, undershoot, and settling time.
Algebraic structures on commutative coquantales
Authors: Oh Ju-Mok
Published: May 2023

In this paper, we present the notion of commutative coquantale frames as logical relational systems. We introduce an approach to study these frames through the utilization of distance functions in place of the commonly used fuzzy partially orders. We show that a commutative coquantale frame can be regarded as an algebraic structure that induces a commutative coquantale, while a commutative coquantale with q-distance function leads to the development of a commutative coquantale frame. Moreover, we provide several examples pertaining to these notions.
Aero-engine residual life prediction based on time-series residual neural networks
Authors: Yu Ping , Wang Haotian , Cao Jie
Published: May 2023

In order to address the timing problem, invalid data problem and deep feature extraction problem in the current deep learning based aero-engine remaining life prediction, a remaining life prediction method based on time-series residual neural networks is proposed. This method uses a combination of temporal feature extraction layer and deep feature extraction layer to build the network model. First, the temporal feature extraction layer with multi-head structure is used to extract rich temporal features; then, the spatial attention mechanism is applied to improve the weights of important data; finally, the deep feature extraction layer is used to process the deep features of the data. To verify the effectiveness of the proposed method, experiments are conducted on the C-MAPSS dataset provided by NASA. The experimental results show that the method proposed in this paper can make accurate predictions of the remaining service life under different sub-datasets and has outstanding performance advantages in comparison with other outstanding networks.
Benchmark datasets and real-time autoimmune disease dataset analysis using machine learning algorithms with implementation, analysis and results
Authors: Ramasamy Uma , Santhoshkumar Sundar
Published: May 2023

A machine learning model intends to produce a secure model with low bias and variance. Finding the optimal machine learning model for a dataset is a challenging task. A suitable machine learning model is yet to be specified for the Arthritis Profile Data dataset. Autoimmune disease is widely spread all over the world. Some autoimmune arthritis diseases are Rheumatoid Arthritis, Psoriatic Arthritis, Juvenile Arthritis, etc. These diseases come under both categories autoimmune and inflammatory diseases. The proposed work is designed to suggest the best machine learning model with the highest observed accuracy for the Arthritis Profile Data. Many authors do not compare newly created datasets with previously used datasets. This can lead to inaccurate results due to the lack of reliable comparison. Additionally, it can prevent researchers from detecting potential bias in the data. Comparing datasets can help to identify and address any potential issues and improve the accuracy of the results. It is important to review existing datasets before beginning a new project to ensure the accuracy of the results. This article is the first study on the topic that analysis the accuracy behavior of each machine learning model concerning the Arthritis Profile Data and various benchmark disease datasets with different hold-out and k-fold cross-validation methods. The study concludes with a glimpse of whether dataset and feature size affect model prediction accuracy and proffers a machine learning model for the Arthritis Profile Data. The proposed research explores base learning classification algorithms and ensemble methods such as Logistic Regression, K-Nearest Neighbor, Support Vector Machine, Random Forest, and Extreme Gradient Boosting from machine learning. Our empirical evidence clearly states XGBoost ensemble technique shows the highest accuracy for the Arthritis Profile Data.
ED algorithm of inscription picture combining fuzzy logic rules
Authors: Guo Wei , Zhang Chuchen
Published: May 2023

The expansive growth of information on the Internet has led to new developments in computer vision technology and image processing techniques. Since stone inscriptions are subject to erosion and polishing by the external environment for years, it is difficult to extract image and text information. In this study, the fuzzy control theory is combined with edge detection technology for image edge detection. Firstly, a suitable fuzzy rule and affiliation function are set, then a fuzzy control system is used to extract and detect the image edge information, and then a fuzzy logic rule-based edge detection algorithm is proposed to detect the inscription images. To test the performance of the algorithm, the detection effect of the image is first analyzed from a subjective perspective. The experimental results show that the proposed algorithm has better edge detection for both inscription and lena images, with better noise suppression without excessive distortion, and clearer inscription images. The proposed algorithm has the lowest MSE value of 41.26 when the detection object is the lena image b, and the highest PSNR value of 33.84 when the detection object is the lena image a. The proposed algorithm has the lowest MSE value of 41.26 when the detection object is the lena image b, and the highest PSNR value of 41.26 when the detection object is the lena image b. The proposed algorithm has the highest PSNR value of 33.84 when the detection object is the lena image b. In summary, the analysis of both subjective and objective indicators shows that the inscription image processing algorithm used in this paper has better processing effect, and the processed images become clearer with less distortion, which is helpful for both inscription image and text extraction.
Trade credit or credit insurance? A green supply chain finance design scheme with multi-objective programming
Authors: Zhang Linzi , Shi Yong
Published: May 2023

