bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efektifitas Penjatuhan Sanksi Pidana Terhadap Kejahatan Tindak Pidana Korupsi
Authors: Sahardian Ikbal , Thalib Hambali , Badaru Baharuddin 
Published: February 2021

Penelitin ini di latar belakangan oleh fenomena bahwa efektif tidaknya penjatuhan sanksi tindak pidana korupsi dikabupaten jayapura papua kebanyakan korupsi terjadi pada lingkup pemerintah maupun swasta tetapi kebanyakan juga korupsi yang terjadi di bidang pertanian terutama dampak negative pada sector perekonomian serta kehidupan pada petani sehingga menghambat kemajuan dan pertumbuhan disektor pertanian. Penelitian ini dilaksakan di kabupaten jayapura papua pada kantor polres jayapura, Kejaksaan Negeri Jayapura dan Pengadilan Negeri jayapura dengan alas an bahwa instansi yang terjadi di kabupaten jayapura selama tiga tahun terakhir. Hasil penelitian ini menukkan bahwa dalam waktu tiga tahun terakhir ini. Tingkat efektifitas penjatuhan sanksi tindak pidana korupsi mengalami peningkatan. Hal ini di sebabkan karena kekurangna kepekaan apparat penegak hokum dalam hal mencegah serta mengurangi terjadinya tindak pidana korupsi disamping itu pula kesadaran hukum dan oknum pemerintah sendiri yang melakukan tindak pidana korupsi yang seharusnya ia mengetahui hukum sebagai unsur pemerintah tetapi malah ia sendiri yang melakukan perbuatan korupsi. Padahal yang melakukan korupsi diancam dengan sanksi penjatuhan yang berat.
This study was in the background by the phenomenon that the effective absence of the rationing of corruption criminal sanctions in the district Jayapura Papua most corruption occurs in the scope of the government and private but most of the corruption in the field of agriculture, especially negative impact on the economic sector and life on the farmers, thereby inhibiting progress and growth of agricultural disetor. This research was established in Jayapura Papua District at the Jayapura Police Office, Jayapura state Attorney and the District Court of Jayapura with the base that the agency occurred in Jayapura district for the last three years. The results of this study have been inserted in the last three years. The level of effectiveness of criminal offence sanctions has increased. This has been caused by the Kekurangna sensitivity apparat the law enforcement in preventing and reducing the corruption of criminal acts besides the legal awareness and the Government itself who committed criminal acts of corruption that he should know the law as an element of the government but instead he himself doing corruption. In fact, corruption is threatened with heavy allotment sanctions.
Problematika Proses Penahanan Dalam Sistem Peradilan Pidana
Authors: Hasriadi K M , Djanggih Hardianto 
Published: February 2021

Penelitian ini adalah untuk mengetahui dan menganalisis tentang proses penahanan dalam sistem peradilan pidana dan untuk mengetahui dan menganalisis faktor-faktor yang mempengaruhi tentang proses penahanan dalam sistem peradilan pidana. Metode penelitian, kalau dilihat dari tipe penelitiannya maka termasuk penelitian hukum empiris karena penekanannya adalah menelaah fenomena hukum yang berkaitan dengan proses penahanan dalam sistem peradilan pidana. Sehingga data yang dibutuhkan dalam peneltian ini adalah data primer dan data sekunder. Hasil penelitian menunjukkan bahwa proses penahanan dalam sistem peradilan pidana kurang efektif disebabkan karena didalam Pasal 31 KUHAP masih memberikan peluang untuk melakukan penangguhan penahanan bagi tersangka. Dan faktor-faktor yang mempengaruhi tentang proses penahanan dalam sistem peradilan pidana adalah faktor substansi hukum, sgtruktur hukum dan budaya hukum. Direkomendasikan bahwa perlu adanya suatu aturan yang jelas tentang penangguhan penahanan karena dalam Pasal 31 KUHAP sebenarnya tidak memberikan peluang untuk melakukan penangguhan penahanan tetapi kalau dikaitkan dengan Pasal 29 KUHAP seakan ada peluang untuk melakukan penangguhan penahanan. Dan jangka waktu penahanan terlalu lama pada tiap-tiap tahap pemeriksaan, sehingga perlu adanya suatu aturan baru yang mengatur tentang penahanan.
This research is to know and analyze about the containment process in the criminal justice system and to know and analyze the factors that affect the containment process in the criminal justice system. The research method, when viewed from the type of research, includes empirical legal studies because the emphasis is on studying legal phenomena related to the detention process in the criminal justice system.sSo the data needed in this study are primary data and secondary data. The results showed that the detention process in the criminal justice system was less effective because in article 31, KUHAP still gave the opportunity to suspend the detention of the suspect. And the factors that affect the detention process in the criminal justice system are the legal substance factors, the legal and cultural sgtructure. It is recommended that there is a clear rule about the suspension of detention because in article 31 the criminal CODE does not actually provide an opportunity to suspend the detention but the Kmalau is associated with article 29 of the criminal CODE as if there is an opportunity to suspend the detention. And the period of detention is too long in each phase of the inspection, so there needs to be a new rule governing the detention of.
Perlindungan Hukum Konsumen Pada Perjanjian Baku (Standar Contract) PT. Telkomsel Terhadap Penggunaan Kartu Pasca Bayar (Halo Kick)
Authors: Yunus Ahyuni , Bilondatu Agustina Ali 
Published: February 2021

