bluuebunny/crossref_metadata_2025 huggingface dataset:
STUDY OF WORKLOAD, JOB SATISFACTION AND EMPLOYEE PERFORMANCE IN MEDICAL RECORD INSTALLATION OF LUBUK PAKAM HOSPITAL
Authors: Widyaningsih Fadlilah , Sundari Lusi
Published: May 2022

The success of a hospital in carrying out its role in individual health services and public health is determined by professional and quality human resources who have good performance. One of the human resources that plays an important role in achieving this role is the medical record employee who documents the actions given while in the hospital. This study is a qualitative research that aims to explore the relationship between workload and job satisfaction with employee performance. The research was conducted at Grandmed Lubuk Pakam Hospital. The sample was taken by purposive sampling, while the data was collected by conducting interviews, Focus Group Discussion (FGD), observation and document review. The validity of the data in this study was carried out through method triangulation and source triangulation. The results showed that workload and job satisfaction were related to employee performance. Most employees are included in the heavy workload category (60%) while the lowest employee performance is in the quantity aspect of work (70%). Therefore, performance improvement can be done by providing a workload that is in accordance with the abilities and abilities of employees.
PENGARUH PREGNANCY MASSAGE PUNGGUNG TERHADAP NYERI PUNGGUNG IBU HAMIL TM III
Authors: Pangesti Christiani Bumi , Puji Astuti Hutari , Eka cahyaningtyas Martina
Published: May 2022

ABSTRAK.

Ketidaknyamanan sering terjadi pada ibu hamil TM III yaitu salah satunya adalah nyeri pada punggung. Sekitar 80% wanita mengalami nyeri pada punggungnya di beberapa titik selama kehamilan. Hal ini terjadi 70% akibat perubahan otot tulang punggung, sedangkan 30% nya mungkin bisa disebabkan karena masalah pada kondisi tulang belakang sebelumnya. Pemijatan juga bertujuan untuk mengembalikan aliran vena dan getah bening, menstimulasi reseptor sensorik pada kulit dan sub kulit untuk mengurangi rasa nyeri. Studi pendahuluan yang dilakukan di Samudra Mom Kids SPA Kabupaten Sragen pada bulan Februari 2021 terdapat 10 ibu hamil yang dilakukan wawacancara menyatakan 8 (80%) ibu hamil mengeluh nyeri punggung pada saat Trimester III. Tujuan penelitian ini untuk mengetahui Pengaruh Pregnancy Massage Punggung Terhadap Nyeri Punggung Ibu Hamil. Metode penelitian ini menggunakan quasy experiment dengan rancangan non randomized pretest and posttest with control group design. Penelitian ini dilakukan selama 3 bulan, pada bulan April sampai dengan Juni 2021. Pengambilan sampel dilakukan secara  non ramdom sampling dengan teknik purposive sampling. Analisis data  menggunakan uji Mann-Whitney. Hasil ada pengaruh yang signifikan dari pemberian pregnancy massage pada punggung terhadap nyeri punggung ibu hamil Trimester III di Samudra Mom Kids SPA Kabupaten Sragen yang dibuktikan dengan nilai probabilitas (p) 0,043 < 0,05.
A, The CORRELATION STUDY OF FACTORS AFFECTING HUSBAND'S PARTICIPATION AS A VASECTOMY ACCEPTOR
Authors: Oni Dechoni Rahmawati , Dewi Anggraeni Fatimah
Published: May 2022

Background: The Family Planning Program (KB) is a program launched by the government to improve the quality of life of people in Indonesia. The results of the 2015 Population Census, Indonesia is ranked fourth as the country with the largest population in the world, which is around 237.6 million people (Indonesia Demographic and Health Survey (IDHS), 2016). As a developing country, Indonesia needs efforts to control the rate of population growth during the last decade. There are various efforts that can be taken by the government in controlling the rate of population growth. One of the efforts that can be done is the family planning program.Objective: To identify the factors that influence the husband's participation as a vasectomy family planning acceptor. Research Methods: This type of research is analytical observational with a cross-sectional approach. The location of this research is Sundi Kidul, Argorejo, Sedayu, Bantul with a sample of 30 respondents and the sampling technique is simple random sampling. The statistical test technique used in this research is chi square.Research Results: The results showed that in the knowledge variable, husbands who had high knowledge were 9 times more likely to be willing to become vasectomy family planning acceptors, in the health facility variable, the husbands who were in good health facilities had a probability of 7.4. times to be willing to become a vasectomy family planning acceptor.Conclusion: Based on the results of the research that has been done, it shows that the knowledge factor and health facilities affect the husband's participation as an MOP family planning acceptor.Keywords: Vasectomy Contraception, Husband
PENGARUH EDUKASI PIJAT OXITOXIN DENGAN PERSIAPAN LAKTASI PADA IBU HAMIL TM III DI KLINIK ASIH WALUYO JATI, BANTUL, YOGYAKARTA
Authors: Fatimah Dewi Anggraeni  , Rachmawati Dechoni
Published: May 2022

