8 research outputs found
ΠΡΠΎΠ±Π»Π΅ΠΌΡ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² Π½Π° Π°Π½Π³Π»ΠΈΠΉΡΠΊΠΎΠΌ ΡΠ·ΡΠΊΠ΅ (EMI) Π² ΡΠ½ΠΈΠ²Π΅ΡΡΠΈΡΠ΅ΡΠ°Ρ ΠΠ°Π·Π°Ρ ΡΡΠ°Π½Π°
Introduction. Fascination with English medium instruction (EMI) is fast growing in higher education institutions in non-native English-speaking countries, including Kazakhstan. The Kazakhstani government adopted a trilingual education policy in 2007 and the Bologna Process in 2010. Both these initiatives motivated universities to offer academic programmes in the English language. As a result, EMI programmes are offered in over 70 higher education institutions across Kazakhstan. In addition, there are four major Kazakhstani universities which offer academic programmes in English only. Despite the increase in the number of EMI programmes, there is a lack of empirical evidence about the difficulties and challenges faced by students in the EMI programmes. Aim. The present study aimed to investigate the nature, forms, and levels of challenges graduate students face in academic reading and writing in English and the way they cope with these challenges. The study was conducted with graduate students and faculty in 10 selected Kazakhstani universities, which offer academic programmes in EMI. Research methodology and methods. The study is based on a mixed-method design, involving an online survey and semi-structured interviews. The closed-ended questions have been analysed using SPSS software (Statistical Package for the Social Sciences). The grounded theory analysis was utilised to scrutinise open-ended questions and interview transcripts. Results and scientific novelty. The studyβs results indicated two major challenges faced by graduate students in academic reading and writing: the personal-psychological challenge and sociological challenge. The first challenge includes studentsβ previous academic backgrounds, exposure, and learning experiences. The second challenge is related to English academic culture and studentsβ worldviews, concepts, and values about English as a language and medium of instruction. As a result, graduate students experienced a lack of vocabulary, inadequate academic literacy skills, unfamiliarity with academic writing styles in English, and lack of skills to synthesise reading materials. Practical significance. Hence, this study recommends systematising English language programmes across secondary and higher education institutions to help students acquire advanced English language proficiency. Also, the study results suggest that local faculty members should be trained according to international standards in terms of their English language skills and innovative teaching methods.ΠΠ²Π΅Π΄Π΅Π½ΠΈΠ΅. ΠΠ½ΡΠ΅ΡΠ΅Ρ ΠΊ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ Π½Π° Π°Π½Π³Π»ΠΈΠΉΡΠΊΠΎΠΌ ΡΠ·ΡΠΊΠ΅ (English Medium Instruction β EMI) Π±ΡΡΡΡΠΎ ΡΠ°ΡΡΠ΅Ρ Π² Π²ΡΡΡΠΈΡ