Penelitian ini bertujuan, pertama Bentuk perlindungan hukum konsumen pada perjanjian baku (Standart Contract) PT Telkomsel Terhadap Penggunaan Kartu Pasca Bayar (Halo Kick), kedua Upaya hukum konsumen Konsumen tindakan sepihak yang dilakukan oleh pihak Telkomsel. Metode penelitian yang digunakan adalah metode penelitian hukum normatif. Hasil penelitian menunjukkan bahwa, pertama, Perlindungan hukum terhadap pekerja dimaksudkan untuk menjamin hak-hak dasar dan menjamin kesamaan kesempatan serta perlakuan tanpa diskriminasi atas dasar apapun untuk mewujudkan kesejahteraan pekerja beserta keluarganya. Perlindungan pekerja tersebut hanya dapat tercapai jika adanya peran serta Negara secara aktif dalam menjaga stabilitas iklim industrialisasi dengan perindungan terhadap pekerja, atau dengan kata lain ditengah gesekan perubahan zaman dan menggeliatnya pertumbuhan ekonomi maka peran serta Negara merupakan keniscayaan.
This study aims, firstly, the form of consumer legal protection in the PT Telkomsel standard contract against the use of postpaid cards (Halo Kick), secondly the consumer's legal efforts for unilateral actions taken by Telkomsel. The research method used is normative legal research method. The results show that, first, legal protection for workers is intended to guarantee basic rights and guarantee equal opportunity and treatment without discrimination on any basis to realize the welfare of workers and their families. Protection of workers can only be achieved if there is an active role of the State in maintaining the stability of the industrialization climate with protection of workers, or in other words, amidst the friction of changing times and stretching economic growth, the participation of the State is a necessity.
Penyelesaian Sengketa Penertiban Pemakaian Tenaga Listrik (PPTL) Pada PLN Persero Unit Pelanggan Daya
Authors: Hidayat Muhammad , Rahman Sufirman , Purnomo Sri Lestari 
Published: February 2021

