bluuebunny/crossref_metadata_2025 huggingface dataset:
A Case of Eosinophilic Granulomatosis with Polyangiitis (Churg-Strauss, EGPA) Presenting With Relapsed Mononeuritis Multiplex
Authors: BA Hilmi , MM Ainon
Published: November 2020

We report a case of eosinophilic granulomatosis with polyangiitis (EGPA), a rare multisystem disorder characterized by difficult-to-control asthma, hypereosinophilia and polyneuropathy. We also discuss the Five Factor Score (FFS) risk stratification strategy, which is used to quantitate the extent of the disease and guide treatment strategy.
Hemorrhagic Thoracic Spinal Epidural Angiolipoma: A Case Report
Authors: A Saufi , KH Chan , Z Zamzuri , AR Ralib , AR Azlina
Published: November 2020

Spinal epidural angiolipomas are rare benign tumors. The tumors contain both vascular and mature adipose components. Typically, they present with a progressive clinical course. Acute presentation is rare. We present a case of a fifteen-year-old girl who presented with a sudden onset of backpain followed by paraparesis with bladder and bowel incontinence. Neurological examination showed sensory loss below T10 with Grade 2 motor power. Spinal MRI showed long segment extradural lesion at T6-T9 level. Multiple laminectomy and excision of the tumor containing areas of hemorrhage was performed. Histopathology report revealed angiolipoma.
A case report of pyomyoma: radiological diagnosis of a potentially fatal complication of uterine leiomyoma.
Authors: MY Mubarak , MD Noordini
Published: November 2020

Pyomyoma (suppurative leiomyoma) is a rare complication of uterine leiomyoma. It results from infarction and infection of a leiomyoma. It may lead to diagnostic and therapeutic difficulties with potential complications such as bacteraemia, uterine rupture, compressive effect to adjacent structures and even death. We report a case of pyomyoma based on the Ultrasound (US) and Computed Tomography (CT) findings and literature review on the subject.
Knowledge, Attitude and Practice of Breast Self Examination in Female Health Workers in Olabisi Onabanjo University Teaching Hospital, Sagamu, Nigeria
Authors: AOJ Agboola , AM Deji-Agboola , KS Oritogun , AA Musa , TY Oyebadejo , BA Ayoade
Published: November 2020

Background: Breast cancer is the leading cause of cancer mortality in women worldwide. This study was designed to assess the knowledge, attitude and practice of breast self examination (BSE) among female health workers in Sagamu. Methods: Questionnaire was used to obtain information such as demographic characteristics, knowledge of breast cancer, attitudes towards BSE and questions relating to practices of BSE from female health workers. Statistical analysis was carried out using descriptive statistics and Chi Square method. Results: The medical doctors had more knowledge about breast cancer than the nurses and laboratory scientists. The medical doctors (81.8%), laboratory scientists (56.5%) and the nurses (41.4%) knew the correct timing and frequency for performance of BSE. The monthly practice of BSE was very low among the nurses (30%), while only 68.2% of the doctors and 78.3% of laboratory scientist admitted carrying out BSE monthly. The doctors (68.2%), nurses (35.7%) and laboratory scientist (30.4%) started BSE below the age of 19 years. Conclusion: The results indicate that the nurses had poor attitude towards BSE and this affected their practice of BSE though they had knowledge. The finding that some of the female health workers did not practice BSE, suggests that there is a need for continuing education programs to change attitude and behaviour towards BSE.
Clinical And Genetic Study of The Sptlc1 Gene Mutation in Patients With Heridetary Sensory Neuropahty Type 1
Authors: H Mourad , W Fadel , M El Batch
Published: November 2020

Introduction: Hereditary sensory neuropathy type 1 (HSN1) is the most common hereditary disorder of peripheral sensory neurons. Materials and methods: This study was carried out on 15 patients with hereditary sensory neuropathy type-1 and 10 healthy individuals as a control group. Detailed family history and thorough clinical and neurological examination were performed to all patients. Nerve conduction velocity of ulnar and lateral popliteal nerves (motor and sensory) as well as audiograms was carried out for all members of the studied groups. The laboratory study included the determination of serum C-reactive protein (CRP) and serum nucleasomes as well as molecular detection of the serine palmitoytransferase (SPTLC-1) gene mutations for all studied groups. Results: There was predominance in male who developed more sever clinical manifestations than females. The disease onset was in the second and third decades of life. Patients with HSN 1 manifested reduced conduction velocity in both motor and sensory fibers of the lateral popliteal nerve (p< 0.01) however the ulnar nerve was spared (p = 0.61). Audiometry revealed bilateral partial nerve deafness in 3 cases and complete deafness in one case. Serum CRP and nucleosomes were significantly elevated in all patients as compared to the control group (p < 0.01). The genetic study revealed mutations of the SPTLC1 in all studied patients compared to the control group. Point mutation C133W was observed in younger patients having severe clinical manifestations with prominent leg ulceration, while the point mutation C133Y was observed in the older patients complaining of hearing loss. The mutation V144D was found in patients with mild clinical presentation having minimal ulceration and no hearing abnormalities. Conclusion: The SPTLC1 gene mutations play an important role in the pathogenesis and variability in clinical presentation of HSN1 disease.
Smoker Desaturation during General Anaesthesia: A Case Report
Authors: MA Hadi , MR Azrina , A Zamzila , O Ariff
Published: November 2020

