scholarly journals PENERAPAN DATA MINING DALAM MENGELOMPOKAN PRODUKSI JAGUNG MENURUT PROVINSI MENGGUNAKAN ALGORITMA K-MEANS

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Nanda Erlangga ◽  
Solikhun Solikhun ◽  
Irawan Irawan
Keyword(s):  
Data Mining ◽  
Clustering Algorithm ◽  
Rapid Development ◽  
Domestic Market ◽  
Corn Production ◽  
Low Level ◽  
High Level ◽  
Level Cluster ◽  
Central Statistics

Corn needs are currently experiencing a fairly rapid development can be seen in terms of the domestic market, here researchers want to increase the productivity and quality of corn production. The data that will be used is the data from the Central Statistics Agency. The method in this study is the K-means clustering algorithm and the application used is Rapidminer which will be grouped into 2 clustering, namely high and low. The results of this study are 2 high level cluster provinces, 32 low level cluster provincesKeywords: Corn, Data mining, K-means Clustering c

Teknik Data Mining Dalam Clustering Produksi Susu Segar Di Indonesia Dengan Algoritma K-Means

2019 ◽  
Vol 1 (1) ◽  
pp. 31-39
Author(s):  
Ilham Safitra Damanik ◽  
Sundari Retno Andani ◽  
Dedi Sehendro
Keyword(s):  
Data Mining ◽  
Milk Production ◽  
Clustering Algorithm ◽  
Clustering Method ◽  
Data Mining Techniques ◽  
Low Level ◽  
Fresh Milk ◽  
Nutritional Needs ◽  
High Level ◽  
Level Cluster

Milk is an important intake to meet nutritional needs. Both consumed by children, and adults. Indonesia has many producers of fresh milk, but it is not sufficient for national milk needs. Data mining is a science in the field of computers that is widely used in research. one of the data mining techniques is Clustering. Clustering is a method by grouping data. The Clustering method will be more optimal if you use a lot of data. Data to be used are provincial data in Indonesia from 2000 to 2017 obtained from the Central Statistics Agency. The results of this study are in Clusters based on 2 milk-producing groups, namely high-dairy producers and low-milk producing regions. From 27 data on fresh milk production in Indonesia, two high-level provinces can be obtained, namely: West Java and East Java. And 25 others were added in 7 provinces which did not follow the calculation of the K-Means Clustering Algorithm, including in the low level cluster.

scholarly journals Penerapan Rapidminer Pada Data Mining Klastering (Kasus: Distribusi Persentase Rumah Tangga Menurut Kabupaten/Kota Dan Bahan Bakar Untuk Memasak)

2020 ◽  
Vol 1 (2) ◽  
pp. 52-58
Author(s):  
Ismi Azhami ◽  
Rahmi Fauziah
Keyword(s):  
Data Mining ◽  
Daily Life ◽  
Energy Sources ◽  
Cooking Fuel ◽  
Low Level ◽  
The North ◽  
The Government ◽  
High Level ◽  
North Sumatra ◽  
Central Statistics

Fuel is any material that can be converted into energy. For example in daily life humans often use energy sources as fuel for cooking including Gas/LPG, Electricity, Kerosene, Charcoal/Briquettes, Wood and others. The purpose of this study is to classify the distribution of the percentage of fuel used in each district/city in Northern Sumatra. This study discusses the analysis of the K-Means method in the case of the distribution of household percentages by district/city and cooking fuel in North Sumatra through the North Sumatra Central Statistics Agency website. The data is processed into 2 clusters namely high level (C1) and low-level clusters (C2). Thus obtained from 34 districts/cities in North Sumatra 23 regions are grouped in high-level clusters (C1) and 10 regions are grouped in low-level clusters (C2).This needs to be done so that it becomes input in the form of information to the government to find out villages that still have low understanding and have not been fulfilled in a district/city in the Province of North Sumatra.

scholarly journals Mobile Networks and Internet of Things Infrastructures to Characterize Smart Human Mobility

Smart Cities ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 894-918
Author(s):  
Luís Rosa ◽  
Fábio Silva ◽  
Cesar Analide
Keyword(s):  
Internet Of Things ◽  
Mobile Networks ◽  
Smart Cities ◽  
Human Mobility ◽  
Rapid Development ◽  
Disruptive Technology ◽  
New Paradigm ◽  
Design And Optimization ◽  
High Level