Classical supply chain finance (SCF) primarily focuses on the financial service among all upstream and downstream supply chain participants. Due to the continuously deteriorating of the ecological environment, an environmental-friendly SCF system is urgently needed. In this paper, we propose a novel SCF design scheme with environmental concerns, i.e., green supply chain finance (GSCF), consider the financing channels both from banks and from consumers, and design a bi-objective optimization model that depicts the trade-off between the benefit and the emission. Further, an improved normalized normal constraint (INNC) Pareto method is developed to address the optimal financing strategy of the bi-objective model. We then conduct a numerical case of a Taiwanese steel firm to verify the effectiveness and efficiency of our method. Results show that our model provides a portfolio of optimal solutions on Pareto frontier which can be applied as an effective decision support system when designing a GSCF. Furthermore, the sensitivity analysis also presents the impact of environmental investment cost, technological ratio of companies and the interest rate of trade credit on the optimal configuration of the GSCF.
CDRKD: An improved density peak algorithm based on kernel fuzzy measure in the overlapping community detection
Authors: Yi Weiguo , Ma Bin , Zhang Heng , Ma Siwei
Published: May 2023

Compared with other traditional community discovery algorithms, density peak clustering algorithm is more efficient in getting network structures through clustering. However, DPC needs to contain the distance information between all nodes as sources, so it cannot directly processing the complex network represented by the adjacency matrix. DPC introduces truncation distance when calculating the local density of nodes, which is usually set as a fixed value according to experience, and lacks self-adaptability for different network structures. A feasible solution to those problems is to combined rough set theory and kernel fuzzy similarity measures. In this work, we present overlapping community detection algorithm based on improved rough entropy fusion density peak. The algorithm applied rough set theory to attribute reduction of massive high-dimensional data. Another algorithm defines the similarity of sample points by the inner product between two vectors on the basis of fuzzy partition matrix. Finally, a community detection algorithm based on rough entropy and kernel fuzzy density peaks clustering (CDRKD) has proposed by combining the two algorithms above, we perform an extensive set of experiments to verify the effectiveness and feasibility of the algorithm.
Mobile robot path planning based on hybrid ant colony optimization
Authors: Zhang Zhaojun , Lu Jiawei , Xu Zhaoxiong , Xu Tao
Published: May 2023

To solve the problems of the ant colony optimization (ACO), such as slow convergence speed, easy to fall into local extremum and deadlock in path planning, this paper proposed an improved ACO, which was hybridized by PSO based on logistic chaotic mapping, called hybrid ant colony optimization (HACO). According to the number of obstacles around the next feasible node, HACO distributes the initial pheromones unevenly to avoid the ant getting stuck in deadlock. According to the orientation of the next node selected by the ant, the heuristic information is adaptively adjusted to guide the ant to the direction of the target position. When updating the pheromone, the local and global search mechanism of the particle swarm optimization is used to improve the pheromone update rule and accelerate convergence speed. Finally, the grid method is used to construct the environment map, and simulation experiments are conducted in different environments. The experimental results verify the effectiveness and feasibility of the improved algorithm.
Research on evaluation of emergency communication vehicle cabin’s internal environment design based on q-rung orthopair fuzzy information
Authors: Zhang Jiarui
Published: May 2023