We report a case of sudden hypoxaemia after intubation in a patient who had smoked a few hours prior to a surgical procedure. The cause of his desaturation was not related to bronchial secretions, bronchospasm or obstruction of the upper airways but most likely due to reduced oxygen saturation in the body prior to surgery. We managed to secure the airway and prevent prolonged desaturation by instituting remedial measures. Our conclusion is that cessation of smoking is very important and need to be emphasized in all patients having surgery under general anaesthesia. This applies to emergency cases as well.
Association between Metabolic Syndrome and Alcohol Consumption: A Cross-sectional Study
Authors: Trisrivirat Kochakorn , Pinyopornpanish Kanokporn , Jiraporncharoen Wichuda , Chutarattanakul Lalita , Angkurawaranon Chaisiri
Published: November 2020

Objective: To determine the association between metabolic syndrome and alcohol consumption, including drinking patterns and risk of harm. Materials and Methods: A cross-sectional study was conducted on 400 participants recruited from the Outpatient Unit of the Family Medicine Department, Faculty of Medicine, Chiang Mai University. Physical examination and blood tests were carried out to evaluate the presence of metabolic syndrome. The drinking patterns were stratified into four levels, which were abstinence, occasional drinking, light–moderate drinking, and heavy drinking (>40 gm/day). The Alcohol Use Disorders Identification Test was used to evaluate the risk of harm from alcohol consumption. Results: The percentage of current drinkers was 27.3%, and most of them were men (87.2%). Waist circumference, triglyceride levels, and diastolic blood pressure were significantly higher among those with a heavy drinking habit and harmful alcohol use/dependence. High density lipoprotein cholesterol (HDL-C) showed different results. A J-shaped association was found between HDL-C and drinking pattern, but an inverse relationship was indicated with the risk of harm. Metabolic syndrome was found to be significantly associated with heavy drinking (OR=4.4, 95% Confidence Interval (CI) 1.2–15.6, p-value 0.021) and the harmful use/dependent categories (OR=5.0, 95% CI 1.1–23.1, p-value 0.039). Conclusion: The results suggest that alcohol drinking tends to be associated with an increased risk of metabolic syndrome. This condition should be screened regularly especially in those with heavy drinking or at-risk drinking habits.
Qui, entre Orient et Occident, mange de la viande, quelle viande et pourquoi ?
Authors: Digard Jean-Pierre
Published: November 2020

Abstract:The consumption of meat depends first of all on religious prescripts: unlike Christianity, Judaism and Islam prohibit certain meats. Then comes the cultural status (distinct from the legal status) of animals: in Europe, the consumption of rabbits has declined due to his assimilation to a “pet”. After an increase in the post Second World War period, meat consumption has been declining in Europe since the 2000s; similarly, in North Africa and the Middle East, its consumption tends to be closer to that of Europe. These fluctuations owe more to changes in living modes and standards than to animalist activism.

Résumé :La consommation carnée dépend d’abord de prescriptions religieuses : à la différence du christianisme, le judaïsme et l’islam interdisent certaines viandes. Vient ensuite le statut culturel (distinct du statut légal) des animaux : en Europe, la consommation du lapin a reculé du fait de son assimilation à un « animal de compagnie ». En Europe toujours, après une hausse après la Seconde Guerre mondiale, la consommation carnée diminue depuis les années 2000 ; à l’inverse, en Afrique du Nord et au Moyen-Orient, elle tend à se rapprocher de celle de l’Europe. Ces fluctuations doivent davantage à l’évolution des genres et des niveaux de vie qu’au militantisme animaliste.
Gilân (Northern Iran) Cuisine Specificity
Authors: Bromberger Christian
Published: November 2020

Abstract: In Iran, the northern province of Gilân displays a strong specificity, including the registers of food and cooking. The regional culinary style is characterised by five traits: the base is rice, with a predilection for green, acid, eggs and fish. Cooking methods are also original in the Iranian world: Gilân’s culinary culture is not about ovens or dry cooking or roasting, but about browning, simmering and steaming.

Résumé : En Iran, la province septentrionale du Gilân présente une forte spécificité, en particulier dans les domaines de l’alimentation et de la cuisine. Le style culinaire régional se caractérise par cinq traits : la base est le riz avec une prédilection, en accompagnement, pour le vert et l’acide, pour les oeufs et pour le poisson. Les techniques de cuisson présentent aussi une certaine originalité dans le monde iranien : au grillé et à la cuisson sèche, on préfère le mijoté, le revenu.
Sortir Manger / Eating Out
Authors: Gillot Gaëlle
Published: November 2020

Abstract:Textile workers in Morocco are a vulnerable group. Subjected to exhausting working conditions, poorly paid, often poorly nourished, their lives are structured around working and cooking. Although they say have no leisure activities, they often eat outside. Picnics provide good opportunities for relaxation and above all allow them to make themselves visible throughout the city. This practice gives the textile workers of Rabat and Tangier an experience of urbanness that allows them to appropriate the whole city, to take their time, and to exist as city dwellers. This article is based on a survey carried out as part of an IRD program from 2012 to 2018.