Latar Belakang: Menurunkan angka kesakitan dan kematian anak, United National Fund (UNICEF) dan World Health Organitation (WHO) merekomendasikan anak hanya disusui dengan menggunakan Air Susu Ibu (ASI) paling sedikit 6 bulan dan makanan pendamping ASI diberikan setelah bayi berumur lebih dari 6 bulan. Cakupan bayi yang diberi ASI eksklusif di Kabupaten Bantul Tahun 2019 sebesar 78,96 %, dimana cakupan ASI di Kabupaten Bantul belum mencapai target nasional yakni 80% (Dinkes Bantul, 2020). Rendahnya cakupan pemberian ASI eksklusif ini dapat berdampak pada kualitas hidup generasi penerus bangsa dan juga pada perekonomian nasional. Faktor yang mempengaruhi persiapan adalah pengetahuan, dukungan suami, paritas, pendidikan, tingkat pendapatan dan kelas yoga. Tujuan: Untuk mengetahui pengaruh eduksi pijat oxitoxim dengan persiapan laktasi pada ibu hamil TM 3. Metodologi Penelitian: Jenis penelitian ini adalah observasional analitik dengan pendekatan cross-sectional. Lokasi penelitian ini di Klinik Asih Walyo Jati, Bantul, dengan sampel sebesar 21 responden dan teknik pengambilan sampel acedental. Teknik analisis data yang digunakan dalam penelitian ini adalah dngan menggunan uji non parametrik wilcoxon. Hasil penelitian: Persiapan Laktasi Pada Ibu Hamil TM III di Klinik Asih Waluyo Jati, Bantul, Yogyakarta sebelum diberikan edukasi sebagian besar dalam kategori adalah rendah 66,67 % dan sesudah diberikan edukasi sebagian besar sebagian besar dalam kategori tinggi 52,38 %. Hasil uji analisis data dengan menggunakan wilcoxon didapatkan hasil nilai p sebesar 0,000. Kesimpulan: Terdapat Pengaruh Edukasi Pijat Oxitoxin dengan Persiapan Laktasi Pada Ibu Hamil TM III di Klinik Asih Waluyo Jati, Bantul, Yogyakarta

Kata Kunci: Persiapan Laktasi, Pijat Oxitoxin
THE ROLE OF PATHOLOGIST IN TONSILLECTOMY SPECIMENS: A TIME SINK OR NOT
Authors: Asim Najma , Nair Sarita , P A Asim
Published: May 2022

Chronic tonsillitis - A common inflammatory disease of
childhood.Chronic tonsillitis is still considered as the
commonest indication for tonsillectomy.In the present
scenario, it is a common practice in most institutions to
routinely take all tonsillectomy specimens for histopath
ological examination to evaluate infections or malignancy
without assessing patients risk factors out of fear for
medicolegal issues.
ONLINE SHOPPING TRENDS AMONG WOMEN: A COMPREHENSIVE STUDY
Authors: M Kusuma , Raju J K
Published: May 2022

The goal of this paper is to identify the trend of online apparel shopping as one of the motivating factors for women's
purchasing. To achieve the study's objectives, structured questionnaires were distributed to online apparel customers
who are aware of and purchase apparel products from online stores in and around the Davangere district of Karnataka.
Convenience and snowball sampling techniques were used to collect primary data from online apparel women
employees who are aware of,use,and buy apparel products from online stores.The data analysis and results were based
on the completion of 180 usable questionnaires by online retail apparel women customers who actively participated in
the marketing survey. Frequency analysis and graphs were used to determine trends in women's online apparel. Most
women are interested in the latest trends and western clothes,and they prefer more ethnic clothes and dark shades.They
prefer to buy online clothes during festivals and discounts and sales.
HYPOTHESIZING IMMUNE CELL-BASED POSSIBLE CURATIVE THERAPIES FOR CIGARETTE SMOKE-INDUCED EMPHYSEMA
Authors: Kumar Sinha Pushpam
Published: May 2022

In Emphysema (EM), one of the diseased states of lung disorder Chronic Obstructive Pulmonary Disease (COPD), the
alveoli walls loose shape and or damage leading to the poor exchange of oxygen and carbon dioxide in blood. Such a
disorder is accomplished by the activation of enzyme Macrophage elastase (MME) in Macrophage which breaks down
the protein elastin in the extracellular matrices of the alveoli walls. The objective of this paper is to hypothesize a
possible cure for EM. Because pro-inflammatory cytokine inhibitors have not shown promise in treating EM, I have
engineered the therapeutics (against EM) around two of the anti-inflammatory cytokines Interleukin-4 and Interleukin-
10. The same Macrophage which exhibits pro-inflammatory activation state can be made to exhibit anti-inflammatory
activation state by exposing it to anti-inflammatory cytokines. By assuming that anti-inflammatory activation state of
Macrophage can reverse elastin breakdown, and borrowing ideas from chimeric antigen receptor T cell therapy
(approved for treating many cancers) I have designed my therapeutics.
A Unifying Theory of Electronic Money and Payment Systems
Authors: Buldas Ahto , Saarepera Märt , Steiner Jamie , Draheim Dirk
Published: May 2022