The evolution of Mobile Networks and Internet of Things (IoT) architectures allows one to rethink the way smart cities infrastructures are designed and managed, and solve a number of problems in terms of human mobility. The territories that adopt the sensoring era can take advantage of this disruptive technology to improve the quality of mobility of their citizens and the rationalization of their resources. However, with this rapid development of smart terminals and infrastructures, as well as the proliferation of diversified applications, even current networks may not be able to completely meet quickly rising human mobility demands. Thus, they are facing many challenges and to cope with these challenges, different standards and projects have been proposed so far. Accordingly, Artificial Intelligence (AI) has been utilized as a new paradigm for the design and optimization of mobile networks with a high level of intelligence. The objective of this work is to identify and discuss the challenges of mobile networks, alongside IoT and AI, to characterize smart human mobility and to discuss some workable solutions to these challenges. Finally, based on this discussion, we propose paths for future smart human mobility researches.

Morphological traits of the development of the skin and wool cover in sheep of Prikatunsky meat and wool type

2021 ◽  
pp. 60-68
Author(s):  
I. I. Dmitrik ◽  
G. V. Zavgorodnyaya ◽  
M. I. Pavlova ◽  
N. A. Podkorytov
Keyword(s):  
Physical Properties ◽  
Morphological Traits ◽  
Age Groups ◽  
Body Side ◽  
Low Level ◽  
Research Material ◽  
High Level ◽  
Significant Factors

A large number of works are devoted to the development of the skin and hair cover of sheep, depending on their breed affiliation, age, feeding conditions and housing. The authors point out that along with other conditions the quality of wool and wool clip is greatly influenced by the conditions of the feeding of animals. A high level of feeding increases the wool clip and improves the quality of the wool and vice versa a low level reduces, causes thinning and worsens other physical properties of the wool. As is known, one of the significant factors that determine the increase in wool clip is the size of the animal and, consequently, the total area of the skin. The purpose of the research was to investigate the morphological traits of the development of the skin and wool cover in sheep of Prikatunsky meat and wool type. The research material was wool samples from four topographic areas of the animal’s body (side/thigh/back/belly) and skin (side) of different sex and age groups, selected from the animals of the studied groups. In the course of research, the quality of wool and indicators of the histostructure of the skin of Prikatunsky meat and wool type of sheep have been investigated. In terms of thick-haired of wool, replacement rams and gimbers of Prikatunsky meat and wool type of sheep were superior by 4,82 pcs. per mm² or 19,0 % and 4,41 pcs. per mm² or 15,8 % of adult animals, respectively. Balance secondary follicles/primary follicles in young animals were higher by 10,3 and 17,3 % compared to breeding rams and ewes. The wool of the replacement young animals was thinner by 7,28 and 4,78 microns and they were more thick-haired. The obtained data will be used in the mating campaign when mating program rams in order to improve the sheep of Prikatunsky meat and wool type.

scholarly journals A Comparative Study to Assess the Quality of Life and Stress among Orphan and Non-orphan Children in Selected Areas of Bagalkot

2020 ◽  
Vol 11 (04) ◽  
pp. 19-25
Author(s):  
Santosh B Sajjan ◽  
Keyword(s):  
Quality Of Life ◽  
High Stress ◽  
Poor Quality ◽  
Demographic Variables ◽  
Self Report ◽  
Stress Scale ◽  
Low Level ◽  
High Level ◽  
Moderate Stress

Introduction: The word orphan comes from the Greek word ‘Orfanos’ and refers to a child permanently bereaved of or abandoned by his or her parents. Methods: A non-experimental descriptive comparative design has been adopted for the present study. The sample of the present study comprises orphan children residing in an orphanage and non-orphan children residing in selected areas of Bagalkot. The sample comprised 30 orphans and 30 non-orphans aged between 10 and 16 years. The data were collected by using self-report, structured closed-ended questionnaires for socio-demographic variables of children, self-administered WHO Quality of life BREF scale, and PSS stress scale. The data obtained were analysed with the help of descriptive and inferential statistics. Result: Findings related to the comparison between the level of stress among the orphan and non-orphan children revealed that majority of orphan children (76.66%) had about moderate stress, 23.33% of the orphan children had high stress, and none of the children had a low level of stress, whereas among non-orphan children, majority (90%) had moderate stress, 10% had low level stress, and none of them had high level stress. The findings related to the comparison of levels of quality of life among the orphan and non-orphan children reveal that a high percentage of orphan children (66.66%) had a moderate quality of life and some of them (33.33%) had a poor quality of life, whereas a high number of non-orphan children (66.66%) had a very good quality of life and some (33.33%) had a good quality of life. No significant association was found between the quality of life and stress scores with the socio-demographic variables of orphan and non-orphan children. Conclusion: The study concluded that orphan children need to improve their quality of life and decrease their level of stress.