Résumé :Les ouvrières du textile au Maroc constituent une population vulnérable. Soumises à des conditions de travail épuisantes, mal payées, souvent mal nourries, leurs journées sont rythmées par le travail et les repas. Si elles ne se reconnaissent aucun loisir, elles sortent pourtant souvent manger à l’extérieur. Les pique-niques sont des moments privilégiés de détente et surtout ils permettent de se déployer dans la ville et de se rendre visibles. Grâce à cette pratique, les ouvrières du textile de Rabat et Tanger expérimentent une urbanité qui leur permet de s’approprier toute la ville, de prendre leur temps et d’exister en tant que citadines. Cet article repose sur une enquête menée dans le cadre d’un programme IRD de 2012 à 2018.
Kegagalan Analisis Laporan Keuangan Dalam Memprediksi Kebangkrutan BPR/BPRS di Indonesia
Authors: Miskak Suwandi -
Published: November 2020

Since LPS operated in 2005 until 2017, LPS has liquidated 84 BPR/BPRS which were declared as failed banks by BI/OJK. The cause of the failure of the BPR/BPRS is that the bank cannot meet the minimum capital adequacy ratio (CAR) due to losses suffered by the bank. The bank losses are caused fraud by owner, management and employees. Losses are recognized in the financial statements after it found by BI/OJK. We forecast quarterly CAR data before a BPR/BPRS is determined as a bank under special supervision to determine the ability of CAR data prediction whether the bank will be placed as a bank under special supervision using ARIMA. The research result shows the difference between forecasting CAR and actual CAR is significant. This means that CAR data calculated based on financial statements cannot predict the BPR/BPRS will be determined as a bank under special supervision, which in turn has the potential to become a failed bank.
Pengaruh KPR terhadap Keterjangkauan Harga Properti Residensial
Authors: Buhaerah Pihri
Published: November 2020

AbstractThis paper describes and examines the linkage of house mortgages on residential property price growth in Indonesia by using qualitative and quantitative research methods. The qualitative research approach is used to elaborate descriptively the role of house mortgages on residential property prices. To strengthen it, this study then employs one of time series regression analyses namely autoregressive distributed lag (ARDL) model for the period of 2002Q1-2017Q4. To achieve the objective of this study, data was collected from secondary sources such as Bank for International Settlements (BIS), Bank Indonesia (BI), and Central Statistics Agency (BPS). The qualitative approach shows that under lack of land banking and public housing zones, the expansion of house mortgages affect positively residential property prices both for private and public housing.Â  The argument has been confirmed from regression analysis by using the ARDL model. The estimation results using the ARDL model show that there is a positive and significant relationship between house mortgage on residential property price growth both in the long-run and in the short-run. Â Keywords: house mortgage, property residential prices, land, ARDL modelJEL Classification: C22, E51, G21Â Â AbstrakStudi ini membahas secara deskriptif dan empiris peran pembiayaan pemilikan rumah terhadap harga properti residensial di Indonesia dengan menggunakan metode penelitian kualitatif dan kuantitatif. Pendekatan kualitatif digunakan untuk menggambarkan secara deskriptif peran pembiyaan pemilikan rumah terhadap harga properti residensial. Selanjutnya, untuk memperkuat argument tersebut, studi ini kemudian melibatkan salah satu teknik analisis regresi data runtun waktu yaitu model autoregressive distributed lag (ARDL) untuk periode 2002Q1-2017Q4. Untuk mencapai tujuan penelitian, data dikumpulkan dari beragam sumber data sekunder seperti Bank for International Settlements (BIS), Bank Indonesia (BI), dan Badan Pusat Statistik (BPS). Hasilnya, dengan menggunakan pendekatan kualitatif menunjukkan bahwa tanpa pelembagaan bank tanah dan zonasi khusus perumahan rakyat, skema pembiayaan kepemilikan rumah hanya akan melambungkan harga properti residensial. Argumen ini juga terkonfirmasi dari analisis regresi dengan menggunakan model ARDL. Hasil estimasi dengan menggunakan model ARDL menunjukkan bahwa terdapat hubungan jangka panjang antara kredit kepemilikan rumah dengan harga property residensial baik untuk jangka pendek maupun jangka panjang.Â Â Kata Kunci: Kredit pemilikan rumah, harga properti residensial, tanah, model ARDLJEL Classification: C22, E51, G21Â
Pengaruh Quantitative Easing dan Tapering Off serta Indikator Makroekonomi terhadap Nilai Tukar Rupiah
Authors: Dinata Almuyasa Vidia , Oktora Siskarossa Ika
Published: November 2020

Since the 2008 financial crisis, rupiahâ€™s volatility has experienced high volatility. This volatility is indicated associated with other macroeconomic indicators such as BI-Rate, export-import ratio, CPI, IHSG, and foreign exchange reserves against the rupiah exchange rate. In addition, in terms of an external factor, there is a nonconventional monetary policy package taken by The Fed to restore the economy of the United States after the 2008 financial crisis called Quantitative Easing (QE) and Tapering Off (TO). This study aims to see the effect of these two policies and macroeconomic variables on the rupiah exchange rate. This research uses time-series data from January 2005-December 2017 is carried out using the Autoregressive Distributed Lag (ARDL) method. Based on the result, we concluded that the model obtained was ARDL (3,0,5,0,4,3). We found that rupiah exchange rate 1st and 3rd lag, export-import ratio 3rd lag, foreign exchange reserves current period, CPI 4th lag, IHSG current period, 1st, 2nd, and 3rd lag, and the QE policy significantly affect the rupiahâ€™s volatility. This shows that the stability of the rupiah is not only based on fundamental economic variables but also based on the monetary policies of other countries.
Pengaruh Nilai Pelanggan, Kepuasan Pelanggan dan Kepercayaan terhadap Loyalitas Pelanggan pada Kedai Kopi Online di Kota Medan
Authors: Sebayang Stevani Korentia , Situmorang Syafrizal Helmi
Published: November 2020

The purpose of this study was to determine the influence of perceived value, customer satisfaction, and trust on online coffee shop customer loyalty in medan city. The population in this study are customer of online coffee shops in the city of Medan. The sample in this study were 150 online coffee shop customer in city of Medan who had bought online coffee priducts at least 2 times. The method of analysis used in this research is descriptive analysis method and multiple linear regression analysis processed with SPSS for windows software. Based on the F test (simultaneously) it shows that customer value, customer satisfaction and trust together or simultaneously have a significant effect on customer loyalty. The results of t-test (partial), the variable customer value has a positive and significant effect on customer loyalty, the customer satisfaction variable has a positive and significant effect on customer loyalty, and trust has a positive and significant effect on customer loyalty. Based on the large value of Adjusted Rsquare, it can be seen that the variable customer value, customer satisfaction and trust have a simultaneous effect on customer loyalty by 0.462 or 46.2% while the remaining 53.8% are other factors outside the variables studied.