ΡΡΠ΅Π±Π½ΡΡ
Π·Π°Π²Π΅Π΄Π΅Π½ΠΈΡΡ
ΡΡΡΠ°Π½, Π΄Π»Ρ ΠΊΠΎΡΠΎΡΡΡ
Π°Π½Π³Π»ΠΈΠΉΡΠΊΠΈΠΉ ΡΠ·ΡΠΊ Π½Π΅ ΡΠ²Π»ΡΠ΅ΡΡΡ ΡΠΎΠ΄Π½ΡΠΌ, Π²ΠΊΠ»ΡΡΠ°Ρ ΠΠ°Π·Π°Ρ
ΡΡΠ°Π½. ΠΡΠ°Π²ΠΈΡΠ΅Π»ΡΡΡΠ²ΠΎ ΡΡΡΠ°Π½Ρ ΠΏΡΠΈΠ½ΡΠ»ΠΎ ΠΏΠΎΠ»ΠΈΡΠΈΠΊΡ ΡΡΠ΅Ρ
ΡΡΠ·ΡΡΠ½ΠΎΠ³ΠΎ ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ Π² 2007 Π³ΠΎΠ΄Ρ ΠΈ ΠΠΎΠ»ΠΎΠ½ΡΠΊΠΈΠΉ ΠΏΡΠΎΡΠ΅ΡΡ Π² 2010 Π³ΠΎΠ΄Ρ. ΠΠ±Π΅ ΡΡΠΈ ΠΈΠ½ΠΈΡΠΈΠ°ΡΠΈΠ²Ρ ΠΏΠΎΠ±ΡΠ΄ΠΈΠ»ΠΈ ΡΠ½ΠΈΠ²Π΅ΡΡΠΈΡΠ΅ΡΡ ΠΏΡΠ΅Π΄Π»Π°Π³Π°ΡΡ Π°ΠΊΠ°Π΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΡ Π½Π° Π°Π½Π³Π»ΠΈΠΉΡΠΊΠΎΠΌ ΡΠ·ΡΠΊΠ΅. Π ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ΅ ΠΎΠ½ΠΈ ΠΏΠΎΡΠ²ΠΈΠ»ΠΈΡΡ Π² 70 Π²ΡΠ·Π°Ρ
ΠΠ°Π·Π°Ρ
ΡΡΠ°Π½Π°. ΠΠΎΠ»Π΅Π΅ ΡΠΎΠ³ΠΎ, Π½Π° Π΄Π°Π½Π½ΡΠΉ ΠΌΠΎΠΌΠ΅Π½Ρ Π΅ΡΡΡ ΡΠ΅ΡΡΡΠ΅ ΠΊΡΡΠΏΠ½ΡΡ
ΡΠ½ΠΈΠ²Π΅ΡΡΠΈΡΠ΅ΡΠ° Ρ Π°ΠΊΠ°Π΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ°ΠΌΠΈ ΠΈΡΠΊΠ»ΡΡΠΈΡΠ΅Π»ΡΠ½ΠΎ Π½Π° Π°Π½Π³Π»ΠΈΠΉΡΠΊΠΎΠΌ ΡΠ·ΡΠΊΠ΅. ΠΠ΅ΡΠΌΠΎΡΡΡ Π½Π° ΡΠ²Π΅Π»ΠΈΡΠ΅Π½ΠΈΠ΅ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π° ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌ EMI, ΠΎΡΡΡΡΡΡΠ²ΡΡΡ ΡΠΌΠΏΠΈΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π΄Π°Π½Π½ΡΠ΅ ΠΎ ΡΡΡΠ΄Π½ΠΎΡΡΡΡ
ΠΈ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ°Ρ
, Ρ ΠΊΠΎΡΠΎΡΡΠΌΠΈ Π² Π½ΠΈΡ
ΡΡΠ°Π»ΠΊΠΈΠ²Π°ΡΡΡΡ ΡΡΡΠ΄Π΅Π½ΡΡ. Π¦Π΅Π»Ρ. ΠΠ°Π½Π½ΠΎΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΈΠ·ΡΡΠ°Π΅Ρ ΠΏΡΠΈΡΠΎΠ΄Ρ, ΡΠΎΡΠΌΡ ΠΈ ΡΡΠΎΠ²Π½ΠΈ ΠΏΡΠΎΠ±Π»Π΅ΠΌ, Ρ ΠΊΠΎΡΠΎΡΡΠΌΠΈ ΡΡΠ°Π»ΠΊΠΈΠ²Π°ΡΡΡΡ ΠΌΠ°Π³ΠΈΡΡΡΠ°Π½ΡΡ ΠΈ Π΄ΠΎΠΊΡΠΎΡΠ°Π½ΡΡ ΠΏΡΠΈ Π°ΠΊΠ°Π΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΌ ΡΡΠ΅Π½ΠΈΠΈ ΠΈ ΠΏΠΈΡΡΠΌΠ΅ Π½Π° Π°Π½Π³Π»ΠΈΠΉΡΠΊΠΎΠΌ ΡΠ·ΡΠΊΠ΅, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΠΎ, ΠΊΠ°ΠΊ ΠΎΠ½ΠΈ ΡΠΏΡΠ°Π²Π»ΡΡΡΡΡ Ρ ΡΡΠΈΠΌΠΈ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ°ΠΌΠΈ. ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΎΡΡ ΡΡΠ΅Π΄ΠΈ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² ΠΌΠ°Π³ΠΈΡΡΡΠ°ΡΡΡΡ ΠΈ Π΄ΠΎΠΊΡΠΎΡΠ°Π½ΡΡΡΡ, Π° ΡΠ°ΠΊΠΆΠ΅ ΠΏΡΠ΅ΠΏΠΎΠ΄Π°Π²Π°ΡΠ΅Π»Π΅ΠΉ ΠΈΠ· 10 Π²ΡΠ±ΡΠ°Π½Π½ΡΡ
ΠΊΠ°Π·Π°Ρ
ΡΡΠ°Π½ΡΠΊΠΈΡ
Π²ΡΠ·ΠΎΠ², ΠΏΡΠ΅Π΄Π»Π°Π³Π°ΡΡΠΈΡ
Π°ΠΊΠ°Π΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΡ Ρ EMI. ΠΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ. ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΠ΅Ρ Π΄ΠΈΠ·Π°ΠΉΠ½ ΠΊΠΎΠΌΠ±ΠΈΠ½ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ², Π²ΠΊΠ»ΡΡΠ°ΡΡΠΈΠΉ ΠΎΠ½Π»Π°ΠΉΠ½-ΠΎΠΏΡΠΎΡ ΠΈ ΠΏΠΎΠ»ΡΡΡΡΡΠΊΡΡΡΠΈΡΠΎΠ²Π°Π½Π½ΡΠ΅ ΠΈΠ½ΡΠ΅ΡΠ²ΡΡ. ΠΠ°ΠΊΡΡΡΡΠ΅ Π²ΠΎΠΏΡΠΎΡΡ Π±ΡΠ»ΠΈ ΠΏΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Ρ Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΏΠ°ΠΊΠ΅ΡΠ° (SPSS). ΠΠ΅ΡΠΎΠ΄ ΠΎΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½Π½ΠΎΠΉ ΡΠ΅ΠΎΡΠΈΠΈ Π±ΡΠ» ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ Π΄Π»Ρ ΠΏΠΎΠ΄ΡΠΎΠ±Π½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΠΎΡΠΊΡΡΡΡΡ