Tujuan penelitian: (1) Untuk mengetahui dan menganalisis serta menjelaskan penyelesaian sengketa penertiban pemakaian tenaga listrik (PPTL) antara PT. PLN (Persero) dengan Pelanggan di kota Makassar; (2) Untuk mengetahui dan menganalisis serta menjelaskan faktor-faktor yang mempengaruhi terjadinya sengketa penertiban pemakaian tenaga listrik (PPTL) antara PT. PLN (Persero) dengan Pelanggan. Metode penelitian adalah penelitian hukum empiris. Hasil penelitian: (1) Penyelesaian sengketa penertiban pemakaian tenaga listrik (PPTL) antara PT. PLN (Persero) dengan Pelanggan di kota Makassar kurang efektif; (2) Faktor yang mempengaruhi terjadinya sengketa penertiban pemakaian tenaga listrik (PPTL) antara PT. PLN (Persero) dengan Pelanggan adalah regulasi/substansi hukum, struktur hukum, sarana, budaya hukum masyarakat dan ekonomi masyarakat. Faktor yang sangat berpengaruh adalah budaya hukum masyarakat dan ekonomi masyarakat.
The aims are: (1) To review and analyze and explain the resolution of disputes the controlling the use of electric power (PPTL) between PT.PLN to its touch with the customers in the city of makassar; (2) To review and analyze and explain factors that affects the occurrence of a dispute over the controlling the use of electric power (PPTL) between PT.PLN with customers. The approach research is empirical legal research. The result of the research: (1) Resolution of disputes the controlling the use of electric power (PPTL) between PT. PLN with customers in the city of makassar said and done; (2) Factors affect the dispute the use of electricity (PPTL). between PT. PLN with customer is or substance, legal regulations, legal structure, facilities the laws of society and culture of the community economic.The most powerful is a culture of the community economic and community law
Faktor Penyebab Terjadinya Perceraian Rumah Tangga AKibat Perselingkuhan
Authors: Nugraha Afgan , Barinong Amiruddin , Zainuddin Zainuddin 
Published: February 2021

Tujuan dari penelitian ini: a) Untuk mengetahui dan menganalisa faktor-faktor yang melatar belakangi perselingkuhan dalam rumah tangga sehingga memicu terjadinya perceraian. Penelitian ini termasuk (Case Study) dan penelitian ini menggunakan tipe penelitian hukum empirik Hasil penelitian menunjukkan bahwa a) faktor yang melatarbelakangi keterlibatan perselingkuhan adalah faktor ekonomi, kurangnya waktu untuk keluarga, perbedaan usia, kurang komunikasi, sosial media, maraknya reuni, adanya kesempatan dan rendahnya akhlak. Sehingga Perlu ada kesadaran pada instansi pemerintahan yang berkaitan dengan pendidikan agar dimasukkan suatu mata pelajaran tentang kehidupan perkawinan dan arti perkawinan sesungguhnya agar setiap siswa dapat mengatahui pandangan tentang perkawinan dan dapat menyikapi masalah-masalah dalam kehidupan rumah tangga sejak dini.
The purpose of this study: a) To find out and analyze the factors behind the affair in the household so that it triggers divorce. This study included (Case Study) and this study uses an empirical legal research type. The results showed that a) the factors behind the involvement of adultery were economic factors, lack of time for family, age difference, lack of communication, social media, reunion revival, opportunities and lack of morals. There is a need for assistance with government planning related to education to be included in lessons about marital life and the meaning of marriage so that each student can know the views about marriage and can address problems in domestic life early on.
A Blind Blur Detection Method for Electro-optic (EO) Images
Authors: Bower Greg 
Published: February 2021

Blurring in Electro-Optic (EO) images is a significant issue that can arise due to the payload and platform operations. It would be advantageous for unmanned platforms to determine if significant blurring is present within captured images before the images are observed and the collection sequence has ended. In this way, the degradation can be identified and remedied in operation in real-time. In this paper, we demonstrate that a statistical algorithm called Symbolic Analysis (SA) is suitable for detecting blurring in the output images of EO systems. The SA algorithm adapted from previous work is described and demonstrated on an example image with artificial Gaussian-based blurring induced.
A Comprehensive Analysis of the Performance of Gear Fault Detection Algorithms
Authors: Bechhoefer Eric , Butterworth Brent 
Published: February 2021

Modern gear fault detection analysis began with algorithms based on the time synchronous average. Over the course of decades, many gear analyses have been proposed, but with no evidence that the analysis was significantly more powerful in terms of fault detection than existing algorithms. This study focuses on a comprehensive comparison of gear fault detection algorithms to evaluate their performance. Using a large, statistically significant set of data from three nominal machines and a damaged machine, the CI responses of 88 different analysis are compared in terms of their statistical significance to detect a cracked tooth. The comparison includes residual, energy operator (and its variants), the narrowband analysis (with a comparison of bandwidth requirements), the amplitude and frequency modulation analysis, an analysis of variance of the "factor” analysis: crest, shape, impulse, and margin, and other standard gear fault CIs. Further, the effect of CI selection in the establishment of gear component health is evaluated, where given a set of CIs, a gear health indicator is built, showing that CIs with high statistically separability and low correlation have improved fault detection power. This is validated on a third, dissimilar gear fault propagation test.
Accurate Estimation of Battery SOH and RUL Based on a Progressive LSTM with a Time Compensated Entropy Index
Authors: Bak Taejun , Lee Sukhan 
Published: February 2021