Keywords : Perceived Value, Customer Satisfaction, Trust dan Customer Loyalty
Pengaruh Motivasi Intrinsik dan Motivasi Ekstrinsik terhadap Kinerja Aparatur Sipil Negara (ASN) pada Badan Kesatuan Bangsa dan Politik Kabupaten Kutai Timur
Authors: Syafranuddin Rizky Aulia Hidayah , Rahmanto Efendi
Published: November 2020

Tujuan dari penelitian ini adalah untuk mengetahui pengaruh motivasi intrinsik dan motivasi ekstrinsik baik secara simultan maupun parsial terhadap kinerja aparatur sipil negara (ASN) pada Badan Kesatuan Bangsa dan Politik Kabupaten Kutai Timur. Sampel dalam penelitian ini adalah seluruh ASN pada Badan Kesatuan Bangsa dan Politik Kabupaten Kutai Timur yang berjumlah 32 orang. Uji yang dilakukan dalam penelitian ini mengunakan uji validitas, reliabilitas, asumsi klasik, regresi berganda, uji T dan uji F dengan menggunakan bantuan aplikasi software SPSS 25.0. Hasil penelitian menunjukkan bahwa motivasi intrinsik dan motivasi ekstrinsik baik secara simultan dan parsial berpengaruh positif dan signifikan terhadap kinerja ASN pada Badan Kesatuan Bangsa dan Politik Kabupaten Kutai Timur, atau dapat dikatakan bahwa seluruh hipotesis dalam penelitian ini diterima.

Kata Kunci: Motivasi Intrinsik, Motivasi Ekstrinsik, Kinerja
Analisis Kualitas Distribusi Air Menggunakan Metode Six Sigma DMAIC Pada Pdam Surya Sembada Kota Surabaya
Authors: Ulfah Evi Maria , Auliandri Tuwanku Aria
Published: November 2020

PDAM Surya Sembada Surabaya is a water supply company. This company distributes and supplies hygienic water to all residents in Surabaya. PDAM Surya Sembada Surabaya always tries to make customers satisfied with the provided services. Moreover, the company also tries to continue the improvements based on the management quality of ISO 9001: 2008. However, in the process of water distribution, some customers are still complaining due to the PDAM’s service, which indicates that not all the customers are satisfied. It is the duty of PDAM Surabaya to improve the quality services. This study focuses on providing the causes defects analysis of PDAM Surabaya Surya Sembada water distribution using the Six Sigma DMAIC. This study used descriptive qualitative approach with an emphasis on the question of how. The results of the research proved that there are two defects in the water distribution change into CTQ; defect TDA (No Water) and IMR (stench muddy water). In 2015, performance of Surabaya PDAM Surya Sembada showed the DPMO value as 844 and the value of capability sigma as 4.64. Based on Pareto diagram, this study stated that the dominant defect is TDA. This study applied the basic cause effect diagram to show the defect cause problem and used FMEA as a recommendation for continuous improvement that is expected to achieve zero defects.

Keywords: Six Sigma, defect, DMAIC, DPMO, value of capability sigma, CTQ, Pareto charts, cause and effect diagram, FMEA.
Psychological Well-being Pekerja Informal Sektor Industri Kreatif UMKM di Kota Semarang (Studi Fenomenal pada Kampung Batik Semarangan)
Authors: Wibowo Mochammad Eric Suryakencana , Djastuti Indi
Published: November 2020

Tujuan dari penelitian ini adalah untuk mengetahui bagaimana kondisi kesejahteraan psikologis dari pekerja informal sektor indusri kreatif UMKM di Kota Semarang, khususnya di Kampung Batik Semarang. Penelitian ini menggunakan 6 dimensi dari kesejahteraan psikologis. Penelitian ini menggunakan metode kualitatif dengan pendekatan fenomenologi dan memuat sejumlah pengrajin batik sebagai partisipan yang berpartisipasi dalam penelitian ini. Pengambilan data menggunakan wawancara mendalam yang dilakukan secara langsung kepada para partisipan tersebut. Hasil dari penelitian menunjukkan bahwa seluruh partisipan memiliki kesejahteraan psikologis yang dipengaruhi oleh masing-masing dimensi. Namun secara khusus, diketahui terdapat dua dimensi yang paling mempengaruhi kesejahteraan psikologis dari para pekerja informal di sana, yakni dimensi hubungan positif dengan orang lain dan dimensi penguasaan lingkungan.