We present a general theory of payment systems that is capable of describing both traditional and electronic forms of payment. Starting from the three basic functions of money and general non-functional requirements, we derive the necessary and sufficient properties of technical implementations of money and payments. We describe possible scalable implementations of e-money schemes based on a general description of their data structures (money distributions) and payments. We define the notion of bill scheme, in which the value units are bills with invariant values, and show that only the bill scheme allows for scalable and practically efficient implementations through decomposition, where the components have to process a considerably smaller amount of data and a number of payment requests, compared to the whole system.
Roadside Sensors for Traffic Management
Authors: Klein Lawrence
Published: May 2022

Knowledge of modern traffic flow sensors is key to providing traffic managers, researchers, and students the ability to understand the operation, installation requirements, strengths, and limitations of current sensor technologies to enable an informed decision as to which is appropriate for a particular application. Accordingly, this paper describes the in-roadway and above-roadway traffic flow sensor technologies, their applications and selection criteria, typical output data, and models representative of each technology. Accounting for life-cycle costs ensures that not only direct hardware and software purchase costs be considered, but also that installation, training, maintenance, and repair are factored into the sensor selection decision. The technologies discussed are mature with respect to current traffic management applications, although some may not provide the data or the accuracy required for a specific application or may not perform as needed under the environmental conditions anticipated at the installation site. Sensors selected for a first-time application should be field tested under actual operating conditions including variations in traffic flow rates, night lighting, inclement weather, and unique road configurations that may be encountered in day-to-day operation before large-scale purchases of the device are made. As alternative traffic data and information sources become increasingly available, they are progressingly finding their way into modern traffic management systems as a complement to conventional roadside sensors. 
Machine learning pattern recognition algorithms with application to coherent laser combination
Authors: Wang Dan , Du Qiang , Li Derun , Wilcox Russell , Kiran Mariam , Gilardi Antonio
Published: May 2022

This paper reports on a novel and general solution using machine learning (ML) for stabilization of a many-input, many-output system, which can learn to correlate patterns while the system is unstable or in operation. We apply this to coherent laser combination systems, to stabilize against optical phase drift. In this application, the ML algorithm finds correspondence between output interference patterns and phase errors, in both temporal pulse combination and spatial beam combination, and can be scaled to large numbers (order 100) of beams or pulses.

This is significant because our approach enables ML to learn and deterministically correct phase drift in a high-channel-count, low repetition rate system designed for high energy, where stochastic, single-output control algorithms (e.g. SPGD) become too slow. The advantage of our approach is that the amount of information scales with the number of channels, enabling high-bandwidth control of arbitrarily high channel count coherent combination, providing for lasers with high energy and power.

The approach presented in this paper has been experimentally demonstrated in a diffractive, 8-beam combination system by our group, with less than one percent stability, Opt. Express 30, 12639-12653 (2022). This manuscript expands on that work by exploring the characteristics of the algorithm in simulations, analyzing its combining efficiency and stability, and generalizing the approach to different types of coherently combined lasers with different learned patterns.

This manuscript covers the ongoing progress of using ML as a deterministic error detector, and contributes to current trends of advanced understanding and novel application in photonic systems
Automatic wheeze segmentation using harmonic-percussive source separation and empirical mode decomposition
Authors: Rocha Bruno , Pessoa Diogo , Marques Alda , Carvalho Paulo , Paiva Rui Pedro
Published: May 2022

Wheezes are adventitious respiratory sounds commonly present in patients with respiratory conditions. The presence of wheezes and their time location are relevant for clinical reasons, such as understanding the degree of bronchial obstruction. Conventional auscultation is usually employed to analyze wheezes, but remote monitoring has become a pressing need during recent years. Automatic respiratory sound analysis is required to reliably perform remote auscultation. In this work we propose a method for wheeze segmentation. Our method starts by decomposing a given audio excerpt into intrinsic mode frequencies using empirical mode decomposition. Then, we apply harmonic-percussive source separation to the resulting audio tracks and get harmonic-enhanced spectrograms, which are processed to obtain harmonic masks. Subsequently, a series of empirically derived rules are applied to find wheeze candidates. Finally, the candidates stemming from the different audio tracks are merged and median filtered. In the evaluation stage, we compare our method to three baselines on the ICBHI 2017 Respiratory Sound Database, a challenging dataset containing various noise sources and background sounds. Using the full dataset, our method outperforms the baselines, achieving an F1 of 41.9%. Our method's performance is also better than the baselines across several stratified results focusing on five variables: recording equipment, age, sex, body-mass index, and diagnosis. We conclude that, contrary to what has been reported in the literature, wheeze segmentation has not been solved for real life scenario applications. Adaptation of existing systems to demographic characteristics might be a promising step in the direction of algorithm personalization, which would make automatic wheeze segmentation methods clinically viable.
Electronics System Design of a Compact Underwater Glider
Authors: Al-Tawil Ahmed , Elkolali Moustafa , alcocer alex
Published: May 2022

Underwater gliders are power-efficient autonomous vehicles that can gather ocean data for extended periods. Small-sized underwater gliders may be more suitable for operation, deployment, and recovery using unmanned platforms in coastal areas. Designing a light compact underwater glider with a relatively compact battery and confined space makes the electronics hardware system design a significant challenge regarding compactness and power efficiency. This work presents an overview of the electronics system designed to fulfill these requirements.
A Model-Free Predictive Current Controller for Voltage Source Inverters
Authors: Kermadi Mostefa
Published: May 2022