The design of the emergency communication vehicle is centered around the overall layout, which is characterized by the fact that the vehicle chassis is mostly purchased parts and is equipped with an insulated and insulated box, mainly used for instrument operation and equipment placement. The emergency communication vehicle cabin environment includes: cabin seats; seat cover; control cabinet, including operation keyboard, display screen, etc; The ceiling and carpet that make up the interior space of the car; Storage box for storage equipment; tool cabinet; cabin control system facilities; Fire prevention and extinguishing facilities in the cabin; various handrails, coat racks, short ladders, lighting facilities, etc. inside the car. The design of emergency communication vehicle interior environment involves multiple disciplines, and the selection of design schemes requires scientific and reasonable evaluation methods to select reasonable schemes for optimization design. The evaluation of emergency communication vehicle cabin’s internal environment design is classical multiple attribute decision making (MADM) problems. In this article, based on bidirectional projection and grey relational projection measure, we shall propose some projection models with q-rung orthopair fuzzy sets (q-ROFSs). First of all, the definition of q-ROFSs is introduced. Furthermore, some projection models with q-ROFSs are proposed based on the bidirectional projection and grey relational projection model. Based on developed weighted projection models, the MADM model is established and all computing steps are simply depicted. Finally, a numerical example for evaluation of emergency communication vehicle cabin’s internal environment design is given to illustrate this new model and some comparisons are conducted to illustrate advantages of the new built method.
Blood platelet RNA profiles do not enable for nivolumab response prediction at baseline in patients with non-small cell lung cancer
Authors: Muller Mirte , Best Myron G. , van der Noort Vincent , Hiltermann T. Jeroen N. , Niemeijer Anna-Larissa N. , Post Edward , Sol Nik , In ’t Veld Sjors G.J.G. , Nogarede Tineke , Visser Lisanne , Schouten Robert D. , van den Broek Daan , Hummelink Karlijn , Monkhorst Kim , de Langen Adrianus J. , Schuuring Ed , Smit Egbert F. , Groen Harry J.M. , Wurdinger Thomas , van den Heuvel Michel M.
Published: May 2023

BACKGROUND:

Anti-PD-(L)1 immunotherapy has emerged as a promising treatment approach for non-small cell lung cancer (NSCLC), though the response rates remain low. Pre-treatment response prediction may improve patient allocation for immunotherapy. Blood platelets act as active immune-like cells, thereby constraining T-cell activity, propagating cancer metastasis, and adjusting their spliced mRNA content.

OBJECTIVE:

We investigated whether platelet RNA profiles before start of nivolumab anti-PD1 immunotherapy may predict treatment responses.

METHODS:

We performed RNA-sequencing of platelet RNA samples isolated from stage III-IV NSCLC patients before treatment with nivolumab. Treatment response was scored by the RECIST-criteria. Data were analyzed using a predefined thromboSeq analysis including a particle-swarm-enhanced support vector machine (PSO/SVM) classification algorithm.

RESULTS:

We collected and processed a 286-samples cohort, separated into a training/evaluation and validation series and subjected those to training of the PSO/SVM-classification algorithm. We observed only low classification accuracy in the 107-samples validation series (area under the curve (AUC) training series: 0.73 (95% -CI: 0.63–0.84, n = 88 samples), AUC evaluation series: 0.64 (95% -CI: 0.51–0.76, n = 91 samples), AUC validation series: 0.58 (95% -CI: 0.45–0.70, n = 107 samples)), employing a five-RNAs biomarker panel.

CONCLUSIONS:

We concluded that platelet RNA may have minimally discriminative capacity for anti-PD1 nivolumab response prediction, with which the current methodology is insufficient for diagnostic application.
Horizon and curvature
Authors: Haraux Alain
Published: May 2023

This short paper is devoted to a strange looking question: is it possible to deduce the shape of a smooth convex set by measuring at each point the distance of the horizon standing at a fixed height h? The question is surprisingly difficult and we only have partial results.
Conflict of Ukrainian Generations X and Y: Ways to overcome it in the context of the war in Ukraine
Authors: Blyznyuk Tetyana , Maistrenko Olga
Published: May 2023