Kata Kunci: Kesejahteraan psikologis, pekerja informal, fenomenologi, pengrajin batik, dimensi hubungan positif dengan orang lain, dimensi penguasaan lingkungan.
Replikasi Model Inovasi Pelayanan Administrasi Kependudukan Di Indonesia
Authors: Wiryanto Wisber
Published: November 2020

Kementerian/lembaga/daerah yang menghasilkan inovasi terbaik dalam kompetisi inovasi pelayanan publik memperoleh penghargaan top-99 perlu dijadikan contoh dengan mereplikasi model inovasinya untuk peningkatan kualitas layanan publik instansi lainnya. Oleh karena itu, dilakukan kajian mencari model inovasi pelayanan administrasi kependudukan (adminduk) yang dapat direplikasi, dengan rumusan permasalahan, apa model inovasi pelayanan adminduk yang dapat direplikasi? Bagaimana cara mereplikasi model inovasi pelayanan tersebut? Metode penelitian kajian pustaka digunakan dengan memanfaatkan referensi, dokumen dan data yang relevan. Teknik accidental sampling digunakan untuk mengambil sampel sejumlah 10 instansi yang diberi penghargaan inovasi pelayanan adminduk top-99 tahun 2018, 2019 dan 2020, kemudian melakukan analisis data deskriptif kualitatif sehingga diperoleh model inovasi pelayanan adminduk yang dapat direplikasi. Kajian dilakukan semester pertama tahun 2020. Hasil kajian menemukan model inovasi pelayanan adminduk sebanyak 12 inovasi terbaik yang dapat direplikasi oleh instansi lainnya. Replikasi model tersebut dapat dilakukan dengan cara adopsi, adaptasi dan modifikasi. Instansi daerah lain perlu mereplikasi model tersebut untuk meningkatkan kualitas layanan adminduk.

Kata Kunci: Administrasi kependudukan, inovasi pelayanan, model inovasi, replikasi
PENGARUH IMPLEMENTASI KEBIJAKAN TATA KELOLA DAN MANAJEMEN PEMBIAYAAN TERHADAP PRESTASI KERJA GURU SEKOLAH MENENGAH KEJURUAN NEGERI DI EKS-KEWEDANAAN KANDANGHAUR KABUPATEN INDRAMAYU
Authors: Komara Agus
Published: November 2020

Pasca ditetapkannya Undang-Undang No. 23 tahun 2014 tentang Pemerintah Daerah, mulai tahun 2016 terjadi perubahan yang cukup signifikan mengenai pengalihan kewenangan pengelolaan pendidikan menengah dalam hal ini adalah SMA, MA dan SMK dari Pemerintah Kabupaten/Kota kepada pemerintah Provinsiuntuk selanjutnya dikelola oleh Dinas Pendidikan Provinsi. Bertolak dari masalah tersebut, fokus penelitian ini pada implementasi kebijakan tata kelola dan manajemen pembiayaannya serta pengaruhnya terhadap prestasi kerja guru. Baik parsial maupun ganda. Metode penelitian yang digunakan adalah metode deskriptif dan verifikatif, dengan teknik pengumpulan data menggunakan angket skala Likert, terhadap 57 orang guru sekolah menengah kejuruan (SMK) Negeri di Wilayah Eks-Kewedanaan Kandanghaur Kabupaten Indramayu. Pengolahan hasil penelitian menggunakan teknik analisis regresi. Uji signifikansi menggunakan uji-F. Hasil penelitian menunjukkan bahwa: (1) Implementasi  kebijakan tata kelola berpengaruh positif dan signifikan terhadap terhadap prestasi kerja guru, dengan besaran pengaruh  41,1%, sementara sisanya 58,9 % dipengaruhi oleh variabel lain. (2) Manajemen pembiayaan berpengaruh positif dan signifikan terhadap terhadap prestasi kerja guru, dengan besaran pengaruh  14,6 %, sementara sisanya 85,4 % dipengaruhi oleh variabel lain. (3) Implementasi  kebijakan tata kelola dan manajemen pembiayaan secara simultan berpengaruh positif dan signifikan terhadap terhadap prestasi kerja guru, dengan besaran pengaruh  42 %, sementara sisanya 58 % dipengaruhi oleh variabel lain. Bertolak dari kondisi tersebut, penulis menyarankan: (1) Sesuai hasil penelitian bahwa implementasi kebijakan tata kelola berpengaruh pada prestasi kerja guru, maka guna meningkatkan prestasi kerja guru bisa dilakukan dengan meningkatkan proses implementasi kebijakan tata kelola dengan perbaikan dimensi yang masih lemah yaitu perbaikan pada struktur birokrasi yang dapat dilakukan dengan pelatihan yang berkaitan dengan organisasi dan pendelegasian kewenangan. (2) Manajemen pembiayaan telah berlangsung bagus, tetapi guna lebih meningkatkan prestasi kerja guru dapat dimulai dengan memperbaiki dimensi yang masih lemah pada manajemen pembiayaan. Berdasarkan pembahasan pada bab IV, dimensi manajemen pembiayaan yang dianggap masih lemah adalah pada sisi perencanaan dan penggunaan biaya. Oleh karenanya, disarankan agar diberikan pelatihan tentang budgeting termasuk prosedur penggunaan anggaran.
ANALISIS KONDISI LINGKUNGAN SEKOLAH DAN MOTIVASI BERPRESTASI SERTA DAMPAKNYA TERHADAP PRODUKTIVITAS KERJA GURU
Authors: Warsid Warsid  , Dekawati Ipong , Pujiyati Wresni
Published: November 2020