Π²ΠΎΠΏΡΠΎΡΠΎΠ² ΠΈ ΡΡΠ°Π½ΡΠΊΡΠΈΠΏΡΠΎΠ² ΠΈΠ½ΡΠ΅ΡΠ²ΡΡ. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΈ Π½Π°ΡΡΠ½Π°Ρ Π½ΠΎΠ²ΠΈΠ·Π½Π°. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π²ΡΡΠ²ΠΈΠ»ΠΈ Π΄Π²Π΅ ΠΎΡΠ½ΠΎΠ²Π½ΡΠ΅ ΠΏΡΠΎΠ±Π»Π΅ΠΌΡ, Ρ ΠΊΠΎΡΠΎΡΡΠΌΠΈ ΡΡΠ°Π»ΠΊΠΈΠ²Π°ΡΡΡΡ ΡΡΡΠ΄Π΅Π½ΡΡ ΠΏΡΠΈ Π°ΠΊΠ°Π΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΌ ΡΡΠ΅Π½ΠΈΠΈ ΠΈ ΠΏΠΈΡΡΠΌΠ΅: Π»ΠΈΡΠ½ΠΎΡΡΠ½ΠΎ-ΠΏΡΠΈΡ
ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠ°Ρ ΠΈ ΡΠΎΡΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠ°Ρ. ΠΠ΅ΡΠ²Π°Ρ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ° Π²ΠΊΠ»ΡΡΠ°Π΅Ρ Π² ΡΠ΅Π±Ρ ΠΏΡΠ΅Π΄ΡΠ΄ΡΡΠΈΠΉ Π°ΠΊΠ°Π΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΎΠΏΡΡ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ², Π° ΡΠ°ΠΊΠΆΠ΅ ΠΎΠΏΡΡ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ. ΠΡΠΎΡΠ°Ρ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ° ΡΠ²ΡΠ·Π°Π½Π° Ρ Π°Π½Π³Π»ΠΈΠΉΡΠΊΠΎΠΉ Π°ΠΊΠ°Π΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΊΡΠ»ΡΡΡΡΠΎΠΉ ΠΈ ΠΌΠΈΡΠΎΠ²ΠΎΠ·Π·ΡΠ΅Π½ΠΈΠ΅ΠΌ, ΠΊΠΎΠ½ΡΠ΅ΠΏΡΠΈΡΠΌΠΈ ΠΈ ΡΠ΅Π½Π½ΠΎΡΡΡΠΌΠΈ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² Π² ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠΈ Π°Π½Π³Π»ΠΈΠΉΡΠΊΠΎΠ³ΠΎ ΡΠ·ΡΠΊΠ° ΠΊΠ°ΠΊ ΡΠ·ΡΠΊΠ° ΠΈ ΡΡΠ΅Π΄ΡΡΠ²Π° ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ. Π ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ΅ ΡΡΡΠ΄Π΅Π½ΡΡ ΡΡΠΎΠ»ΠΊΠ½ΡΠ»ΠΈΡΡ ΡΠΎ ΡΠ»Π΅Π΄ΡΡΡΠΈΠΌΠΈ ΡΡΡΠ΄Π½ΠΎΡΡΡΠΌΠΈ: Π½Π΅Ρ
Π²Π°ΡΠΊΠ° ΡΠ»ΠΎΠ²Π°ΡΠ½ΠΎΠ³ΠΎ Π·Π°ΠΏΠ°ΡΠ°, Π½Π΅Π΄ΠΎΡΡΠ°ΡΠΎΡΠ½ΡΠ΅ Π½Π°Π²ΡΠΊΠΈ Π°ΠΊΠ°Π΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ Π³ΡΠ°ΠΌΠΎΡΠ½ΠΎΡΡΠΈ, Π½Π΅Π·Π½Π°Π½ΠΈΠ΅ ΡΡΠΈΠ»Π΅ΠΉ Π°ΠΊΠ°Π΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΏΠΈΡΡΠΌΠ° Π½Π° Π°Π½Π³Π»ΠΈΠΉΡΠΊΠΎΠΌ ΡΠ·ΡΠΊΠ΅ ΠΈ ΠΎΡΡΡΡΡΡΠ²ΠΈΠ΅ Π½Π°Π²ΡΠΊΠΎΠ² ΡΠΈΠ½ΡΠ΅Π·ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΡΠΎΡΠΈΡΠ°Π½Π½ΠΎΠ³ΠΎ. ΠΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠ°Ρ Π·Π½Π°ΡΠΈΠΌΠΎΡΡΡ. Π’Π°ΠΊΠΈΠΌ ΠΎΠ±ΡΠ°Π·ΠΎΠΌ, Π΄Π°Π½Π½ΠΎΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠ΅ΠΊΠΎΠΌΠ΅Π½Π΄ΡΠ΅Ρ ΡΠΈΡΡΠ΅ΠΌΠ°ΡΠΈΠ·ΠΈΡΠΎΠ²Π°ΡΡ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΡ ΠΈΠ·ΡΡΠ΅Π½ΠΈΡ Π°Π½Π³Π»ΠΈΠΉΡΠΊΠΎΠ³ΠΎ ΡΠ·ΡΠΊΠ° Π² ΡΡΠ΅Π΄Π½ΠΈΡ
ΠΈ Π²ΡΡΡΠΈΡ
ΡΡΠ΅Π±Π½ΡΡ
Π·Π°Π²Π΅Π΄Π΅Π½ΠΈΡΡ
, ΡΡΠΎΠ±Ρ ΠΏΠΎΠΌΠΎΡΡ ΡΡΠ°ΡΠΈΠΌΡΡ ΠΎΠ²Π»Π°Π΄Π΅ΡΡ Π°Π½Π³Π»ΠΈΠΉΡΠΊΠΈΠΌ ΡΠ·ΡΠΊΠΎΠΌ Π½Π° ΠΏΡΠΎΠ΄Π²ΠΈΠ½ΡΡΠΎΠΌ ΡΡΠΎΠ²Π½Π΅. ΠΡΠΎΠΌΠ΅ ΡΠΎΠ³ΠΎ, ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΏΠΎΠΊΠ°Π·ΡΠ²Π°ΡΡ, ΡΡΠΎ ΠΌΠ΅ΡΡΠ½ΡΠ΅ ΠΏΡΠ΅ΠΏΠΎΠ΄Π°Π²Π°ΡΠ΅Π»ΠΈ Π΄ΠΎΠ»ΠΆΠ½Ρ Π±ΡΡΡ ΠΎΠ±ΡΡΠ΅Π½Ρ Π² ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΈΠΈ Ρ ΠΌΠ΅ΠΆΠ΄ΡΠ½Π°ΡΠΎΠ΄Π½ΡΠΌΠΈ ΡΡΠ°Π½Π΄Π°ΡΡΠ°ΠΌΠΈ, Π²ΠΊΠ»ΡΡΠ°Ρ Π½Π°Π²ΡΠΊΠΈ Π°Π½Π³Π»ΠΈΠΉΡΠΊΠΎΠ³ΠΎ ΡΠ·ΡΠΊΠ° ΠΈ ΠΈΠ½Π½ΠΎΠ²Π°ΡΠΈΠΎΠ½Π½ΡΠ΅ ΠΌΠ΅ΡΠΎΠ΄Ρ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ.The research study is funded by Nazarbayev University under Collaborative Research Programme Grant β 021220CRP1322.ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠΈΠ½Π°Π½ΡΠΈΡΡΠ΅ΡΡΡ ΠΠ°Π·Π°ΡΠ±Π°Π΅Π² Π£Π½ΠΈΠ²Π΅ΡΡΠΈΡΠ΅ΡΠΎΠΌ Π² ΡΠ°ΠΌΠΊΠ°Ρ