In the conditions of war, the problem of maintaining a comfortable psychological climate in professional teams and society in general is acutely felt because Ukrainians are in a depressed psychological state. Conflicts among people of different ages are also escalating, as representatives of the baby boomer generation are gradually being replaced by Generation Y, and therefore most Ukrainian companies are teams of representatives of Generations X and Y. The purpose of this study is to find ways to overcome the problem of conflict between different generations. Among the key scientific methods of this study is M. Rokeach’s model, which was used to rank the terminal and instrumental values of representatives of Ukrainian generations X and Y, and the method of canonical correlations, used for comparative analysis of the value structure of the analysed generations. The main results of the study indicate that the aggravation of relations and the emergence of misunderstandings among Ukrainians is a consequence not only of the influence of war, but also of the conflict of the most economically active generations – X and Y. This conflict is caused by differences in the perception of life (i.e., in values), a large difference in the socio-political conditions of formation and belonging to different archetypes of generations according to the Strauss–Howe generational theory. Ukrainian generation X is a recessive generation of “nomads”, while generation Y is a dominant generation of “heroes”. The results of a comparative analysis of the dominant terminal and instrumental values of these generations indicated that 50% of the dominant values are common terminal and only 33% are common instrumental. It was found that the Ukrainian Generation X has more post-materialistic values, while Generation Y prefers materialistic values, which was a consequence of socio-political events in Ukraine, under which these generations were formed. The practical significance of the results obtained lies in the fact that the proposed recommendations for overcoming the conflict of Ukrainian Generations X and Y by factoring in the most important values for each of these generations will help not only to overcome the conflict of generations, but also to increase the effectiveness of their interaction.
Psychological profile and prerequisites for the formation of the killer’s personality
Authors: Spytska Liana
Published: May 2023

The relevance of the study is conditioned upon the elevated level of crime and scientific interest in determining the prerequisites for murders that are individual in nature, develop into a series of hidden intentions and have complex consequences for the life of society. Clarifying the psychological causes of serious crimes is important for preventive work in the defined area. The purpose of this study was to determine the personality traits of murderers, to identify the prerequisites for the formation of criminal behaviour, to investigate the classification and rating of serial crimes by cruelty and methods, to analyse statistical data on the commission of murders. In the study of the nature of serial murders, the following methods were used: the method of analysis and synthesis, the biographical method, the statistical method, and the generalization method. Using theoretical analysis, the psychological root causes of homicide drives, their main features and methods of implementation, and gender characteristics regarding the strength of committing a crime were identified; the data obtained were confirmed by real statistical indicators. The study highlighted the problem of increasing criminal cases caused by the mental state of the individual. The features of the psychology of the killer were covered, and the influence of childhood and life circumstances on the formation of the internal urge to commit murder was substantiated. The factors that encourage violence were identified. The types of serial killers were identified, and the “handwriting” of crime execution was analysed. The essence of impulsive and serial murder was delineated, and the concept of moral statistics as a provocative factor in committing a crime was covered. A psychological portrait of a serial killer was formed. Features of early research at the level of physiology and genetics were established. The presented theoretical material not only serves as an informational resource but can also be used in carrying out preventive measures related to early education, the methods of which have a preventive and correctional impact.
Pemetaan Ruangan Dua Dimensi Menggunakan Sensor Lidar 360 Derajat Pada Mobile Robot
Authors: Ranaminanta Adib Nur , Nurcipto Dedi , Heryanto M Ary
Published: May 2023

Sensor lidar sering diterapkan pada kendaraan dan robot untuk mengetahui jarak pada objek sekitar. Pada sensor lidar 360o sudut pengambilan data dapat dilakukan pada satu putaran penuh, sehingga pada sensor lidar jenis ini dapat menampilkan antarmuka objek sekeliling 360o. Pada penelitian ini peneliti mencoba mengambil data objek ruang menggunakan sensor Lidar 360o yang diterapkan pada mobile robot untuk memperkirakan ukuran ruang. Namun, untuk mengukur sebuah ruang secara penuh yang tidak terjangkau oleh sensor diperlukan pembacaan odometri pada robot. Pada penelitian ini membahas mengenai pembacaa sensor gyroscope   dan rotary encoder untuk memperoleh titik x dan y pada robot. Dan membahas tentang pemetaan dari sensor lidar menggunakan data x dan y yang telah diperbarui menggunakan data pengolahan sensor gyroscope   dan rotary encoder. Hasil dari penelitian ini diperoleh pembacaan odometri dari sensor gyroscope   dan rotary encoder diperoleh error RMS 13.40 cm pada sumbu x, 10.63 cm pada sumbu y.
Simulasi Sistem Otomasi Rumah Hemat Energi Berbasis Programmable Logic Controller
Authors: Syafrudi Syafrudi , Ningtias Dieta Wahyu Asry
Published: May 2023