This work proposes a model-free deadbeat predictive
current controller using the input and output data of the controlled system. The
proposed controller can be used for electric drives or grid-forming inverters. The
proposed control scheme does not require knowledge of the system parameters for
its correct operation; thus, all load parameter mismatch issues in conventional
model-based controllers are avoided. This is performed using an auto-regressive
with exogenous input (ARX) model to represent the physical system with a recursive
least square (RLS) estimation algorithm for the ARX model parameters
identification. Using the identified system parameters, an observable canonical
state-space model is constructed. Based on this system, the inverter voltage
references using the space vector modulation (SVM) are calculated using the
deadbeat control principle. The inherent sensibility of the deadbeat controller
to parameters mismatch is avoided. Experimental results confirm the validity of
the proposed Model-Free controller in terms of tracking accuracy and waveform
quality.
FLAP: Federated Learning with Attack and Privacy Awareness
Authors: xue wanli , Ahmed Nadeem , Masood Rahat , Hu Wen , Seneviratne Aruna , Jha Sanjay K.
Published: May 2022

Federated learning provides data privacy protection by keeping data used for clients' machine learning training private, and only sending model parameters updates to the centralised server/aggregator. However, the federated learning framework is still vulnerable to various attacks, such as data poisoning, launched by malicious/compromised clients. Cautious clients participating in federated learning, on the other hand, employ privacy protection techniques such as differential privacy to keep their model updates safe from inference attacks launched by the centralised aggregator. An aggregator thus needs to employ techniques to differentiate between model updates from benign, malicious and cautious clients, and to mitigate the effects of updates from clients other than benign clients. To reach this goal, we propose a novel federated learning system called FLAP which is robust against attacks launched by malicious clients and privacy protections employed by cautious clients.
Serpentine and Spiral Routing Schemes for Microwave Transmission Lines to Ensure UWB Interference Immunity
Authors: Zhechev Yevgeniy , Belousov Anton , Zabolotsky Alexander , Vlasov Sergey , Murmansky Mikhail , Pavlov Nikita , Gazizov Talgat
Published: May 2022

This article analyzes novel, adventurous routing schemes employed in designing microwave transmission lines (TL). In contrast to traditional schemes, we propose to locate two independent traces close to each other. The strong electromagnetic coupling thus formed can cause unwanted crosstalk between traces. However, if their level is acceptable, we can use the suggested routing schemes to significantly increase the powerful interference immunity of the electrical circuits by using modal distortion. Two prototypes of such TLs in the form of a serpentine and a spiral were made in which the far-end crosstalk voltage waveforms do not exceed 4.4% of the useful signal amplitudes. We performed electrodynamic simulations and measurements of such TLs in a transverse electromagnetic cell in the frequency range from 10 MHz to 5.3 GHz. The investigated lines have a low level of radiated emissions. Experimental results show that the proposed TLs decrease the voltage amplitude of the ultra-wideband pulse by at least 4 times and the voltage change rate by 10.7 times and more. In addition, the effective voltage value on the load is decreased by at least 2.2 times. The spiral scheme was found to be better than the serpentine scheme in almost all parameters. Simultaneously, the electrodynamic approach is in full agreement with the experimental study.
Intelligent Radio Resource Management in Reconfigurable IRS-enabled NOMA Networks
Authors: Basharat Sarah , Pervaiz Haris bin , Hassan Syed Ali , Ansari Rafay , Jung Haejoon , Dev Kapal , Huang Gaojian
Published: May 2022

Intelligent reflecting surfaces (IRSs) are anticipated to provide reconfigurable propagation environment for next generation communication systems. In this paper, we investigate a downlink IRS-aided multi-carrier (MC) non-orthogonal multiple access (NOMA) system, where the IRS is deployed to especially assist the blocked users to establish communication with the base station (BS). To maximize the system sum rate under network quality-of-service (QoS), rate fairness and successive interference cancellation (SIC) constraints, we formulate a problem for joint optimization of IRS elements, sub-channel assignment and power allocation. The formulated problem is mixed non-convex. Therefore, a novel three stage algorithm is proposed for the optimization of IRS elements, sub-channel assignment and power allocation. First, the IRS elements are optimized using the bisection method based iterative algorithm. Then, the sub-channel assignment problem is solved using one-to-one stable matching algorithm. Finally, the power allocation problem is solved under the given sub-channel and optimal number of IRS elements using Lagrangian dual-decomposition method based on Lagrangian multipliers. Moreover, in an effort to demonstrate the low-complexity of the proposed resource allocation scheme, we provide the complexity analysis of the proposed algorithms. The simulated results illustrate the various factors that impact the optimal number of IRS elements and the superiority of the proposed resource allocation approach in terms of network sum rate and user fairness. Furthermore, we analyse the proposed approach against a new performance metric called computational efficiency (CE).
Dissolution of Nickel-Manganese-Gallium Alloys: the first step for manufacturing hybrid micro-devices composed of Ni-Mn-Ga and Silicon layers
Authors: HU HAO , Ullakko Kari
Published: May 2022