Π³ΡΠ°Π½ΡΠ° ΠΡΠΎΠ³ΡΠ°ΠΌΠΌΡ ΡΠΎΠ²ΠΌΠ΅ΡΡΠ½ΡΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ β 021220CRP1322
Analysis of K-ras codon 12 and TP53 mutations in patients with advanced colorectal carcinoma
Background. Colorectal cancer (CRC) is one of the most common types of cancer, affecting 3 - 5% of the global population. K-ras protooncogene and TP53 tumour suppressor gene mutations are among the most common genetic alterations detected in advanced colorectaltumours.Objective. To investigate the role of K-ras codon 12 and TP53 exons 5 - 9 mutations in late-stage CRC patients.Methods. Blood samples were collected from 249 CRC patients, of whom 147 presented with advanced carcinoma. K-ras codon 12 mutations were analysed using polymerase chain reaction-restriction fragment length polymorphism, while direct sequencing was used in screening for TP53 exons 5 - 9 mutations.Results. No significant changes were observed in TP53 exons 5 - 9, except for two cases in which nucleotide replacements were observed in the non-coding regions in intron 4 (c.376-19C>T) and intron 9 (c.993+12T>C). Heterozygous mutations in K-ras codon 12 were observed in 79 individuals suffering from advanced CRC (53.7%). Colon and rectal tumours were equally distributed among the heterozygotes, but colon tumours were mostly present in wild-type homozygotes (84.6%). There was also a predominance of Caucasians among heterozygotes and a predominance of Asians among the wild-type homozygotes.Conclusion. Analysis of peripheral blood samples of CRC patients suffering from advanced carcinoma has prognostic value only for K-ras codon 12 mutations, and not for TP53 mutations
Segmentation of Aerospace Images by A Non-standard Approach Using Informative Textural Features
The article presents an analysis of a non-standard approach to the segmentation of textural areas in aerospace images. The question of the applicability of sets of textural features for the analysis of experimental data is being investigated to identify characteristic areas on aerospace images that in the future it will be possible to identify types of crops, weeds, diseases, and pests. The selection of suitable algorithms was carried out and appropriate software tools were created on Matlab 2021a and in the software package for statistical analysis Statistica 12.
The main way to extract information is to decrypt images, which are the main carrier of information about the underlying surface. The main tasks of texture area analysis include selection and formation of features describing textural differences; selection and segmentation of textural areas; classification of textural areas; identification of an object by texture.