Sistem smart home yang meliputi efisiensi energi, kenyamanan dan keamanan rumah merupakan faktor penting bagi kegiatan modern. Sistem ini dikontrol secara otomatis, hemat energi, dan diimplementasikan pada smart home dengan fitur dasar pada kenyamanan dan keamanan penghuni rumah. Peralatan rumah seperti lampu ruangan, lampu taman, motor pintu garasi, dan motor pintu digunakan sebagai beban yang nantinya dikontrol oleh PLC menggunakan program utama berupa diagram ladder. Sensor LDR dan sensor PIR yang terhubung dengan PLC menjadikan lampu ruangan dapat dikontrol penggunaannya sesuai kondisi lingkungan untuk memenuhi kebutuhan efisiensi energi. Pintu gerbang dan pintu garasi dapat dikontrol secara otomatis maupun manual sehingga dapat meningkatkan kenyamanan penghuni rumah. Fasilitas keamanan juga ditambahkan dengan menggunakan sensor. Hasil pengujian endurance testing menunjukkan tingkat keberhasilan kinerja prototipe sebesar 100% pada operasi manual, 100% pada mode keamanan, dan 90% pada otomatisasi. Sementara penilaian oleh ahli/pakar menunjukkan bahwa prototipe sudah baik dan layak untuk diimplementasikan sebagai smart home.
Desain Perancangan Inverter 1 Fasa Pada Pompa Submersibel Mengunakan Sumber Hybrid Solar Cell Dan Microhydro
Authors: Prakoso Dimas Nur , Hidayatullah Nur Asyik , Triyono Budi , Hidayat Muhammad Edy
Published: May 2023

Inverter adalah salah satu alat elektronika yang digunakan untuk mengubah tegangan DC (Dirrect Current) menjadi tegangan AC (Alternating Current). Gelombang output dari suatu inverter dapat berupa gelombang sinus (sine wave), gelombang kotak (square wave), dan gelombang sinus modifikasi (modified sine wave). Inverter 1 fasa full bridge ini dirancang menggunakan teknik PWM berbasis mikrokontroler Arduino uno, optocoupler sebagai driver 4 MOSFET, transistor 9014 sebagai penguat tegangan inverter, serta rangkaian double boost converter sebagai penaik tegangan pengganti transformator. Inverter ini mengubah tegangan dari double boost converter sebesar 311volt DC menjadi 220volt AC dan menggunakan baterai berkapasitas 12V-35Ah sehingga mampu digunakan untuk menyalakan beban lebih lama. Tegangan output yang dihasilkan oleh double boost converter sebesar 316volt DC. Inverter ini mampu mengubah dari tegangan 316volt DC ke 288,1volt AC frekuensi 49,50 Hz dengan gelombang output berbentuk gelombang kotak. Inverter ini diaplikasikan pada pembangkit listrik tenaga floating hydro portable.
Deteksi Bahasa Isyarat Dalam Pengenalan Huruf Hijaiyah Dengan Metode YOLOV5
Authors: Mulyana Dadang Iskandar , Lazuardi Muhammad Faizal , Yel Mesra Betty
Published: May 2023

Bahasa isyarat adalah Bahasa yang menggunakan gerakan tangan dan tubuh, serta ekspresi dalam menyampaikan kata dan kalimat. Belajar huruf Hijaiyah adalah langkah awal untuk bisa membaca Al-Qur'an. Anak penyandang tunarungu dan tunawicara memiliki IQ di bawah rata-rata anak normal, yang menyebabkan proses belajar mereka lebih lambat dan memerlukan metode khusus. Ada sekelompok besar tunarungu-bisu di seluruh dunia, dan bahasa isyarat adalah alat komunikasi utama dalam komunitas ini. Penyandang tunarungu dan tunanetra perlu untuk dapat berkomunikasi dengan orang lain yang mampu mendengar, dan orang yang mendengar juga perlu memahami bahasa isyarat, yang menghasilkan permintaan yang besar untuk pelajaran bahasa isyarat. Sudah banyak penelitian yang membahas tentang pendeteksian sebuah objek menggunakan citra digital untuk mengenali macam-macam bahasa isyarat. Penelitian kali ini penulis menerapkan metode YOLOV5 untuk mendeteksi Bahasa isyarat khususnya huruf hijaiyah. Pada penelitian ini penulis menggunakan dataset sebesar 1014 gambar dengan kelas huruf hijiyah dari alif sampai ya. Hasil penelitian yang di peroleh menggunakan metode YOLOV5 terbukti dapat mengenali objek secara konsisten dengan nilai tingkat akurasi yang cukup tinggi yaitu 95%
Menghitung Jumlah Sel Goblet Usus Ayam Secara Otomatis Dengan Metode Multilevel Thresholding
Authors: Sepriana Dedi , Adi Kusworo , Widodo Catur Adi
Published: May 2023