Salah satu tolak ukur suksesnya pengembangan sekolah adalah produktivitas kerja guru di sekolah tersebut. Oleh karena itu, penelitian ini menelaah faktor yang mempengaruhi produktivitas kerja guru, terutama menyangkut faktor kondisi lingkungan sekolah dan mortivasi berprestasi guru. Fokus penelitian ini adalah untuk mengetahui besaran pengaruh kondisi lingkungan sekolah dan motivasi berprestasi guru baik secara parsial maupun ganda. Metode penelitian yang digunakan adalah metode deskriptif dan verifikatif, dengan teknik pengumpulan data menggunakan angket skala Likert, terhadap 68 orang guru. Pengolahan hasil penelitian menggunakan teknik analisis regresi. Uji signifikansi menggunakan uji-F. Hasil penelitian menunjukkan bahwa: (1) Terdapat pengaruh yang signifikan antara kondisi lingkungan sekolah terhadap produktivitas kerja guru. (2) Terdapat pengaruh yang signifikan antara motivasi berprestasi guru terhadap produktivitas kerja guru. (3) Terdapat pengaruh yang signifikan antara kondisi lingkungan sekolah dan motivasi berprestasi guru secara simultan terhadap produktivitas kerja guru. Terbukti bahwa kondisi lingkungan sekolah berpengaruh signifikan terhadap produktivitas kerja, oleh karena itu dimensi lingkungan sekolah yang masih dianggap lemah segera dikembangkan, melalui harmonisasi pada lingkungan internal yaitu antara sesama guru, antara guru dengan peserta didik dan  antara peserta didik dengan peserta didik lainnya. Guna meningkatkan produktivitas kerja guru melalui motivasi berprestasi disarankan agar guru lebih banyak dilibatkan dalam perencanaan serta diberikan keleluasaan dalam mencari kesempatan untuk merealisasikannya. Hal ini dapat dilakukan dengan pemberian tanggung jawab yang lebih dari biasanya melalui penunjukkan sebagai penitia dalam berbagai kegiatan secara bergiliran, sehingga semua guru dapat mengembangankan potensi dan motivasinya.
A case of multisystem sarcoidosis on 18F-FDG PET/CT
Authors: ERHAMAMCI Seval , RAMADAN Saime , YAŞAR Bülent
Published: November 2020

We present in a 67-year-old woman with multisystem sarcoidosis on 18F-FDG PET/CT
Renal Transplantation Survival Using ANN
Authors: Rajendran Manivasagam , Perumal Vigneshwaran
Published: November 2020

The aim of this paper is to study pre and post-transplant health records of kidney transplanted people and to find the importance of various factors in renal transplantation. Once the importance of these factors are quantified it can be used to predict the survival probability of the graft for given time. The possibility of using Artificial Neural Network (ANN) as a tool to predict the survival probability is discussed. Transplantation is the best option available to increase the life expectancy of the people who are suffering from end stage renal disease all over the world. The present system for organ procurement and management by the hospital and other reputed legal organizations are not sufficient to deal with the situation. The need of the hour is Systematic procedures for collection of organs, networking and sharing information about both pre transplantation and post transplantation levels. Application of scientific techniques and well proven methodologies of other domains like manufacturing and production can be utilized to improve the level of efficiency in organ transplants of our country.
Cyber-Attacks Detection Using Novel IDDMS Framework
Authors: Bhivsen Gadekar Ganesh , N P G Udayabhanu , Jalindar Dange Bapusaheb , K Vengatesan , Kumar Abhishek
Published: November 2020

Security of a data system is a significant property, particularly today when PCs are interconnected by means of the internet. Since no system can be totally secure, the opportune and precise detection of intrusions is essential. Cyber security is the region that manages shielding from cyber terrorism. Cyber-attacks incorporate access control infringement, unapproved intrusions, and disavowal of service just as insider risk. For this reason, IDS were planned. The IDS in the mix with DM can give security to the next level. DM is the way toward presenting inquiries and separating designs, frequently already ambiguous from huge amounts of data utilizing design coordinating or other thinking techniques. This Paper gives the IDDMS (Intrusion Detection with Data Mining system) Framework which is a mix of data mining techniques with the Intrusion detection system, this can be utilized in Cyber-security for accomplishing the next level of service.
A Deep Learning Based System to Predict the Noise (Disturbance) in Audio Files
Authors: P V S M S Kartik , G Jeyakumar
Published: November 2020

Generally, people prefer their audio to be with very good clarity. They want no disturbances during any interaction and while listening audio files. Automated systems to remove disturbances in an audio file to bring good clarity real time audio communications are in high demand. In this paper a deep learning model to detect the noises in a given audio file is proposed and it working principle is explained. The proposed model was trained, first, to predict the places of noise in the audio file by a well-defined training set which consists of set of audio files with the interval of clear audio and noise. After training, the proposed model predicts the area of disturbance (noise) in any given audio file using the integrated techniques of deep learning and audio processing, and the results are reported. The prediction accuracy of the model was found 90.50 %.
Effective Feature Subset Identification Using Adaptive Bee Colony Algorithm
Authors: K Suja , A Rengarajan
Published: November 2020

The irrelevant features, along with redundant features, severely affect the accuracy of the learning machines. Feature subset selection as the process of identifying and removing many irrelevant and redundant features. The overall process of the optimal feature selection method is divided into two main steps, such as, i) preprocessing (ii) Optimal feature selection using clustering and tree generation. At first, preprocessing is done in the input micro array dataset. Then the Possibilistic fuzzy c-means clustering algorithm with optimal minimum spanning tree algorithm is applied on the high dimensional micro array dataset to select the important features. Here the proposed method is optimally select the features with the help of Adaptive artificial bee colony algorithm.
Disease Detection in Tomato Plants Using Deep Learning
Authors: S Marimuthu , J Bhuvana , T T Mirnalinee
Published: November 2020