The accurate estimation of the State of Health (SOH) and Remaining Useful Life (RUL) has been a subject of keen interest due to its impact on safety and condition-based maintenance services. A number of approaches have been proposed to tackle this problem based either on a model-driven or on a data-driven framework. Due to the electro-chemical complexity involved in battery aging, they are yet to achieve the accuracy required, especially, for real-world applications. This is because of the difficulty either in identifying the time-varying nature of model parameters and in collecting the real-world training dataset from widely varying modes of battery usage.
In this paper, we propose a method of estimating SOH and RUL simultaneously in such a way as to contribute to its real-world applicability. First, noticing that battery aging causes the time sequence of charging and discharging voltage and current in a cycle to be shortened and dispersed, we define an aging index, referred to here as the time compensated entropy, for SOH and RUL. Second, for LSTM-based RUL prediction, we optimize the number of SOH input and the RUL prediction sequences for the minimum prediction error associated with a sequence of cycles. Third, we adopt a progressive framework of LSTMs such that whatever learned from the prior predictions are transferred to the subsequent prediction, starting with learned SOH. For experimental verification, we train the proposed progressive LSTM network based on CALCE datasets and apply to various cases of charging and discharging cycles. With SOH estimated online, we achieve less than 10 cycles of accuracy in RUL prediction, moving closer to real-world applicability.
Best Practices Framework for Improving Maintenance Data Quality to Enable Asset Performance Analytics
Authors: Lukens Sarah , Naik Manjish , Saetia Kittipong , Hu Xiaohui 
Published: February 2021

Field maintenance data is often captured manually and is prone to have incomplete and inaccurate information in the structured fields. However, unstructured fields captured through work order planning, scheduling, and execution contains a wealth of historical information about asset performance, failure patterns, and maintenance strategies. The prevalent data quality issues in maintenance data need to be understood and processed in order to extract actionable intelligence. This paper describes a best practices framework for measuring and improving data quality, developed through years of research and working with 120+ process and manufacturing organizations. The framework enables evaluating and executing analytics by identifying strengths in the data. It determines where and how asset performance measures such as benchmarking metrics, reliability measures, and bad actor identification can be evaluated with confidence. Missing or inconsistent information can be extracted from the unstructured fields using natural language processing (NLP) techniques to bridge gaps in the analysis. While the NLP algorithms make historical data usable for some analytics, the best practices identify improvements in the work process of capturing data, thereby improving future quality. A feedback on data quality indicators completes the loop to sustain improvements.
Advanced Fault-tolerant Control Strategy of Wind Turbine Based on Squirrel Cage Induction Generator with Rotor Bar Defects
Authors: Roubah Boubakeur , Toubakh Houari , Sayed-Mouchaweh Moamar 
Published: February 2021

Several research works in Wind Energy Conversion Systems (WECS) based on Squirrel Cage Induction Generator (SCIG) are developed for isolated site applications. Where, WECS are usually controlled by the Maximum Power Point Trucking (MPPT) algorithm in order to extract the maximum power from wind with constant operating point of SCIG. However, this WECS based on SCIG generator suffers from the problem of breaking rotor bars, therefore a failure in rotor bars is particularly a challenging task because: 1) it can change the operating point generated by MPPT algorithm, 2) increase mechanical vibrations, 3) affect the operation of gearbox, 4) inject a harmonic current in the grid. Therefore, Fault Tolerant Control (FTC) scheme is necessary to allow an optimum energy production, to reduce the maintenance costs and to increase the WECS availability. In this work, a new fault diagnosis approach based on frequency analysis of stator currents is used to detect the failure in bars of SCIG, then FTC algorithm is developed to adjust the pitch angle in max wind speed zone by determining a new operating point according to the wind speed, which leads to extend the lifetime of WECS. Simulation results using MATLAB SIMULINK showed a nominal current in healthy rotor bars and the lifetime of WECS was increased.
Hybrid PSO-SVM Based Method for Degradation Process Prediction of Reciprocating Seal
Authors: Ramachandran Madhumitha , Keegan Jon , Siddique Zahed 
Published: February 2021