Goblet cell was an indicator the health of chicken intestine that was strongly influence of chicken productivity. So far, the determination of goblet cell was conducted by visual used of microscope. These methods required a long time and also the result was subjective value. The aim of this study was image processed for calculating the number of goblet cells in the chicken intestine and assessed the method applied performance. The material used was 30 images of broiler intestine preparations with AB-PAS staining. The research was carried out used multilevel thresholding and labeling methods for calculating the number of goblet cells in intestine of chicken. Chicken intestinal tissue that had been prepared with AB-PAS staining was acquired used a microscope equipped with a camera and connected to a PC. The result of the acquisition was an RGB scale image, so needed to be converted into an HSV scale image. Next, conducted the extraction process the hue component to convert the image to a gray scale. The gray scale image can be used in the process of identifying goblet cells using the multilevel thresholding method. Objects in the form of goblet cells that have been separated from other tissues were then repaired using morphological operations. The results of morphological operations were then calculated using the labeling method. The results showed that the method applied was successful in automatically calculated the number of goblet cells. The results of calculations using the multilevel thresholding and labeling method had accuracy rate of 90% compared with the results of calculated of visually directly by analyst.
Studi Pengaruh Covid-19 Pada Berbagai Sektor Pengguna Tenaga Listrik di Bangka Belitung
Authors: Ramadani Fajar , Asmar Asmar , Gusa Rika Favoria , Sunanda Wahri
Published: May 2023

Electricity in Indonesia, especially in the Bangka Belitung Islands, has been affected by the COVID-19 pandemic. The effect occurred at the beginning of the pandemic in the second quarter of 2020, namely the household sector rose to 3.3%, the social sector fell -3.1%, the industrial sector rose to 15%, business fell -9.8%, the office sector government buildings rose 3%, and the public/other street lighting sector fell -47%. By using statistical tests on the classical assumption test all sectors are normally distributed. In the partial test using multiple linear regression test for the household sector, industry, and government office buildings, only connected power affects energy consumption, namely 70.5%, 97.7%, and 37.4%. In the social and business sectors, there is an effect of connected power and tariff prices on energy consumption, namely 92% and -13%, while business is 42% and 10%, respectively. By using the simultaneous test, the household sector has an effect of 68.2%, the social sector is 75.5%, the industrial sector is 97.5%, the business sector is 44.2% and government buildings are 32.5%.
Development Arduino Data Logger using INA219 Sensor for Battery Capacity Monitoring
Authors: Kusuma Hollanda Arief , Ariandhi Rifki , Refly Septia , Nugraha Sapta
Published: May 2023

A battery, also known as an accumulator, is an electrical cell that can reverse an electrochemical process with high efficiency. It is essential in the use of electrical systems as storage devices. It has two critical parameters: current and voltage. These parameters can affect the battery's behavior, which leads to battery usage. As a result, a battery monitoring instrument is required to monitor the battery's current and voltage while it is in use. The researchers designed a monitoring instrument with an Arduino Pro Mini 5V microcontroller as the main processor, INA219 as a current and voltage sensor, RTC DS3231 as a time reader, micro SD card module as a data logger, and OLED SH1106 to display the current, voltage, and time readings. The calibration of the INA219 sensor has a current reading accuracy of 91.43% and a voltage reading accuracy of 99.87%. RMSE was measured at 227.65 mA and 0.0146 V. The device was tested with a BSB DB 12-55Ah battery connected to 30W PJU lamps. In the results of this test, we experienced voltage drop and current ripple in the battery performance. The battery usage capacity was 49.71 Ah. Based on this research, the device built can monitor battery conditions.