Our aim is to develop next generation of MEMS (microelectromechanical systems) devices that are composed Ni-Mn-Ga and silicon layers. Due to large magnetic-field-induced strains of Ni-MnGa, actuating components can be fabricated in the Ni-Mn-Ga layers. Other functional components can be manufactured in silicon layer. Single crystalline Ni-Mn-Ga alloys that are grown by using the Bridgman vertical growth technique obtained so far the largest Magnetic Field Induced Strain (MFIS), a Magnetic Shape Memory (MSM) effect. Like silicon wafers, Ni-Mn-Ga wafers are also sliced from crystal-oriented single crystalline ingots. For fabricating hybrid MEMS devices such as micromanipulators and robots, lab-on-chip containing micro-pump manifolds and valves, or vibration energy harvesters, the fabrication processes used for MEMS devices will be used also for fabricating components in the NiMn-Ga layer of the hybrid MEMS devices. One of the most important processes for MEMS fabrication is the structuring of materials by chemical etching. Main goal of this study is to prove the etchant that etches silicon but not Ni-Mn-Ga and to find an etchant that etches Ni-Mn-Ga but not silicon. The present paper reports on a novel experiment about dissolving Ni-Mn-Ga alloys. An etchant composition of 69% HN𝑂3, 98% 𝐻2𝑆𝑂4, and CuSO4 • 5H2O is proposed for dissolving NiMn-Ga alloys and the variation of the dissolution rate by adjusting the concentrations of HNO3 and ultrapure water (UPW) is demonstrated. This etchant was demonstrated to etch Ni-Mn-Ga but not silicon. An HF + HNO3 acid solution commonly used for etching silicon does not dissolve Ni-MnGa.
Segmentation Quality Assessment by Automated Detection of Erroneous Surface Regions in Medical Images
Authors: Zaman Fahim Ahmed , Zhang Lichun , Zhang Honghai , Sonka Milan , Wu Xiaodong
Published: May 2022

Despite the advancement in deep learning-based semantic segmentation methods, which have achieved accuracy levels of field experts in many computer vision applications, the same general approaches may frequently fail in 3D medical image segmentation due to complex tissue structures, noisy acquisition, disease-related pathologies, as well as the lack of sufficiently large datasets with associated annotations. For expeditious diagnosis and quantitative image analysis in large-scale clinical trials, there is a compelling need to predict segmentation quality without ground truth. In this paper, we propose a deep learning framework to locate erroneous regions on the boundary surfaces of segmented objects for quality control and assessment of segmentation. A Convolutional Neural Network (CNN) is explored to learn the boundary related image features of multi-objects that can be used to identify location-specific inaccurate segmentation. The predicted error locations can facilitate efficient user interaction for interactive image segmentation (IIS). We evaluated the proposed method on two data sets: Osteoarthritis Initiative (OAI) 3D knee MRI and 3D calf muscle MRI. The average sensitivity scores of $0.96\pm0.00$ and $0.96\pm0.02$, and the average positive predictive values of $0.87\pm0.01$ and $0.93\pm0.03$ were achieved, respectively, for erroneous surface region detection of knee cartilage segmentation and calf muscle segmentation. Our experiment demonstrated promising performance of the proposed method for segmentation quality assessment by automated detection of erroneous surface regions in medical images.
Probabilistic Meta-Conv1D Driving Energy Prediction for Mobile Robots in Unstructured Terrains
Authors: Visca Marco , Powell Roger , Gao Yang , Fallah Saber
Published: May 2022

Driving energy consumption plays an important role in the navigation of autonomous mobile robots in off-road scenarios. However, the accuracy of the driving energy predictions is often affected by a high degree of uncertainty due to unknown and constantly varying terrain properties, and the complex wheel-terrain interaction in unstructured terrains. In this paper, we propose a probabilistic deep meta-learning approach to model the existing uncertainty in the driving energy consumption and efficiently adapt the probabilistic predictions based on a small number of local measurements. Our method expands upon an existing deterministic deep-meta learning model that, in contrast, only provided single-point energy estimates. The performance of our method is compared against the deterministic approach in a 3D-body dynamic simulator over several typologies of deformable terrains and unstructured geometries. In this way, we provide evidence of the benefit of the proposed method to enhance the predictions with informative probabilistic considerations, which can be crucial to the safety of mobile robots traversing challenging, unstructured environments.
Mathematical Modeling and Optimal Stopping Theory-based additional layers for 30-Day Rate Risk Prediction of Readmission to Intensive Care Units
Authors: El hassouny Azeddine , El Bouanani Faissal , Qaraqe Khalid A.
Published: May 2022