scholarly journals High-Speed Railway Clearance Intrusion Detection with Improved SSD Network

2019 ◽  
Vol 9 (15) ◽  
pp. 2981 ◽  
Author(s):  
Baoqing Guo ◽  
Jiafeng Shi ◽  
Liqiang Zhu ◽  
Zujun Yu
Keyword(s):  
Intrusion Detection ◽  
High Speed ◽  
Rapid Development ◽  
Single Shot ◽  
L1 Norm ◽  
Low Level ◽  
Model Size ◽  
Public Dataset ◽  
The Mean ◽  
High Level

With the rapid development of high-speed railways, any objects intruding railway clearance will do great threat to railway operations. Accurate and effective intrusion detection is very important. An original Single Shot multibox Detector (SSD) can be used to detect intruding objects except small ones. In this paper, high-level features are deconvolved to low-level and fused with original low-level features to enhance their semantic information. By this way, the mean average precision (mAP) of the improved SSD algorithm is increased. In order to decrease the parameters of the improved SSD network, the L1 norm of convolution kernel is used to prune the network. Under this criterion, both the model size and calculation load are greatly reduced within the permitted precision loss. Experiments show that the mAP of our method on PASCAL VOC public dataset and our railway datasets have increased by 2.52% and 4.74% respectively, when compared to the original SSD. With our method, the elapsed time of each frame is only 31 ms on GeForce GTX1060.

Powered Ankle-Foot Prostheses: A Survey on Sensing Systems and Control Strategies

2019 ◽  
Author(s):  
Erik Chumacero-Polanco ◽  
James Yang
Keyword(s):  
Control Strategies ◽  
Level Control ◽  
Low Level ◽  
Kinetic Information ◽  
Sensing Systems ◽  
Systems And Control ◽  
Finite State ◽  
High Level ◽  
And Control

Abstract People who have suffered a transtibial amputation show diminished ambulation and impaired quality of life. Powered ankle foot prostheses (AFP) are used to recover some mobility of transtibial amputees (TTAs). Powered AFP is an emerging technology that has great potential to improve the quality of life of TTAs with important avenues for research and development in different fields. This paper presents a survey on sensing systems and control strategies applied to powered AFPs. Sensing kinematic and kinetic information in powered AFPs is critical for control. Ankle angle position is commonly obtained via potentiometers and encoders directly installed on the joint, velocities can be estimated using numerical differentiators, and accelerations are normally obtained via inertial measurement units (IMUs). On the other hand, kinetic information is usually obtained via strain gauges and torque sensors. On the other hand, control strategies are classified as high- and low-level control. The high-level control sets the torque or position references based on pattern generators, user’s intent of motion recognition, or finite-state machine. The low-level control usually consists of linear controllers that drive the ankle’s joint position, velocity, or torque to follow an imposed reference signal. The most widely used control strategy is the one based on finite-state machines for the high-level control combined with a proportional-derivative torque control for low-level. Most designs have been experimentally assessed with acceptable results in terms of walking speed. However, some drawbacks related to powered AFP’s weight and autonomy remain to be overcome. Future research should be focused on reducing powered AFP size and weight, increasing energy efficiency, and improving both the high- and the low-level controllers in terms of efficiency and performance.

Comparison of quality of facial scars after single low-level laser therapy and combined low-level with high-level (PDL 595 nm) laser therapy

2015 ◽  
Vol 28 (4) ◽  
pp. 201-209 ◽  
Author(s):  
Jana Vranova ◽  
Eva Remlova ◽  
Helena Jelinkova ◽  
Jozef Rosina ◽  
Tatjana Dostalova
Keyword(s):  
Laser Therapy ◽  
Low Level Laser Therapy ◽  
Low Level ◽  
Low Level Laser ◽  
Level Laser ◽  
High Level

Adaptive Feature Selection for Ultrasound Image Processing and its Application to Liver Cirrhosis Detection