Reciprocating machines such as piston pumps, compressors and internal combustion engines are widely used in several manufacturing industries including automobile, aircraft, paper, oil and gas, etc. Reciprocating seal located directly on the rod/piston of a reciprocating equipment is used for preventing leakage and reducing wear between two parts that are in relative motion. Seals failure is one of the foremost causes of breakdown of reciprocating machinery and such a failure can be catastrophic, resulting in costly downtime and large expenses. Assessment of reciprocating seal is extremely important in the manufacturing industry to avoid fatal breakdown of reciprocating equipment and machines. Prediction of time series using predictive maintenance practices and tools to estimate the evolution of the future conditions of the system is of great interest to the operators for taking timely and appropriate maintenance decisions. In this paper, we have built and trained a hybrid PSO-SVM model to predict the reciprocating seal degradation. Particle swarm optimization is used to optimize the penalty factor and kernel parameter of SVM model. Controlled experiments are designed and performed, and data collected from a dedicated experimental set-up is used to validate the proposed approach.
Data-Driven Detection of Anomalies and Cascading Failures in Traffic Networks
Authors: Basak Sanchita , Ayman Afiya , Laszka Aron , Dubey Abhishek , Leao Bruno 
Published: February 2021

Traffic networks are one of the most critical infrastructures for any community. The increasing integration of smart and connected sensors in traffic networks provides researchers with unique opportunities to study the dynamics of this critical community infrastructure. Our focus in this paper is on the failure dynamics of traffic networks. We are specifically interested in analyzing the cascade effects of traffic congestions caused by physical incidents, focusing on developing mechanisms to isolate and identify the source of a congestion. To analyze failure propagation, it is crucial to develop (a) monitors that can identify an anomaly and (b) a model to capture the dynamics of anomaly propagation. In this paper, we use real traffic data from Nashville, TN to demonstrate a novel anomaly detector and a Timed Failure Propagation Graph based diagnostics mechanism. Our novelty lies in the ability to capture the the spatial information and the interconnections of the traffic network as well as the use of recurrent neural network architectures to learn and predict the operation of a graph edge as a function of its immediate peers, including both incoming and outgoing branches. To study physical traffic incidents, we augment the real data with simulated data generated using SUMO, a microscopic traffic simulator. Our results show that we are able to build LSTM-based traffic-speed predictors with an average loss of 6.55 × 10^−4 compared to Gaussian Process Regression based predictors with an average loss of 1.78 × 10^−2. We are also able to detect anomalies with high precision and recall, resulting in an AUC of 0.8507 for the precision-recall curve. Finally, formulating the cascade propagation problem as a Timed Failure Propagation Graph, we are able to identify the source of a failure accurately.
Noisy Multipath Parallel Hybrid Model for Remaining Useful Life Estimation (NMPM)
Authors: AlDulaimi Ali , Mohammadi Arash , Asif Amir 
Published: February 2021

The parallel hybrid models of different deep neural networks architectures are the most promising approaches for remaining useful life (RUL) estimation. In light of that, this paper introduces for the first time in the literature a new parallel hybrid deep neural network (DNN) solution for RUL estimation, named as the Noisy Multipath Parallel Hybrid Model for Remaining Useful Life Estimation (NMPM). The proposed framework comprises of three parallel paths, the first one utilizes a noisy Bidirectional Long-short term memory (BLSTM) that used for extracting temporal features and learning the dependencies of sequence data in two directions, forward and backward, which can benefit completely from the input data. While the second parallel path employs noisy multilayer perceptron (MLP) that consists of three layers to extract different class of features. The third parallel path utilizes noisy convolutional neural networks (CNN) to extract another class of features. The concatenated output of the previous parallel paths is then fed into a noisy fusion center (NFC) to predict the RLU. The NMPM has been trained based on a noisy training to enhance the generalization behavior, as well as strengthen the model accuracy and robustness. The NMPM framework is tested and evaluated by using CMAPSS dataset provided by NASA.