The importance of 30-day patients’ readmissions (PRs) to intensive unit care stems from the significant cost and mortality risk when the patient’s chosen class (i.e., readmitted or not to the hospital) is incorrect. The overall accuracy (OA) of the PRs classification obtained in the literature is still moderate, particularly for machine learning (ML)-enabled ANNs, where OA is around 65%, resulting in 35% critical wrong decisions. To improve such an OA, a three-stage ML-assisted algorithm employing both support vector machines (SVMs) and artificial neural networks (ANNs) techniques is proposed. Starting with a well-fitted PR accuracies distribution and using mathematical modeling, the global optimal accuracies’ interval of misclassified patients (OIMP) is obtained, and a novel theorem for the generalized secretary problem is introduced and used to select the most likely well-classified patients. The algorithm’s final phase consists of flipping the remaining incorrectly classified patients in the OIMP. Using the presented approach with ANN and SVM, the OA was raised by 5% and 19%, respectively. The proposed approach may be used for any binary classification application and expanded to any multi-class problem.
Self-Referencing Method for Removing Surface Tilting and Warping in THz Time-Domain Reflection Imaging
Authors: Artesani Alessia , Ljubenovic Marina , Traviglia Arianna , Bonetti Stefano
Published: May 2022

In this work, we demonstrate a self-referencing method for removing the optical distortion from terahertz time-domain reflection imaging. To the authors’ knowledge, this is the first time a robust and flexible method is proposed to solve spatial phase variation problem without relying on any numerical parameter optimization nor extra-instrumental components. Here, we show the errors induced by the object physical distortion in the evaluation of the electric field phase and amplitude can be removed by correcting the spatial misalignment of the temporal terahertz signal. This consequently adjusts the severe corruption of the electric field in the far-infrared frequencies. We explain and demonstrate how to address the spatial misalignment of an object, employing the method on a tilted rigid surface and a warped surface. On these examples, we obtained highly successful results, being capable to remove imaging artifacts in the frequency-domain. We retain the method advantageous for preliminary data treatment of any not-perfectly flat surface, whenever the scope of the analysis consists in the estimation of phase and amplitude of THz signal in imaging modality. 
A Signature-Based Wireless Intrusion Detection System Framework for Multi-Channel Man-in-the-Middle Attacks Against Protected Wi-Fi Networks
Authors: Thankappan Manesh , Pous Helena Rifà , Garrigues Carles
Published: May 2022

One of the advanced Man-in-the-Middle (MitM) attacks is the Multi-Channel MitM (MC-MitM) attack, which is capable of manipulating encrypted wireless frames between clients and the Access Point (AP) in a Wireless LAN (WLAN). MC-MitM attacks are possible on any client no matter how the client authenticates with the AP. Key reinstallation attacks (KRACK) in 2017-18, and the latest FragAttacks in 2021 are frontline MC-MitM attacks that widely impacted millions of Wi-Fi systems, especially those with Internet of Things (IoT) devices. Although there are security patches against some attacks, they are not applicable on every Wi-Fi or IoT device. In addition, existing defense mechanisms to combat MC-MitM attacks are not feasible because of two reasons: they either require stringent firmware modifications on all the devices in a system, or they mandate the use of several advanced hardware and software for deployment. On top of that, high technical overhead is imposed on users in terms of network setup and maintenance. In this paper, we present a lightweight and signature-based intrusion detection system framework to detect MC-MitM attacks. Our solution is a centralized, online passive monitoring system for Wi-Fi-based IoT environments without modifying any network settings or existing devices. The evaluation results show that our proposed framework can detect MC-MitM attacks with a maximum delay of 60 seconds and a minimum accuracy of 90% by short-distance detectors and 84% by long-distance detectors under normal network scenarios. Lastly, we identify our future research works to conclude this paper.
Social Media Usage Behaviors: Evidence of College Students from a Selected University in Thailand
Authors: Promsri Chaiyaset , Chaigusin Suchira , Tupmongkol Thanatas
Published: May 2022

This present study seeks to investigate college students’ social media usage behaviors. Data were collected from 109 freshman students at a selected public university through an online survey. Results demonstrated that respondents had used social media platforms for about 7.49 years. The average time spent daily on social media application was 8.23 hours. This study also revealed that this group of college students frequently used social media during the evening. For the highest use social media platform, the majority of these respondents used Facebook as a primary application followed by Instagram and YouTube. In addition, the primary purpose of social media usage among these college students was for entertainment. Limitations and research applications were also discussed
Channels of Contagion Effect on Stock Market Development in Asean – 5 Countries
Authors: Yusoff Mohd Yushairi Mat , Hassan Sallahuddin
Published: May 2022

This paper explains the theoretical channels of contagion effects on stock market development. Four channels are concerned in this paper. Portfolio adjustment by investors and monetary policies review made by the government and central bank to adapt the contagion effects, trade and financial linkages among the firms across countries and speculative activities through information asymmetry are the main channels concerned in this paper. Given by these channels, market players especially policymakers should play an important role to keep sustain the development of the stock market in ASEAN – 5 countries
Impacts of Foreign Direct Investments (Fdi) on the Nigerian Economy
Authors: Inyang Inyang , Bassey Felix
Published: May 2022