2013 ◽  
Vol 411-414 ◽  
pp. 1372-1376
Author(s):  
Wei Tin Lin ◽  
Shyi Chyi Cheng ◽  
Chih Lang Lin ◽  
Chen Kuei Yang
Keyword(s):  
Clustering Algorithm ◽  
Ultrasound Image ◽  
Image Features ◽  
Ultrasound Images ◽  
Analytic Hierarchy ◽  
Low Level ◽  
Adaptive Feature Selection ◽  
High Level ◽  
Objects Detection ◽  
Hierarchy Process

An approach to improve the regions of interesting (ROIs) selection accuracy automatically for medical images is proposed. The aim of the study is to select the most interesting regions of image features that good for diffuse objects detection or classification. We use the AHP (Analytic Hierarchy Process) to obtain physicians high-level diagnosis vectors and are clustered using the well-known K-Means clustering algorithm. The system also automatically extracts low-level image features for improving to detect liver diseases from ultrasound images. The weights of low-level features are adaptively updated according the feature variances in the class. Finally, the high-level diagnosis decision is made based on the high-level diagnosis vectors for the top K near neighbors from the medical experts classified database. Experimental results show the effectiveness of the system.

scholarly journals ANALISIS BUKU AJAR MARUGOTO: BAHASA DAN KEBUDAYAAN JEPANG A1 DITINJAU DARI RANAH KOGNITIF TAKSONOMI BLOOM

2018 ◽  
Vol 3 (1) ◽  
pp. 24
Author(s):  
Rakhmania Wulandari ◽  
Febi Ariani Saragih
Keyword(s):  
Bloom's Taxonomy ◽  
Data Sources ◽  
Learning Needs ◽  
Language And Culture ◽  
Low Level ◽  
Descriptive Research ◽  
Bloom’S Taxonomy ◽  
Qualitative Descriptive ◽  
High Level

Penelitian ini bertujuan untuk mengetahui kualitas isi buku ajar Marugoto: Bahasa dan Kebudayaan Jepang A1 ditinjau dari ranah kognitif taksonomi Bloom.  Kualitas buku ajar menjadi pertimbangan pengajar dalam menentukan buku ajar yang baik untuk digunakan. Menelaah kualitas buku ajar dapat dilakukan dengan menggunakan teori belajar taksonomi Bloom. Taksonomi Bloom adalah pengelompokan belajar berdasarkan tingkatan belajar. Yaitu belajar tingkat rendah yang terdiri dari kualifikasi C1 (mengingat), C2 (memahami), dan C3 (mengaplikasikan), serta belajar tingkat tinggi yang terdiri dari kualifikasi  C4 (menganalisis), C5 (mengevaluasi), dan C6 (mencipta).Penelitian ini merupakan penelitian deskriptif kualitatif. Sumber data utama adalah buku ajar Marugoto rikai dan katsudou. Analisis dilakukan dengan menganalisis bahan ajar menggunakan kualifikasi kognitif pada taksonomi Bloom. Hasil Analisis menunjukkan bahwa buku Marugoto A1 mencapai hasil yang sangat baik pada kualifikasi C1, C2, C3, C4; hasil analisis baik pada C5, dan  hasil analisis sangat kurang pada C6. Materi yang disajikan mewakili kata kerja operasioanal dalam memenuhi kebutuhan belajar tingkat rendah dengan sangat baik, namun hanya cukup mewakili kata kerja operasional dalam memenuhi kebutuhan belajar tingkat tinggi.   This research is aimed to find out the quality of Marugoto's textbook content: Japanese Language and Culture A1 from the cognitive aspects of Bloom's taxonomy. The quality of textbooks becomes the teacher's consideration in determining which textbooks are best used. Reviewing the quality of textbooks can be done using Bloom's theory of taxonomic learning. Bloom's Taxonomy is a learning grouping based on the level of learning. That is a low level study consisting of qualifications C1 (remembering), C2 (understanding), and C3 (applying), as well as a high-level learning consisting of C4 qualifying (analyzing), C5 (evaluating), and C6 (creating). is a qualitative descriptive research. The main data sources are Marugoto rikai and katsudou textbooks. The analysis was done by analyzing the teaching materials using cognitive qualifications on Bloom's taxonomy. The analysis shows that Marugoto: Language and Culture of Japan A1 achieved excellent results on qualification C1, C2, C3, C4, good analytical results on C5, and the result of analysis is very less on C6. The material presented represents operational verbs in meeting low-level learning needs very well, but only enough to represent operational verbs in meeting high-level learning needs.

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