Agriculture is the backbone of the economy of any country. Productivity of the crops depends on soil quality, proper irrigation and fertilizer, appropriate pesticide. Mostly pesticides were applied without having knowledge about the type of diseases or pests. Type and the quantity of pesticide for any depends on the disease category. If we could identify the appropriate disease, then applying appropriate pesticide will increase the yield of the crop. To address this issue, we propose a method to detect the diseases in tomato plants. We have designed a Convolutional Neural Network architecture that efficiently detects the disease of tomato plant. The system is evaluated with Plant Village benchmark dataset. Results show that our network is detecting the diseases with 90.86% accuracy. We have identified a suitable variant of Convolutional Neural Network that efficiently detects the disease of tomato plant.
The Necessitate of Regulation for Social Media Posting in India
Authors: N Bala Sundara Ganapathy , K Mohana Prasad
Published: November 2020

It has been recently assessed that the quantity of social media clients are generally around two billion; in addition, it is foreseen that this number would altogether ascend in an incentive because of the expanding utilization of PDAs, which thus brings about the expanding utilization of mobile social networks. Developed nations have their own guideline for posting and getting to the substance from/to the social media. Numerous nations didn’t outline any guideline for posting internet based social media substance. This paper dismembers about the peril components of social media and the proposed guideline of the government of India for Social Media posting. The purpose of this investigation is to make the attention about the social media issues and the need of immediate and effective regulation against the publication and proliferation of sexually abusive web content like kid erotic entertainment, assault and assault recordings and frightful material through Internet.
A Review on Stroke Lesion Analysis in MRI Datasets
Authors: Irish Sylvia , J Dhalia Sweetlin
Published: November 2020

Stroke is one of the major causes of disability in the world. The various disabilities due to stroke includes intellectual functioning damage locomotory dysfunction, visual and hearing impairment, disfigurement etc., This occurs due to occlusion or inhibition of blood supply to the brain which is known as Ischemic stroke, whereas rupturing of blood vessels to the brain causes hemorrhagic stroke. Imaging techniques such as CT and MRI have played a huge role in the visualization of stroke lesions. Segmentation of the salvageable tissue and its outcome of how it affects a person’s lifestyle is the key focus of research as automated model is highly recommended to reduce the time and increase the accuracy in the prediction of stroke lesion in comparison to manual intervention.
Minimizing Delay and Maximizing Network Lifetime by Power-Aware Energy Efficient Routing [PAEER] Mechanism in Wireless Sensor Networks
Authors: S Ramprakash , B Vijayakumari , P Subathra
Published: November 2020

We propose an efficient routing mechanism called PAEER (Power-Aware Energy Efficient Routing) for meeting Network Lifetime Maximization and energy efficiency in the Wireless Sensor Networks(WSN). The different contributions of the PAEER approach are following (a) Multisink node approach which can lead to increase the nodes network lifetime and event detection mechanism that meets reliability requirement of the WSN (b) Using PAEER mechanism sends the data to sink node by covering multi-path routes to aggregate the nodes data. Thus energy consumption of the WSN can be reduced maximum level therefore network lifetime increased. This can be proved both theoretical and experiment solutions can be better when compared to other solutions. By using Network Simulator-3 (NS-3) testbed the results show the better results for the all Quality of Service parameters (QoS) like Throughput, Network Lifetime, Power Consumption, etc.
An Inclusive Survey on Various Adaptive Beam Forming Algorithm for 5G Communications Systems
Authors: K R Kaviya , S Deepa
Published: November 2020

There are several existing wireless system in 5G technology, originating interference in same frequency band and degenerate the concert of received signal. Antenna System comprise of different Beam forming methods in which direction of required signal is generated by the beam and nulls and the voids are set in the direction of unwanted signal (Interference). The survey of different blind and non-blind beam forming algorithms are discussed using smart antenna and phased array. It involves Least Mean Square (LMS), Normalized Least Mean Square (NLMS), Recursive Least Square (RLS), Sample Matrix Inversion(SMI), Linear Constrained Minimum Variance (LCMV), Constant Modulus (CMA), Decision feedback equalization based LMS (DFE-LMS) are considered. These algorithms are outlined to be claimed in 5G network to provide good quality, capacity and dealing with coincidence of signals and interference.
Detection of Pneumonia from X-Ray Images Using Convolutional Neural Networks
Authors: P Saranya , TanmayThapliyal  , AvibhashBajpai
Published: November 2020

Pneumonia is an infection which is caused by bacteria or viruses. Early diagnosis is critical to treat the disease successfully without delaying the treatment much. In most of the cases and as per the usual process the patient with pneumonia-like symptoms can be dragonized via frontal and lateral chest x-ray images, which are then seen over by the naked eye by doctors or radiologists. The diagnoses can be misleading and confusing as the appearance of the disease can be unclear in X-ray images and can put the doctor in a dilemma, as the features may not be visible clearly via naked eyes. That is why computer-aided diagnosis is generally required to guide clinicians. The model is based upon the convolutional neural network architecture, wherein pre-processed images are fed to the developed network layers and trained to provide us results with high accuracy of 94.3%, a precision rate of 93.18%, recall of 98.20% and an F1 score of 95.63%. The objective of the work is to design a model that can provide fast and accurate analysis which not only may save diagnosis cost, but also provide invaluable time for the doctors to begin the treatment if the disease is detected early.
Anomaly Based Sensor Nodes with IoT for Environment Sustainability
Authors: J Sathya Priya , S L Bharathi , A R Sathyabama
Published: November 2020