Foreign Direct Investment (FDI) is real investment interaction of the rest of the world with domestic economy. Whether this interaction mar or make economic growth depends on the area of strength of each country and usage. The relative increased trend of FDI into the extractive industry especially during the present democratic dispensation compared to the non – extractive sectors pose a question as to whether the quantum add the same way to economy growth in the country, hence this study. The study was meant to determine the effect of foreign direct investment on the Nigeria economy with the ultimate purpose of looking at the relative performance of foreign firms in both the private and public sectors of the economy, determine the relationship between foreign investment and growth of Nigerian economy, as well as evaluate the various contributions of FDI to technological and expertise base of Nigeria. To enhance efficient and effective prosecution of the study, a total sample size of fifty(50) respondents out of a total population of one hundred (100) staff of the foreign exchange market and banks ( both senior and junior were selected for the study). The investigation made use of both primary and secondary sources of data. While text books, journal articles, and other internet materials were reviewed for secondary data, personal Interviews and questionnaires were also used as instruments to gather primary data for the work. A total of nine (9) research questions and two (2) research hypotheses were formulated and used in this study, just as the study was based on stratified random sampling design. Some of the major findings of this work include that FDI; has significant impact on economic growth of Nigeria, accelerates infrastructural development in Nigeria, contributes to the development of Nigeria economy, has positive and negative Impacts on an economy, is adequately spread to all the sectors of Nigerian economy, represents a cornerstone strat
The Influence of Accounting Knowledge and Entrepreneurial Personality on Managerial Performance (Empirical Study on Customers of Bank Aceh, operational Headquarters, Banda Aceh, Indonesia )
Authors: Hambali Said , Darwanis Darwanis , Djalil Muslim A.
Published: May 2022

This study aims to test; (1) the influence of accounting knowledge and entrepreneurial personality simultaneously on the managerial performance of Bank Aceh's customers, (2) the influence of accounting knowledge on the managerial performance of Bank Aceh's customers, and (3) the influence of entrepreneurial personality on the managerial performance of Bank Aceh's customers. The unit of analysis in this study was Bank Aceh at Operational Head Office. Furthermore, the unit of observation (respondents) in this study is Bank Aceh customers who have a position as manager on owned business. Sources of research data using primary data sources derived from the acquisition of research questionnaires. While the data collection technique in this research is done by the technique of spreading the questionnaire. The method of analysis used in this research is Multiple Linear Regression Analysis. The result of the research shows that (1) knowledge of accounting and entrepreneurial personality together influence to managerial performance of Bank of Aceh customer, (2) accounting knowledge has positive influence but not significant to managerial performance of Bank of Aceh customer, and (3) entrepreneurial personality has positive influence and significant to managerial performance of Bank Aceh.
The Impact of Managerial Ownership, Institutional Ownership and Audit Committee toward Firm Value with Corporate Social Responsibility Disclosure as a Moderation of Listed Manufacturing Company in Indonesian Stock Exchange
Authors: Agusmadi Agusmadi , Nadirsyah Nadirsyah , Arfan Muhammad
Published: May 2022

This study aims to investigate the impact of managerial ownership, institutional ownership and audit committee towards the firm value with corporate social responsibility disclosure as a moderation of listing manufacturing company in Indonesia Stock Exchange (IDX) in 2011-2015. This study is categorized as a hypothesis testing research. The sample was chosen by using purposive sampling. There were 29 firms that fit the criteria as the sample; So, the observation data were 145. The data was analysed by using multiple regression linear analysis and Moderated Regression Analysis (MRA). The finding showed that managerial ownership, institutional ownership, audit committee and corporate social responsibility disclosure had significant impact to the firm value. The result of each variable such as managerial ownership, audit committtee and corporate social responsibility disclosure had positive impact towards the firm value; However, the institutional ownership had no significant impact on the firm value. The result of moderation testing from each variable indicated that corporate social responsibility disclosure had no influence on managerial ownership towards the firm value; While the influence of institutional ownership and audit committee towards the firm value of manufacturing company in Indonesia Stock Exchange (IDX) in 2011-2015 made it possible for the corporate social responsiblity disclosure used as moderation variable.
Impact of Good Governance on Sustainable Economic Development: Pakistan’s Case
Authors: Akhter Faheem , Ummara Umme
Published: May 2022

Sustainable economy of any state directly and positively affects the governance. Pakistan in last 70 years has seen many economic turf and crust. Economist as well as the responsible for the governance do show their concerns on uncertain and frequent fluctuation in Pakistan’s economy. Its high time Pakistan should have sustainable economy for the economic and social development. Sustainable economic development is a key factor which uplifts the standard of living of a common man and that also helps the state to exercise good governance effectively. The current research argues that some social and economic reforms are immediately required to have good governance in the country. Through analysis of the data endeavor would be to find the causes of economic instability and challenges for the government to impart good governance. Qualitative analysis would be carried out by collecting data available on official websites of the government institutions, international monetary agencies, interviews of the selected relevant personnel and views of the common people who are sufferers due to weak governance system in Pakistan. The bottom line is that the sustainable economic development is the key to success in the field of good governance in case of Pakistan.
A Time-Series Analysis of the Impact of Population Growth and Climate Change on Food Security in Nigeria
Authors: Korgbeelo Clement , Deekor Leelee N.
Published: May 2022