To solve the tasks, spectral brightness coefficient (SBC), Normalized Difference Vegetation Index (NDVI), textural features of various crops and weeds. Much attention will be paid to the development of software tools that allow the selection of features describing textural differences for the segmentation of textural areas into subdomains. That is the question of the applicability of sets of textural features and other parameters for the analysis of experimental data to identify types of soils and soils, vegetation types, humidity, crop damage in aerospace images will be resolved.
This approach is universal and has great potential for identifying objects using image clustering. To identify the boundaries of areas with different properties of the image under study, images of the same surface area taken at different times are considered
Trace element biomonitoring in hair and blood of occupationally unexposed population residing in polluted areas of East Kazakhstan and Pavlodar regions
Introduction: Eastern and North-Eastern regions of Kazakhstan are considered to be environmentally disadvantaged due to industrial pollution and activity of the former Semipalatinsk Nuclear Test Site. Ferrous metallurgy is represented by the world's largest ferroalloy plant located in Aksu. In addition to a ferroalloy plant, Aksu is the home for the largest thermal power plant in Kazakhstan. Objective: Biomonitoring of 31 hair and blood trace elements (Ag, Ba, Be, Bi, Cs, Co, Ce, Cr, Cu, Eu, Gd, Hf, In, La, Li, Mn, Mo, Nb, Nd, Pb, Sc, Sn, Tl, Th, U, V, W, Y, Yb, Zn, and Zr) in non-occupationally exposed population residing in polluted areas of East Kazakhstan and Pavlodar regions. Methods: Five case groups, residing in the vicinity to the former Semipalatinsk Nuclear Test Site (Akzhar, Borodulikha, and Karaul) or in proximity to industrial plants (Aksu and Ust-Kamenogorsk) have been assessed vs. controls from a rural settlement in Kurchum. In total, 204 hair and blood samples were analyzed by inductively coupled plasma mass spectrometry. Results: The observed blood concentrations of trace elements were in agreement with earlier studies on residents of industrially polluted areas. Elevated levels of blood Ba, Mn, Pb, V, and Zn were detected in residents of Aksu and Ust-Kamenogorsk. The elemental composition of head hair was characterized by greater stability between the study sites. Conclusion: Residency near the former Semipalatinsk Test Site could be considered as safe, while the environmental status of industrial settlements appears to be rather adverse. Β© 2019 Elsevier Gmb