The proposed works implements a prototype of detecting harmful gases in a given environment, along with air and water quality monitoring. This device is capable of detecting temperature and LPG leakage in home environment, monitoring water quality in a given area along with warm body detection and methane concentration inside drains. The temperature and LPG leakage is detected with the help of temperature and MQ-6 sensors, the water quality is monitored with the help of pH and turbidity sensors. The human presence inside the drain is detected with the help of PIR sensor and methane concentration with the help of MQ-4 sensor. The sensor nodes are based on wifi enabled Arduino microcontroller, that receives data from the sensors and converts it into digital data that are transmitted to the webpage. The main concern of this paper is the real time monitoring of various parameters by implementing low-cost sensors that are useful for both home and the society.
Analysis of Various Textural Descriptors for Ovarian Cyst Classification
Authors: S Sheela , M Sumathi , S Sumathy , S Thirumoorthy , E Subalakshmi
Published: November 2020

Ovarian cyst is one of the main causes of infertility. Ovarian cancers are also caused by the ovarian cyst that grows in the ovary. An ovarian cyst can be benign (non-cancerous) or malignant (cancerous). If the cyst is not diagnosed and treated at the earliest, the benign cyst may turn into malignant and can be fatal. Various image processing techniques are used to assist the clinicians to characterize the ovarian cyst using the textural descriptor. This paper reviews several textural descriptors for feature extraction like Local Binary Pattern (LBP), Local Directional Pattern (LDP) and Local Optimal Oriented Pattern (LOOP). Finally, extracted features are applied to SVM, KNN and Ensemble classifiers to compare the performance of the textural descriptors.
Analysis of Various Techniques for Ovarian Cyst Segmentation
Authors: S Sheela , V Subashini , Sumathi M. , G Roopsree , B Soundhar , R Ramya
Published: November 2020

In the female reproductive system, ovary plays a major role. The diseases caused by ovaries are ovarian cysts, ovarian cancer, menstrual cycle disorder and polycystic ovarian syndrome(PCOS). PCOS in women mainly causes infertility. The method of analyzing a polycystic ovarian image varies with every individual patient and a great deal for the image analyst to segment the cyst. This paper reviews several segmentation algorithms like Level set algorithm, K-means clustering and Adaptive thresholding segments the ovarian cyst from the ultrasound images exactly. The four parameters such as accuracy, jaccard coefficient, precision, and sensitivity are used for the evaluation of segmentation processes.
Disease Detection in Birds and Animals Using Image Processing
Authors: R Venkatesh , S Rajakumar
Published: November 2020

In this research, a method is proposed and implemented for detecting and classifying the infected chicken. Dominant factors have been analyzed the health of the chicken and production of egg and many other conditions which will be beneficial in the living environment. For each processing stage, different algorithms have been implemented to estimate the infection produced in the chicken. The proposed algorithms are exploited to perform in a faster manner. The experimental results have been shown using MATLAB.
Classification of Unbalanced Data Based on RSM and Binomial Distribution
Authors: Li Rong , Zhou Wei-Bai
Published: November 2020

In the case of extremely unbalanced data, the results of the traditional classification algorithm are very unbalanced, and most samples are often divided into the categories of majority samples, so the accuracy of judgment of the minority classes will be reduced. In this paper, we propose a classification algorithm for unbalanced data based on RSM and binomial undersampling. We use RSM’s random part features rather than all each classifier to make each training classifier reduce the dimensions, and dimension reduction makes relatively minority class samples indirectly lift. Using the above characteristics of the RSM to reduce dimension can solve the problem that unbalanced data classification in the minority class samples is too little, and it can also find the important attribute of variables to make the model have the ability of explanation. Experiments show that our algorithm has high classification accuracy and model interpretation ability when classifying unbalanced data.
Origin and Evolution of Conceptual Differences Between Two Measurement Theories
Authors: Shi Huisheng , Ye Xiaoming , Xing Cheng , Ding Shijun
Published: November 2020

In several published literatures, some new measurement concepts have been proposed to reinterpret measurement theory, which leads to a new interpretation method of measurement theory. By directly comparing the measurement concept differences between the new theory and the traditional theory, this paper reveals that the root of these differences is due to the different understanding of the mathematical concept of random variable, and clarifies the evolution process of other conceptual differences. Also, by reviewing the mathematical concept, it points out that the traditional theory has been gone astray, and the concept of error classification is actually the product of going astray, while the new concept theory should get active attention and research.
Customer Churn Prediction Based on HMM in Telecommunication Industry
Authors: Zhu Huisheng , Yu Bin
Published: November 2020

The rapid development of technology and increasing numbers of customers have saturated the communication market. Communication operators must give focused attention to the problem of customer churn. Analyzing the customer’s communication behavior and building a prediction model of customer churn can provide the advance evidence for communication operators to minimize churn. This paper describes how to design a HMM to predict customer churn based on communication data. First, we oversample churners to increase the number of positive samples and establish the relative balance of positive and negative samples. Second, the continuous numerical attributes that affect communication customer churn are relatively discretized and their monthly values are converted into monthly change tendencies. Next, we select the communication features by calculating the information gains and information gain rates of all communication attributes. We then construct and optimize a prediction model of customer churn based on HMM. Finally, we test and evaluate the model by using a Spark cluster and the communication data set of Taizhou Branch of China Telecom. Experimental evaluation provides proof that our prediction model is exceptionally reliable.