Food production in Nigeria has not kept pace with rapid population growth resulting in declining levels of national food self-sufficiency. Consequently, Nigeria faces severe food security challenges. This paper, therefore, analyzed the effects of population growth and climate change on food security in Nigeria. Specifically, the study examined the effects of population growth, mean annual rainfall, mean annual temperature, and rate of urbanization on food security (proxied by food production index) in Nigeria; Annual time-series on the above variables from 1984 to 2018 were used. The data were obtained from secondary sources. The study applied Augmented Dickey-Fuller (ADF) unit root test, Johansen cointegration test and Error Correction Mechanism (ECM) on the data. The results of data estimation indicated that population growth has a negative impact on food security while climate change (in terms of rainfall and temperature) has significant adverse effects on food security in Nigeria. The paper recommends among other things, a set of climate change adaptation and mitigation measures to improve the food security situation in the country.
The Marketing Ethical Strategies of Thailand’s Organic Rice Based on Eastern Economic Corridor (EEC)
Authors: BAOGUO LI , LAKSITAMAS PRIN
Published: May 2022

Despite being one of the world’s major exporters of food, Thailand is facing mounting problems concerning unstainable agriculture practices. Organic farming could help to address environmental, social and economic issues, organic rice practices are proven to improve soil fertility, foster biodiversity, increase economic yield. The stakeholders of organic rice practices should adopt the Eastern Economic Corridor (EEC) favorable policies and embrace the digital era. The increased utilization of smart organic farming technology and greater access of corporate social responsibility could help to add the organic rice value and enlarge the export volumes to international markets. The effectively implementation of the marketing ethical strategies could help to reduce Thailand’s rice famer heavy household debt and get out of Thai poverty debt traps.
Citizen’s Participation in the Urban Local Governance Process in Bangladesh: A Case Study on Rajshahi City Corporation
Authors: Kabir Md. Rezwanul , Bithi Taskin Ara Taznin , Jyoti Tanzima Aktar
Published: May 2022

This paper, based on an empirical study, analyses the scopes, forms and nature of people’s participation in the urban local governance process in Bangladesh. It provides insight into why and how representative democracy has failed to ensure active citizen participation. In doing so, it explores the underlying socio-political, institutional and legal factors that should be taken into account when implementing interventions aimed at encouraging more inclusive participatory local governance practices. This paper argues that the institutional design of the urban local government system largely follows the political elites’ intention of consolidating political power bases. This in turn severely narrows down the scope for citizen’s participation in the governance process.
A Study Assessing the Brand Loyalty Creation by Promotion Mix for KOTON Brand
Authors: Singh Swapnil , Singh Uma Shankar
Published: May 2022

Today, the competitive markets are full of similar products and goods which sometimes do not have any physical differences also. Therefore, there is a need for the companies to develop a specific feature which makes their brand distinguishable from the commonly available products in the same category. Research problem observed was to have the conceptual verification for promotion mix impact on creation of brand loyalty in the specific case of KOTON brand. The research has adopted the quantitative research method where the design of research is descriptive. Simple random sampling technique of probability sampling is applied for choosing respondents with sample size of 216 respondents. A survey instrument has been adopted to collect the data which comprises of two sections; the first section is of demographic information (Gender, Age, Marital Status, Level of Education and Family Income). The second section is related to Sales Promotion activities (Advertising: Item 1 - Item 4; Sales Promotion: Item 5 - Item 8; Public Relation: Item 9 - Item 12, and Personal Selling: Item 13 – Item 16) and Brand Loyalty consisting of Item 17 - Item 21. The scope of the study is well defined where conceptual scope is promotion mix and brand loyalty, industrial scope chosen is KOTON brand, and the geographic scope is taken as the Kurdistan region for the present study. Data analysis performed using SPSS 24 for statistical tests includes Percentage, Frequency, One sample T-test, Correlation and Regression. Research problem got the solution fulfilling research objectives formulated as the Brand Loyalty of consumers towards KOTON brand. Promotion Mix has shown the highest effect (B) on Brand Loyalty with .472, and the correlation is (Beta) .275. The four variables tested with respect to Brand Loyalty and they justified that Personal Selling has the highest B value (.451) and Beta .315. Public Relation is the second important variable followed by Advertising with a comparatively lower B and
Crisis Leadership in a Hotel Industry during COVID-19 Pandemic in Thailand
Authors: Promsri Chaiyaset , Chaigusin Suchira , Magtanaroong Pinya , Magtanaroong Kawin
Published: May 2022

As previous literatures and research demonstrated the importance of crisis leadership, the major purpose of this article was to identify the significance of crisis leadership during COVID-19 Pandemic. Numerous key characteristics of crisis leadership were proposed in many sources. During COVID-19 pandemic, the plea for crisis leadership is unavoidable in all business arenas. Nonetheless, as hotel industry has been severely affected by COVID-19, this article needed to explore whether or not crisis leadership played a vital role on mitigating the crisis. Three listed hotel companies in Stock Exchange of Thailand (SET) were selected as the cases for analysis. Results demonstrated that only one company among these three hotel companies could earn positive net profit income during the pandemic while the other two companies ended up with negative net income. Despite CEOs of these hotel companies implemented key qualities of crisis leadership, the results were not the equivalent in terms of financial performance depending on several hidden forces that were excluded in this analysis, which outlined the limitations of this study. Hence, the repetitive study and analysis with additional approaches and information were recommended.